STEIN Fireside Podcast: When the Lab Meets the Clinic: Inside Mayo Clinic’s Neurology Innovation Engine

1
00:00:08,675 --> 00:00:10,210
Hi, and welcome to another episode

2
00:00:10,210 --> 00:00:11,478
of STEIN Fireside Podcast.

3
00:00:11,811 --> 00:00:13,813
We're here today with Dr. Sean Pittock,

4
00:00:13,813 --> 00:00:15,215
who is the chair of

5
00:00:15,215 --> 00:00:15,849
neurology at Mayo Clinic

6
00:00:16,282 --> 00:00:17,183
and a neuroimmunologist,

7
00:00:17,784 --> 00:00:19,719
and Dr. Nathan Staff, who is a

8
00:00:19,719 --> 00:00:20,687
neuromuscular neurologist

9
00:00:20,854 --> 00:00:22,489
and the chair of the Mayo

10
00:00:22,489 --> 00:00:23,857
Neurology Research Committee.

11
00:00:24,791 --> 00:00:26,226
And so thanks for coming on today.

12
00:00:26,860 --> 00:00:27,861
Hope we'll have a nice chat.

13
00:00:28,294 --> 00:00:29,396
We'll give you your steins.

14
00:00:30,363 --> 00:00:30,930
Thank you very much.

15
00:00:30,964 --> 00:00:31,664
You can keep that.

16
00:00:32,198 --> 00:00:33,366
Thank you, appreciate it.

17
00:00:33,733 --> 00:00:34,367
Great to be here.

18
00:00:34,601 --> 00:00:35,935
We'd like to talk a little bit just about

19
00:00:36,036 --> 00:00:37,270
how you kind of got

20
00:00:37,270 --> 00:00:37,904
interested in medicine

21
00:00:38,271 --> 00:00:39,773
and then got interested, I

22
00:00:39,773 --> 00:00:40,774
guess, in the research aspects.

23
00:00:41,474 --> 00:00:43,009
Well, as you probably

24
00:00:43,009 --> 00:00:43,943
know from my accent,

25
00:00:43,943 --> 00:00:45,178
I'm from Dublin, Ireland.

26
00:00:46,312 --> 00:00:47,680
I've been in Minnesota for

27
00:00:47,680 --> 00:00:49,749
26 years, came over in 1999.

28
00:00:51,351 --> 00:00:52,552
I really started off

29
00:00:52,552 --> 00:00:53,953
with a passionate interest

30
00:00:54,187 --> 00:00:55,955
in psychiatry, actually.

31
00:00:56,489 --> 00:00:57,690
I was reading a little bit of Freud

32
00:00:57,791 --> 00:00:58,324
when I was in high

33
00:00:58,324 --> 00:00:59,893
school, got really into it.

34
00:01:00,627 --> 00:01:02,495
And I always decided that I

35
00:01:02,495 --> 00:01:03,396
was gonna be a psychiatrist.

36
00:01:04,030 --> 00:01:05,732
So in Ireland, you go

37
00:01:05,732 --> 00:01:06,966
straight from high school,

38
00:01:07,033 --> 00:01:08,268
straight into medicine.

39
00:01:08,535 --> 00:01:10,870
And I started medicine at

40
00:01:10,870 --> 00:01:12,005
University College Dublin.

41
00:01:12,605 --> 00:01:13,907
Really loved it and

42
00:01:13,907 --> 00:01:15,708
loved my psychiatry courses.

43
00:01:16,009 --> 00:01:17,844
But when I stepped into

44
00:01:17,844 --> 00:01:19,045
this psychiatric hospital

45
00:01:19,045 --> 00:01:21,214
to do my rotations, it was at that point

46
00:01:21,214 --> 00:01:22,148
that I suddenly realized

47
00:01:22,148 --> 00:01:24,250
that psychiatry was not for me,

48
00:01:24,951 --> 00:01:25,852
neurology was for me.

49
00:01:25,885 --> 00:01:27,287
And so I ended up in neurology,

50
00:01:27,287 --> 00:01:30,390
very happy that I continued in that vein.

51
00:01:30,990 --> 00:01:32,926
So that's how I ended up in neurology.

52
00:01:33,293 --> 00:01:34,327
In Ireland, you go

53
00:01:34,327 --> 00:01:35,428
straight from medical school

54
00:01:35,695 --> 00:01:37,597
into either medicine or surgery.

55
00:01:38,031 --> 00:01:39,265
And your internship, you

56
00:01:39,265 --> 00:01:41,835
have to do half your time

57
00:01:41,835 --> 00:01:42,735
in surgery and half

58
00:01:42,735 --> 00:01:44,070
your time in medicine.

59
00:01:44,270 --> 00:01:46,306
So I did six months of

60
00:01:46,306 --> 00:01:48,241
urology as a surgical intern,

61
00:01:48,875 --> 00:01:50,743
admitting 26 patients for

62
00:01:50,743 --> 00:01:53,446
urological surgical procedures

63
00:01:54,214 --> 00:01:56,249
in one day and realized very quickly

64
00:01:56,249 --> 00:01:57,984
that urology was not for me.

65
00:01:59,252 --> 00:02:01,354
So then did internal

66
00:02:01,354 --> 00:02:03,123
medicine, went into neurology,

67
00:02:03,323 --> 00:02:04,023
didn't really feel I

68
00:02:04,023 --> 00:02:05,191
was getting an education,

69
00:02:05,492 --> 00:02:06,726
a good education in Ireland.

70
00:02:06,726 --> 00:02:07,460
It's very much you

71
00:02:07,460 --> 00:02:08,394
learn from your mistakes

72
00:02:08,394 --> 00:02:09,329
on your patients.

73
00:02:10,563 --> 00:02:12,899
Whereas I really looked and was looking

74
00:02:12,899 --> 00:02:14,968
for a didactic kind of course where,

75
00:02:14,968 --> 00:02:15,735
I know a place where I could

76
00:02:15,735 --> 00:02:17,437
be taught and learn better.

77
00:02:17,437 --> 00:02:20,607
And so I interviewed throughout the US

78
00:02:20,807 --> 00:02:21,774
and decided that Mayo

79
00:02:21,774 --> 00:02:22,509
Clinic was the place

80
00:02:22,675 --> 00:02:23,843
that I wanted to do my training.

81
00:02:23,843 --> 00:02:27,280
And I started my internship here in 1999,

82
00:02:27,914 --> 00:02:28,715
so many years ago.

83
00:02:29,249 --> 00:02:30,416
And having looked back,

84
00:02:30,416 --> 00:02:31,518
really enjoyed it, love Mayo.

85
00:02:32,452 --> 00:02:33,553
Did you know, at what point did you know

86
00:02:33,553 --> 00:02:35,188
you wanted to go into MS or immunology?

87
00:02:35,889 --> 00:02:37,257
Yeah, well that's a story.

88
00:02:37,590 --> 00:02:39,225
So I did, when I was

89
00:02:39,225 --> 00:02:40,393
doing neurology in Ireland,

90
00:02:40,393 --> 00:02:41,761
I decided I was gonna do stroke.

91
00:02:42,395 --> 00:02:44,130
At that time, TPA was coming out,

92
00:02:44,130 --> 00:02:45,365
it was kind of somewhat exciting.

93
00:02:46,399 --> 00:02:50,470
And I also was wanting to get away

94
00:02:50,570 --> 00:02:52,672
from the armchair neurologist concept.

95
00:02:53,373 --> 00:02:54,474
Didn't like that, I'm

96
00:02:54,474 --> 00:02:55,975
much more of a gung ho guy.

97
00:02:56,376 --> 00:02:57,644
And so I thought, yeah, I can do

98
00:02:57,644 --> 00:02:59,512
some interventional kind of work here.

99
00:03:00,547 --> 00:03:01,514
But when I came here,

100
00:03:01,514 --> 00:03:03,650
started to work and learn

101
00:03:04,183 --> 00:03:05,785
in the residency program at Mayo,

102
00:03:07,187 --> 00:03:08,454
I became interested

103
00:03:08,454 --> 00:03:10,023
just by being a resident

104
00:03:10,256 --> 00:03:13,092
and watching and learning from the staff

105
00:03:13,326 --> 00:03:15,194
that autoimmune neurology or

106
00:03:15,194 --> 00:03:16,729
neurominology was of interest.

107
00:03:16,729 --> 00:03:18,064
And so I knocked on Van

108
00:03:18,064 --> 00:03:19,866
de Lenden's door in her lab

109
00:03:19,933 --> 00:03:22,669
and said, hi, I'm a second year resident,

110
00:03:22,669 --> 00:03:24,370
could I do some projects with you?

111
00:03:24,370 --> 00:03:25,505
And she said, yep, come in.

112
00:03:26,206 --> 00:03:27,473
And I started off that way,

113
00:03:27,473 --> 00:03:28,608
she gave me a small project

114
00:03:28,608 --> 00:03:30,877
to do on a rare perineoplastic disease,

115
00:03:31,511 --> 00:03:33,046
which I did, and I did well.

116
00:03:33,479 --> 00:03:34,914
And then she gave me another project.

117
00:03:34,914 --> 00:03:36,216
And then I happened

118
00:03:36,216 --> 00:03:37,417
to be very, very lucky.

119
00:03:38,685 --> 00:03:41,020
I was in the lab working with her

120
00:03:41,988 --> 00:03:43,323
at the time of the discovery

121
00:03:43,323 --> 00:03:44,757
of the water channel antibody,

122
00:03:44,757 --> 00:03:45,391
which is the first

123
00:03:45,391 --> 00:03:47,627
ever antibody biomarker

124
00:03:47,794 --> 00:03:49,562
of an MS-like illness.

125
00:03:50,463 --> 00:03:53,566
And I helped out in that project,

126
00:03:54,234 --> 00:03:54,867
managed to get an

127
00:03:54,867 --> 00:03:56,469
authorship on that discovery paper,

128
00:03:56,469 --> 00:03:58,705
and I worked on that disease for 25 years

129
00:03:59,706 --> 00:04:01,207
and still working on it.

130
00:04:02,275 --> 00:04:02,675
Got it.

131
00:04:03,543 --> 00:04:05,044
Well, Nathan, tell us a

132
00:04:05,044 --> 00:04:06,379
little bit about your journey

133
00:04:06,379 --> 00:04:07,413
as far as how you got

134
00:04:07,413 --> 00:04:08,681
interested in medicine and--

135
00:04:08,748 --> 00:04:10,984
Yeah, I mean, a lot less ocean story

136
00:04:10,984 --> 00:04:12,252
than what Sean had to provide.

137
00:04:13,186 --> 00:04:15,488
I'm a Midwest person, so

138
00:04:15,488 --> 00:04:16,356
I grew up in Wisconsin,

139
00:04:16,889 --> 00:04:18,091
went to the University of

140
00:04:18,091 --> 00:04:18,791
Minnesota for undergrad,

141
00:04:20,093 --> 00:04:22,228
always liked biology growing up,

142
00:04:22,629 --> 00:04:24,931
always digging in the

143
00:04:24,931 --> 00:04:26,232
dirt, playing in the fields,

144
00:04:26,866 --> 00:04:29,302
playing with bugs, got to college

145
00:04:29,469 --> 00:04:31,371
and decided that I liked neuro things,

146
00:04:31,371 --> 00:04:34,607
kind of also reading books about the mind

147
00:04:34,741 --> 00:04:37,510
and neurophysiology and things like that.

148
00:04:37,543 --> 00:04:38,144
Where was college?

149
00:04:39,312 --> 00:04:39,879
University of Minnesota.

150
00:04:40,513 --> 00:04:41,848
Wanted to start doing research,

151
00:04:42,048 --> 00:04:43,916
interested in trying to

152
00:04:43,916 --> 00:04:45,585
decide whether to do a PhD or MD,

153
00:04:46,486 --> 00:04:49,389
ended up in a retinal physiology lab

154
00:04:49,956 --> 00:04:52,358
and did work with some of the first

155
00:04:52,358 --> 00:04:53,593
confocal microscopes

156
00:04:53,693 --> 00:04:56,496
and did some electrophysiologies,

157
00:04:57,263 --> 00:04:59,065
impaling retinal ganglia

158
00:04:59,065 --> 00:05:01,134
cells, which was a lot of fun.

159
00:05:01,901 --> 00:05:03,536
And that kind of combined

160
00:05:03,536 --> 00:05:05,805
with interest in ultimately

161
00:05:06,606 --> 00:05:07,774
having something practical

162
00:05:07,774 --> 00:05:09,442
led me to MD-PhD program.

163
00:05:10,543 --> 00:05:11,144
I did that at

164
00:05:11,144 --> 00:05:13,913
Northwestern, really enjoyed that,

165
00:05:13,946 --> 00:05:17,050
spent four and a half years doing my PhD.

166
00:05:18,051 --> 00:05:20,420
I did patch clamp neurophysiology

167
00:05:20,853 --> 00:05:23,890
in slices of rat hippocampus.

168
00:05:24,490 --> 00:05:26,225
So we would kind of claim

169
00:05:26,225 --> 00:05:27,593
to fame in that laboratory,

170
00:05:27,593 --> 00:05:28,795
which was Nelson's, Bruce's

171
00:05:28,795 --> 00:05:30,563
laboratory would be to patch

172
00:05:31,097 --> 00:05:34,067
upon the soma of a pyramidal neuron

173
00:05:34,067 --> 00:05:34,901
and then also on the

174
00:05:34,901 --> 00:05:36,235
long apical dendrite,

175
00:05:36,536 --> 00:05:38,438
300 microns away from the cell body

176
00:05:39,138 --> 00:05:40,173
and look at the

177
00:05:40,173 --> 00:05:42,008
conductances and voltage changes

178
00:05:42,341 --> 00:05:44,110
that would happen throughout that cell

179
00:05:44,110 --> 00:05:45,545
and correlate that

180
00:05:45,545 --> 00:05:47,914
with learning and memory

181
00:05:47,914 --> 00:05:50,216
sort of phenomenology such

182
00:05:50,216 --> 00:05:51,551
as long-term potentiation.

183
00:05:52,352 --> 00:05:53,786
And at that point, trying to figure out,

184
00:05:54,353 --> 00:05:55,488
I knew I was gonna, you know,

185
00:05:55,488 --> 00:05:56,656
I finished up medical school,

186
00:05:56,656 --> 00:05:57,824
knew I was gonna do residency,

187
00:05:58,491 --> 00:05:59,225
wasn't sure whether I

188
00:05:59,225 --> 00:06:00,760
was gonna do neurology,

189
00:06:00,760 --> 00:06:01,627
neurosurgery,

190
00:06:02,795 --> 00:06:05,465
neuropsychiatry, neuroradiology.

191
00:06:06,232 --> 00:06:07,033
Didn't really like my

192
00:06:07,033 --> 00:06:08,534
neurology hospital experience.

193
00:06:09,669 --> 00:06:11,204
So I was leaning toward neuroradiology

194
00:06:11,771 --> 00:06:13,606
and then I did family medicine

195
00:06:14,006 --> 00:06:16,075
and that got me back to neurology

196
00:06:16,075 --> 00:06:17,043
because I really liked

197
00:06:17,043 --> 00:06:18,111
the outpatient setting

198
00:06:18,111 --> 00:06:20,246
and the relationships with patients,

199
00:06:21,047 --> 00:06:22,181
getting to know them.

200
00:06:22,615 --> 00:06:26,986
And then residency, it was, we had a

201
00:06:26,986 --> 00:06:28,221
small kid at the time.

202
00:06:28,221 --> 00:06:29,021
So we're like wanting

203
00:06:29,021 --> 00:06:30,289
to stay close to family,

204
00:06:30,289 --> 00:06:31,657
my wife's from the Twin Cities.

205
00:06:32,425 --> 00:06:34,827
So we applied in the Midwest

206
00:06:34,827 --> 00:06:37,330
and Mayo was by and far away

207
00:06:38,331 --> 00:06:41,868
the best program at that time and still.

208
00:06:43,035 --> 00:06:44,771
So ended up coming to Mayo for training

209
00:06:44,937 --> 00:06:47,807
and ended up getting interested in,

210
00:06:48,408 --> 00:06:49,575
thought I was gonna go do MS.

211
00:06:50,343 --> 00:06:51,611
You may have called, I was

212
00:06:51,611 --> 00:06:52,945
hopping around saying hello

213
00:06:52,945 --> 00:06:53,946
to all the MS people,

214
00:06:53,946 --> 00:06:55,748
even did an MS project during residency.

215
00:06:56,582 --> 00:06:59,418
But then I did EMG and it

216
00:06:59,418 --> 00:07:00,553
brought me back to physiology

217
00:07:01,053 --> 00:07:02,789
and the electrode and the

218
00:07:02,789 --> 00:07:06,025
electricity and I was hooked.

219
00:07:06,092 --> 00:07:07,593
So I switched over to neuromuscular

220
00:07:07,994 --> 00:07:10,463
and haven't looked back since then.

221
00:07:10,863 --> 00:07:14,133
So both you guys actually measure EMGs,

222
00:07:14,133 --> 00:07:15,735
you do it in movement, you do it in

223
00:07:15,735 --> 00:07:16,569
neuromuscular disorders.

224
00:07:17,303 --> 00:07:19,806
To the neurosurgeon, in my

225
00:07:19,806 --> 00:07:22,008
mind, this is like the same thing

226
00:07:22,008 --> 00:07:23,576
but I know that for you

227
00:07:23,576 --> 00:07:24,610
guys, it's very different.

228
00:07:24,911 --> 00:07:26,679
Could you explain to us

229
00:07:26,679 --> 00:07:29,182
sort of how the types of tests

230
00:07:29,182 --> 00:07:30,149
that you do with patients

231
00:07:30,149 --> 00:07:31,451
are different from one another

232
00:07:32,084 --> 00:07:34,854
and then the kinds of functions

233
00:07:34,854 --> 00:07:36,789
that you're both looking at?

234
00:07:37,390 --> 00:07:41,227
So for neuromuscular EMG

235
00:07:41,227 --> 00:07:42,261
and he can talk about this,

236
00:07:42,595 --> 00:07:44,664
it's a very detailed and

237
00:07:44,664 --> 00:07:47,366
kind of a smaller region

238
00:07:47,366 --> 00:07:48,334
that you're looking at at a time.

239
00:07:48,801 --> 00:07:50,069
For what I do with EMG,

240
00:07:50,069 --> 00:07:51,804
it's really either surface EMG

241
00:07:52,738 --> 00:07:54,907
or we do some needle EMG, calligraphy.

242
00:07:54,907 --> 00:07:55,541
Can you explain what

243
00:07:55,541 --> 00:07:56,576
you mean by surface EMG?

244
00:07:56,909 --> 00:07:57,944
So with the surface EMG,

245
00:07:58,144 --> 00:07:59,245
you're recording the muscles'

246
00:07:59,245 --> 00:08:00,513
electroactivity with stickers.

247
00:08:00,847 --> 00:08:02,548
So basically, a surface electrode,

248
00:08:02,548 --> 00:08:03,716
it's kind of like an EKG electrode

249
00:08:03,716 --> 00:08:05,284
positioned over the muscle

250
00:08:06,018 --> 00:08:07,320
and then a needle EMG would

251
00:08:07,320 --> 00:08:08,788
be just one of the electrodes

252
00:08:08,788 --> 00:08:09,622
at the tip of a needle and

253
00:08:09,622 --> 00:08:11,157
you put that into the muscle

254
00:08:11,157 --> 00:08:11,891
and so you get a

255
00:08:11,891 --> 00:08:13,092
higher fidelity recording.

256
00:08:13,659 --> 00:08:14,293
But either way, what

257
00:08:14,293 --> 00:08:15,661
I'm more interested in is

258
00:08:16,395 --> 00:08:17,029
the activity in

259
00:08:17,029 --> 00:08:18,364
multiple EMG channels at once.

260
00:08:18,965 --> 00:08:20,233
So for example, in tremor,

261
00:08:20,233 --> 00:08:21,567
you may see a contraction

262
00:08:21,567 --> 00:08:22,768
of an agonist and antagonist

263
00:08:22,768 --> 00:08:24,003
in a certain pattern together

264
00:08:24,537 --> 00:08:29,375
or in dystonia, whereas, and I'm looking

265
00:08:29,542 --> 00:08:30,009
at the overall

266
00:08:30,009 --> 00:08:31,544
pattern and the overall flow

267
00:08:31,644 --> 00:08:32,411
between the muscles,

268
00:08:32,411 --> 00:08:33,446
whereas in your case,

269
00:08:33,980 --> 00:08:36,048
you're looking at a single motor unit.

270
00:08:36,749 --> 00:08:38,918
Yeah, and as you probably remember,

271
00:08:39,352 --> 00:08:40,353
we went through clinical

272
00:08:40,353 --> 00:08:41,921
neurophysiology at the same time.

273
00:08:41,954 --> 00:08:42,588
Yeah, we were

274
00:08:42,588 --> 00:08:44,891
co-residents and did the EMG--

275
00:08:45,558 --> 00:08:46,125
Train at the same time.

276
00:08:46,125 --> 00:08:47,026
Train at the same time, yeah.

277
00:08:47,793 --> 00:08:48,561
Diverged a little bit.

278
00:08:49,896 --> 00:08:50,563
But yeah, so I mean,

279
00:08:50,563 --> 00:08:51,264
there's two main parts

280
00:08:51,264 --> 00:08:52,632
of the EMG study.

281
00:08:52,632 --> 00:08:53,566
There's the nerve conduction

282
00:08:53,566 --> 00:08:55,534
study where we shock nerves

283
00:08:55,768 --> 00:08:57,303
and record potentials

284
00:08:57,303 --> 00:08:58,671
either over a traveling wave

285
00:08:58,838 --> 00:08:59,472
through a sensory

286
00:08:59,472 --> 00:09:01,807
nerve or kind of magnified

287
00:09:01,974 --> 00:09:03,809
through the voltage changes that happen

288
00:09:03,809 --> 00:09:04,810
when a muscle contracts.

289
00:09:06,078 --> 00:09:07,446
And we get information about

290
00:09:07,446 --> 00:09:10,283
the strength of the fidelity

291
00:09:10,283 --> 00:09:11,183
of the axon.

292
00:09:11,984 --> 00:09:13,786
Is it a full axon response

293
00:09:13,786 --> 00:09:15,755
or is it slowed in some way

294
00:09:15,755 --> 00:09:17,223
in its conduction, which gives us

295
00:09:17,223 --> 00:09:18,491
insights as to damage

296
00:09:18,491 --> 00:09:19,992
to the axons or the

297
00:09:19,992 --> 00:09:21,727
myelin within the nerve.

298
00:09:22,762 --> 00:09:24,463
And then the second part of the test is,

299
00:09:24,964 --> 00:09:25,932
as Brian was mentioning,

300
00:09:25,932 --> 00:09:27,166
you stick a knee electrode

301
00:09:27,366 --> 00:09:28,534
directly into a muscle

302
00:09:28,534 --> 00:09:30,236
and there we can get down

303
00:09:30,236 --> 00:09:31,304
to the resolution of

304
00:09:31,304 --> 00:09:33,372
single myofibrils and activity

305
00:09:33,372 --> 00:09:34,840
that are happening within that.

306
00:09:35,841 --> 00:09:36,742
They can tell us a

307
00:09:36,742 --> 00:09:37,944
little more detail about,

308
00:09:38,511 --> 00:09:39,812
is there damage to the nerve,

309
00:09:39,812 --> 00:09:41,647
is there damage to the muscle.

310
00:09:42,715 --> 00:09:44,083
And as you know,

311
00:09:44,083 --> 00:09:45,451
every muscle's innervated

312
00:09:45,451 --> 00:09:46,419
by different nerves, so

313
00:09:46,419 --> 00:09:47,186
it can kind of tell us

314
00:09:47,186 --> 00:09:47,787
where in the nervous

315
00:09:47,787 --> 00:09:49,088
system the problem might be.

316
00:09:49,088 --> 00:09:49,922
Is it a length dependent

317
00:09:49,922 --> 00:09:51,891
process where things are bad

318
00:09:51,891 --> 00:09:52,825
out in the feet and get

319
00:09:52,825 --> 00:09:54,293
normal more proximally

320
00:09:54,627 --> 00:09:56,395
into the thighs or is it

321
00:09:56,395 --> 00:09:57,530
something at the root level

322
00:09:57,630 --> 00:09:59,198
where say for example,

323
00:09:59,198 --> 00:10:00,967
the fifth lumbar nerve root

324
00:10:01,367 --> 00:10:03,569
innervates a muscle down here

325
00:10:03,569 --> 00:10:04,904
but also a muscle in your hip.

326
00:10:05,404 --> 00:10:06,339
And so you can kind of

327
00:10:06,339 --> 00:10:09,275
tease apart by innervating

328
00:10:09,408 --> 00:10:11,043
and examining all those

329
00:10:11,043 --> 00:10:12,411
muscles where the problem is.

330
00:10:13,112 --> 00:10:14,447
I see, so obviously on this

331
00:10:14,447 --> 00:10:16,449
podcast we're fairly interested

332
00:10:16,749 --> 00:10:19,352
in prosthetic devices of different kinds,

333
00:10:19,352 --> 00:10:19,585
measuring

334
00:10:19,585 --> 00:10:21,554
electrophysiology with new technologies.

335
00:10:22,188 --> 00:10:22,688
I guess from my

336
00:10:22,688 --> 00:10:25,091
perspective, I would think,

337
00:10:25,091 --> 00:10:25,591
well a lot of what

338
00:10:25,591 --> 00:10:27,660
you do is you're trying

339
00:10:27,660 --> 00:10:30,296
to understand diseases of the brain

340
00:10:30,896 --> 00:10:33,132
and then sometimes I guess of the brain

341
00:10:33,132 --> 00:10:33,799
is in the spinal cord

342
00:10:33,799 --> 00:10:34,734
but mostly of the brain

343
00:10:35,101 --> 00:10:36,869
and then using signals from the muscles

344
00:10:37,403 --> 00:10:38,904
to understand those diseases

345
00:10:39,171 --> 00:10:40,106
and then we have various

346
00:10:40,106 --> 00:10:41,107
interventions that we do.

347
00:10:41,507 --> 00:10:45,311
Whereas for you, the abnormalities may

348
00:10:45,311 --> 00:10:46,112
arise really anywhere

349
00:10:46,112 --> 00:10:47,647
from the brain down to the periphery.

350
00:10:48,547 --> 00:10:48,948
Is that right?

351
00:10:49,415 --> 00:10:50,249
Yeah, absolutely.

352
00:10:50,616 --> 00:10:52,885
So a lot of what EMG and

353
00:10:52,885 --> 00:10:54,053
nerve conduction studies

354
00:10:54,053 --> 00:10:54,987
are looking for are

355
00:10:54,987 --> 00:10:56,389
problems either at the anterior

356
00:10:56,389 --> 00:10:58,190
horn cell or the

357
00:10:58,190 --> 00:11:00,693
dorosaruganglion out into the periphery

358
00:11:01,027 --> 00:11:02,361
neuromuscular junction for

359
00:11:02,361 --> 00:11:04,430
diseases like myasthenia gravis

360
00:11:04,764 --> 00:11:06,666
or the muscle itself for muscular

361
00:11:06,666 --> 00:11:08,334
dystrophies and myopathies.

362
00:11:09,035 --> 00:11:10,269
And do you first see a time

363
00:11:10,269 --> 00:11:12,004
when we'll have technologies

364
00:11:12,405 --> 00:11:14,607
where we're using recordings

365
00:11:14,607 --> 00:11:15,675
that we make from the brain

366
00:11:15,675 --> 00:11:16,409
at the same time as

367
00:11:16,409 --> 00:11:17,276
we're making recordings

368
00:11:17,977 --> 00:11:19,145
from nerves and

369
00:11:19,145 --> 00:11:21,414
muscle and basically trying

370
00:11:21,547 --> 00:11:23,516
to assist normal

371
00:11:23,516 --> 00:11:25,418
biology in the disease state

372
00:11:25,418 --> 00:11:26,619
with prosthetic devices

373
00:11:26,619 --> 00:11:27,520
that are really distributed

374
00:11:28,087 --> 00:11:29,288
throughout the whole neural axis

375
00:11:29,288 --> 00:11:30,289
beginning up with the brain

376
00:11:30,790 --> 00:11:31,557
but actually ending at

377
00:11:31,557 --> 00:11:32,591
the end effector muscles?

378
00:11:32,591 --> 00:11:33,325
Is that the kind of

379
00:11:33,325 --> 00:11:33,926
thing that will happen

380
00:11:33,926 --> 00:11:35,795
or do you think you and

381
00:11:35,795 --> 00:11:36,729
I of course do some work

382
00:11:36,729 --> 00:11:37,463
with neural prosthetics

383
00:11:37,463 --> 00:11:38,364
together and I don't know

384
00:11:38,364 --> 00:11:39,498
that that's the best

385
00:11:39,498 --> 00:11:41,167
thing for today's conversation

386
00:11:41,400 --> 00:11:43,135
but in terms of neurotechnologies,

387
00:11:43,803 --> 00:11:45,638
is there a role for

388
00:11:45,638 --> 00:11:47,873
devices that are hybridized

389
00:11:47,973 --> 00:11:49,875
between the brain and the periphery?

390
00:11:50,543 --> 00:11:51,477
Absolutely, I mean I think

391
00:11:51,477 --> 00:11:52,878
it will ultimately depend

392
00:11:53,045 --> 00:11:56,015
on where the major part of

393
00:11:56,015 --> 00:11:57,183
degeneration is occurring.

394
00:11:57,883 --> 00:11:59,285
So if the nerves gone

395
00:11:59,285 --> 00:12:00,286
and the muscles gone,

396
00:12:00,653 --> 00:12:01,654
then you're gonna have to

397
00:12:01,654 --> 00:12:03,456
have some sort of prosthetic

398
00:12:03,589 --> 00:12:05,958
that's more of a

399
00:12:05,958 --> 00:12:08,561
cyborg or robotics control

400
00:12:09,428 --> 00:12:10,763
that may be being

401
00:12:10,763 --> 00:12:13,766
controlled central nervous system

402
00:12:13,933 --> 00:12:15,334
or at the spinal cord level.

403
00:12:15,768 --> 00:12:17,670
If there's issues where

404
00:12:17,670 --> 00:12:18,704
the nerves and muscles

405
00:12:18,704 --> 00:12:20,106
are still intact but

406
00:12:20,106 --> 00:12:21,474
the signals from the brain

407
00:12:21,474 --> 00:12:23,209
to the nerves and muscles aren't working,

408
00:12:23,209 --> 00:12:24,577
say with the spinal cord injury,

409
00:12:25,244 --> 00:12:27,580
potentially you could utilize the

410
00:12:27,580 --> 00:12:29,915
continued living muscle

411
00:12:29,915 --> 00:12:33,119
and nerve to be able to have an effector

412
00:12:33,119 --> 00:12:35,154
through a brain interface.

413
00:12:36,388 --> 00:12:36,889
Well Nathan, I was

414
00:12:36,889 --> 00:12:37,823
kind of interested to hear

415
00:12:37,957 --> 00:12:39,391
how things have changed since

416
00:12:39,391 --> 00:12:40,860
we were an EMG lab together.

417
00:12:41,193 --> 00:12:42,995
Really qualitatively I guess assessing

418
00:12:42,995 --> 00:12:44,663
sizes of these units

419
00:12:44,663 --> 00:12:45,664
and these patterns and

420
00:12:45,664 --> 00:12:47,500
how, whether it's algorithms

421
00:12:47,500 --> 00:12:48,734
or actually new technology

422
00:12:48,734 --> 00:12:50,436
has really changed the field

423
00:12:50,569 --> 00:12:52,004
of I guess EMG nerve conduction.

424
00:12:52,671 --> 00:12:55,241
Yeah, I mean as you may know,

425
00:12:55,441 --> 00:12:57,376
the actual physiology

426
00:12:57,376 --> 00:12:59,011
and basic technology

427
00:12:59,011 --> 00:13:01,046
really hasn't changed much since the 50s.

428
00:13:01,447 --> 00:13:02,014
It's just we have

429
00:13:02,014 --> 00:13:03,315
computers to drive it much

430
00:13:03,315 --> 00:13:04,116
more sophisticated

431
00:13:04,116 --> 00:13:06,085
fashion than we had previously.

432
00:13:06,619 --> 00:13:07,753
I do think that we're

433
00:13:07,753 --> 00:13:09,989
right now at kind of a critical

434
00:13:10,089 --> 00:13:11,357
juncture where

435
00:13:11,357 --> 00:13:13,425
algorithms and the computers

436
00:13:13,425 --> 00:13:14,426
are fast enough to

437
00:13:14,426 --> 00:13:15,694
actually run the algorithms

438
00:13:16,295 --> 00:13:17,963
on the data as it's coming through

439
00:13:18,297 --> 00:13:19,365
during a patient study

440
00:13:19,365 --> 00:13:20,766
to where we can actually

441
00:13:21,534 --> 00:13:22,868
be able to kind of

442
00:13:22,868 --> 00:13:24,737
utilize that technology.

443
00:13:25,371 --> 00:13:27,039
And so we've done a fair

444
00:13:27,039 --> 00:13:29,074
amount at Mayo Clinic with this.

445
00:13:29,508 --> 00:13:33,112
Some things are very nascent programs.

446
00:13:33,112 --> 00:13:33,979
We've taken all of

447
00:13:33,979 --> 00:13:35,147
the neurophysiology data

448
00:13:35,414 --> 00:13:36,315
and we've used

449
00:13:36,315 --> 00:13:37,750
machine learning to look at

450
00:13:38,083 --> 00:13:39,151
particular types of

451
00:13:39,151 --> 00:13:40,186
nerve conduction studies

452
00:13:40,419 --> 00:13:42,388
and looked at them in ways

453
00:13:42,388 --> 00:13:43,389
that we've never been able

454
00:13:43,389 --> 00:13:44,490
to look at them before.

455
00:13:44,990 --> 00:13:46,392
You know using wavelet

456
00:13:46,392 --> 00:13:47,493
and furrier transform

457
00:13:47,826 --> 00:13:50,796
and be able to pick out things

458
00:13:50,796 --> 00:13:52,331
that were never experienced before

459
00:13:52,464 --> 00:13:55,467
and relate that to specific diseases

460
00:13:55,467 --> 00:13:56,335
and to be able to

461
00:13:56,335 --> 00:13:57,770
differentiate different diseases

462
00:13:57,937 --> 00:13:58,537
from each other.

463
00:13:58,537 --> 00:14:00,172
We can differentiate ALS

464
00:14:00,172 --> 00:14:02,775
from inclusion body myositis

465
00:14:02,775 --> 00:14:04,210
which is a very similar disease.

466
00:14:04,944 --> 00:14:06,645
It's not built into the

467
00:14:06,645 --> 00:14:08,113
workflow of the patient care

468
00:14:08,113 --> 00:14:09,448
at this point but I

469
00:14:09,448 --> 00:14:10,449
think we're now in a position

470
00:14:10,649 --> 00:14:12,484
where we could potentially do that

471
00:14:12,484 --> 00:14:14,553
and we're working very hard to figure out

472
00:14:14,920 --> 00:14:16,088
how to get the data up,

473
00:14:16,088 --> 00:14:17,256
get it to the clinician

474
00:14:17,623 --> 00:14:19,592
to be able to use it in real time

475
00:14:20,326 --> 00:14:21,193
at the time that

476
00:14:21,193 --> 00:14:22,995
we're doing these studies.

477
00:14:23,629 --> 00:14:24,930
That's mostly been done on the nerve

478
00:14:24,930 --> 00:14:26,532
conduction study side

479
00:14:28,200 --> 00:14:29,935
which is a fairly easy

480
00:14:29,935 --> 00:14:31,370
time series to work with.

481
00:14:32,037 --> 00:14:33,339
Moving over to the needle EMG

482
00:14:33,405 --> 00:14:38,244
which is a free running noisy signal

483
00:14:38,711 --> 00:14:41,280
is more complicated but we've

484
00:14:41,280 --> 00:14:42,548
got some ideas there as well

485
00:14:42,548 --> 00:14:43,115
that we can

486
00:14:43,115 --> 00:14:45,251
incorporate into the practice.

487
00:14:46,051 --> 00:14:46,585
Yeah I mean I remember

488
00:14:46,585 --> 00:14:48,354
even something as simple

489
00:14:48,354 --> 00:14:50,656
as the duration of the motor unit

490
00:14:50,889 --> 00:14:51,390
and when I was doing

491
00:14:51,390 --> 00:14:52,491
it it was just by ear

492
00:14:52,491 --> 00:14:53,626
and then you could try

493
00:14:53,626 --> 00:14:54,526
to hold a unit long enough

494
00:14:54,526 --> 00:14:55,327
to kind of measure it.

495
00:14:55,694 --> 00:14:57,329
Are there even algorithms

496
00:14:57,329 --> 00:14:59,765
that can do that more easily?

497
00:15:00,432 --> 00:15:00,633
If--

498
00:15:00,866 --> 00:15:01,500
Yeah so--

499
00:15:01,800 --> 00:15:02,902
To take account where you're at

500
00:15:02,902 --> 00:15:04,403
and relative distance to the unit

501
00:15:04,403 --> 00:15:05,704
so that you can hold it a little easier.

502
00:15:06,438 --> 00:15:08,007
Yeah so there are

503
00:15:08,007 --> 00:15:10,576
programs within the EMG suite

504
00:15:10,876 --> 00:15:12,278
that are able to kind of

505
00:15:12,278 --> 00:15:14,046
determine whether a spike

506
00:15:14,046 --> 00:15:16,215
has a sufficient rise time

507
00:15:16,215 --> 00:15:17,449
to be able to be interpreted

508
00:15:17,816 --> 00:15:19,885
and then to be able to measure it

509
00:15:19,885 --> 00:15:21,153
actually at the time.

510
00:15:22,054 --> 00:15:22,821
Frankly we still use

511
00:15:22,821 --> 00:15:23,689
our ears for most of that.

512
00:15:23,689 --> 00:15:24,823
Yeah that was gonna be my next question

513
00:15:24,823 --> 00:15:25,824
is actually what's, I

514
00:15:25,824 --> 00:15:26,759
mean this is all exciting

515
00:15:26,759 --> 00:15:27,393
but actually what's

516
00:15:27,393 --> 00:15:28,227
happening in there right now

517
00:15:28,227 --> 00:15:31,130
and that's kind of the same in the DBSOR.

518
00:15:31,163 --> 00:15:33,599
We have a lot of tools

519
00:15:33,599 --> 00:15:35,100
that we're developing

520
00:15:35,100 --> 00:15:37,136
and I think will be sort of the future

521
00:15:37,870 --> 00:15:40,906
but still if all the screens were down

522
00:15:40,906 --> 00:15:42,041
we'd be pretty good.

523
00:15:42,541 --> 00:15:44,944
Yeah I think what I'm

524
00:15:44,944 --> 00:15:45,744
really excited about

525
00:15:45,744 --> 00:15:46,812
is to be able to pull

526
00:15:46,812 --> 00:15:49,014
information out of the data streams

527
00:15:49,014 --> 00:15:50,249
that we didn't know was there.

528
00:15:50,616 --> 00:15:51,984
And to be able to utilize that

529
00:15:52,318 --> 00:15:54,286
rather than kind of just making it easier

530
00:15:54,520 --> 00:15:57,556
for anyone off the street to do an EMG

531
00:15:57,623 --> 00:16:00,893
because that's not as important I think.

532
00:16:01,827 --> 00:16:04,530
And in your case can you tell us

533
00:16:04,530 --> 00:16:06,098
about your clinical practice?

534
00:16:06,298 --> 00:16:09,468
I mean our interactions are always,

535
00:16:10,436 --> 00:16:11,503
and in fact I guess most of our

536
00:16:11,503 --> 00:16:12,137
interactions with you

537
00:16:12,137 --> 00:16:13,605
are about your role as a leader.

538
00:16:14,506 --> 00:16:15,374
But what does your

539
00:16:15,374 --> 00:16:16,442
clinical practice look like

540
00:16:16,442 --> 00:16:17,376
in your role as a clinician?

541
00:16:18,110 --> 00:16:19,445
Yeah so my clinical

542
00:16:19,445 --> 00:16:20,713
practice really evolved.

543
00:16:21,046 --> 00:16:22,915
So when I started at Mayo

544
00:16:22,915 --> 00:16:24,717
as a resident and then fellow

545
00:16:24,717 --> 00:16:26,952
there was no field of ultra-immunology.

546
00:16:27,386 --> 00:16:28,887
So there was neuraminology

547
00:16:28,887 --> 00:16:30,689
and neuraminology was multiple cirrhosis.

548
00:16:31,857 --> 00:16:34,393
And a lot of people think when you say

549
00:16:34,426 --> 00:16:35,527
inflammatory brain disease

550
00:16:35,527 --> 00:16:36,662
they think multiple cirrhosis.

551
00:16:36,995 --> 00:16:37,730
Well you can imagine

552
00:16:37,730 --> 00:16:40,566
there's a whole world of diseases

553
00:16:40,799 --> 00:16:41,533
that affect both the

554
00:16:41,533 --> 00:16:43,402
central nervous system,

555
00:16:43,402 --> 00:16:44,269
the brain, the spinal cord

556
00:16:44,269 --> 00:16:45,604
but also the peripheral nervous system

557
00:16:46,672 --> 00:16:47,673
that are immune mediated

558
00:16:47,673 --> 00:16:49,708
that are not multiple cirrhosis.

559
00:16:50,609 --> 00:16:52,444
And so during my

560
00:16:52,444 --> 00:16:53,779
fellowship we kind of created

561
00:16:54,346 --> 00:16:56,415
a fellowship for what we

562
00:16:56,415 --> 00:16:57,850
consider a new field of disease

563
00:16:58,083 --> 00:16:59,218
where you actually have

564
00:16:59,218 --> 00:17:00,786
immune mediated attack

565
00:17:01,487 --> 00:17:03,989
of the nervous system but

566
00:17:03,989 --> 00:17:05,591
different to multiple cirrhosis

567
00:17:05,758 --> 00:17:06,992
where it's immune mediated

568
00:17:06,992 --> 00:17:08,894
but we don't know what the target is.

569
00:17:09,695 --> 00:17:11,430
This is a field where we

570
00:17:11,430 --> 00:17:13,198
study immune mediated diseases

571
00:17:13,432 --> 00:17:14,166
where we actually know

572
00:17:14,166 --> 00:17:15,801
what the neural target is.

573
00:17:16,035 --> 00:17:19,605
So for example in the field of NMO

574
00:17:19,605 --> 00:17:21,140
which is a really severe

575
00:17:21,140 --> 00:17:22,574
form of multiple cirrhosis,

576
00:17:22,674 --> 00:17:25,544
in that condition in 2004,

577
00:17:26,045 --> 00:17:27,212
Van der Lenden led the team

578
00:17:27,613 --> 00:17:28,947
that discovered the first

579
00:17:28,947 --> 00:17:31,150
ever biomarker of the disease

580
00:17:31,150 --> 00:17:32,584
where we actually showed

581
00:17:33,352 --> 00:17:34,086
that the disease was

582
00:17:34,086 --> 00:17:35,187
caused by an antibody

583
00:17:35,654 --> 00:17:36,588
that targets a water

584
00:17:36,588 --> 00:17:38,424
channel that sits on an astrocyte.

585
00:17:39,558 --> 00:17:42,161
And that was a seminal advance

586
00:17:42,327 --> 00:17:43,195
because that led to the

587
00:17:43,195 --> 00:17:44,730
first FDA approved drug

588
00:17:44,730 --> 00:17:45,831
for any inflammatory

589
00:17:45,831 --> 00:17:47,266
brain disease other than MS.

590
00:17:47,833 --> 00:17:49,101
And this was all done at Mayo Clinic.

591
00:17:49,101 --> 00:17:49,568
So it was really,

592
00:17:49,968 --> 00:17:51,270
this was a seismic jump.

593
00:17:51,303 --> 00:17:55,007
So that was happening in the lab

594
00:17:55,808 --> 00:17:58,177
and then the work trying

595
00:17:58,177 --> 00:17:59,711
to figure out the mechanisms

596
00:18:00,012 --> 00:18:02,448
by which that antibody causes the disease

597
00:18:02,748 --> 00:18:03,515
with the ultimate objective

598
00:18:03,515 --> 00:18:05,250
of finding a novel therapy and cure.

599
00:18:06,051 --> 00:18:06,885
That was all happening

600
00:18:06,885 --> 00:18:08,187
in the research realm

601
00:18:08,620 --> 00:18:09,388
whereas in the clinic

602
00:18:09,688 --> 00:18:11,223
we developed the first autoimmune

603
00:18:11,223 --> 00:18:12,991
neurology clinic in 2007.

604
00:18:13,692 --> 00:18:14,993
We developed the first autoimmune

605
00:18:14,993 --> 00:18:16,328
neurology fellowship

606
00:18:16,628 --> 00:18:20,365
in 2008 and actually we founded

607
00:18:21,333 --> 00:18:23,969
the first, the

608
00:18:23,969 --> 00:18:25,437
autoimmune neurology section

609
00:18:25,671 --> 00:18:26,038
at the American

610
00:18:26,038 --> 00:18:27,906
Academy of Neurology in 2017.

611
00:18:28,574 --> 00:18:30,042
So the clinic

612
00:18:30,042 --> 00:18:32,044
essentially attracted patients

613
00:18:32,044 --> 00:18:33,212
that came with

614
00:18:33,212 --> 00:18:34,446
inflammatory brain diseases

615
00:18:34,446 --> 00:18:35,848
that were not multiple cirrhosis.

616
00:18:36,849 --> 00:18:37,716
And though each

617
00:18:37,716 --> 00:18:39,251
individual disease was rare,

618
00:18:39,518 --> 00:18:40,619
when you put them all together,

619
00:18:41,019 --> 00:18:42,888
they're actually not so uncommon.

620
00:18:43,388 --> 00:18:44,756
And they're complex diseases

621
00:18:44,890 --> 00:18:45,924
because you can imagine

622
00:18:45,924 --> 00:18:48,026
that you've got a brain

623
00:18:48,260 --> 00:18:51,964
which has 200 billion neural cells,

624
00:18:52,297 --> 00:18:53,665
most of them are astrocytes.

625
00:18:54,066 --> 00:18:55,434
And then you have the immune system

626
00:18:56,001 --> 00:18:57,903
which has an incredible diversity

627
00:18:58,170 --> 00:18:59,104
of potential

628
00:18:59,104 --> 00:19:01,340
antigenic targets with B-cell,

629
00:19:02,074 --> 00:19:03,475
B-cells with antibodies that target

630
00:19:03,876 --> 00:19:05,077
millions of different epitopes,

631
00:19:05,310 --> 00:19:06,979
T-cells with T-cell

632
00:19:06,979 --> 00:19:07,846
receptors that target.

633
00:19:08,113 --> 00:19:09,815
And so you mix those together,

634
00:19:09,815 --> 00:19:11,850
you've got high complexity of disease.

635
00:19:12,851 --> 00:19:14,820
And so what we did was through the center

636
00:19:14,820 --> 00:19:16,421
for MS and autoimmune neurology

637
00:19:16,588 --> 00:19:19,458
and through really having, first of all,

638
00:19:19,491 --> 00:19:21,093
recruiting and training brilliant people

639
00:19:21,093 --> 00:19:22,528
and developing incredible teams,

640
00:19:23,128 --> 00:19:24,997
we began to see the patients

641
00:19:25,631 --> 00:19:27,165
but then enroll them in

642
00:19:27,165 --> 00:19:29,468
biobanks, biorepositories.

643
00:19:29,968 --> 00:19:31,570
And so unusual disease,

644
00:19:32,237 --> 00:19:33,272
we would then collect their

645
00:19:33,272 --> 00:19:34,406
blood, their spinal fluid.

646
00:19:35,007 --> 00:19:36,642
And then working in conjunction

647
00:19:36,642 --> 00:19:37,843
with the neuraminology department,

648
00:19:38,243 --> 00:19:41,713
we began to search for biomarkers

649
00:19:41,780 --> 00:19:44,850
like aquaporin-4 antibodies in NMO-SD.

650
00:19:45,684 --> 00:19:47,519
And how did we discover that antibody?

651
00:19:48,086 --> 00:19:50,189
Well, we took people's blood,

652
00:19:51,423 --> 00:19:52,224
we took their serum,

653
00:19:52,691 --> 00:19:53,825
we put it on mouse

654
00:19:53,825 --> 00:19:55,594
tissues, mouse brain tissues,

655
00:19:56,295 --> 00:19:59,665
and we looked for immunoglobulins, IgGs,

656
00:19:59,665 --> 00:20:01,600
that were binding to the neural targets

657
00:20:01,600 --> 00:20:02,534
on the mouse tissues.

658
00:20:03,268 --> 00:20:04,369
And when we looked for the

659
00:20:04,369 --> 00:20:05,370
water channel, for example,

660
00:20:05,370 --> 00:20:06,605
we saw a pattern of staining.

661
00:20:07,506 --> 00:20:09,007
And then that pattern of staining,

662
00:20:09,007 --> 00:20:10,342
we used a variety of different

663
00:20:10,342 --> 00:20:11,310
techniques in the laboratory.

664
00:20:12,277 --> 00:20:12,911
There was older

665
00:20:12,911 --> 00:20:15,047
techniques back in the 90s.

666
00:20:15,080 --> 00:20:17,115
Now we have much more technologically

667
00:20:17,115 --> 00:20:18,150
advanced techniques.

668
00:20:18,617 --> 00:20:19,785
And that allowed us to discover

669
00:20:19,785 --> 00:20:21,353
what the target of that antibody was.

670
00:20:22,154 --> 00:20:23,589
And at the current time,

671
00:20:23,589 --> 00:20:25,157
we're discovering about two to three

672
00:20:25,157 --> 00:20:26,892
novel antibody biomarkers

673
00:20:26,892 --> 00:20:28,126
of disease every year,

674
00:20:28,360 --> 00:20:29,928
based on those patterns of staining.

675
00:20:30,596 --> 00:20:31,797
And each of those antibodies

676
00:20:32,030 --> 00:20:33,465
has a very, very clear

677
00:20:33,465 --> 00:20:34,466
clinical significance.

678
00:20:34,733 --> 00:20:35,534
So these are antibodies,

679
00:20:35,968 --> 00:20:37,302
they're not just research

680
00:20:37,302 --> 00:20:39,104
hypothesis testing antibodies,

681
00:20:39,338 --> 00:20:39,972
these are real

682
00:20:39,972 --> 00:20:41,573
clinically relevant antibodies.

683
00:20:42,274 --> 00:20:44,977
And so the clinic essentially grew

684
00:20:45,477 --> 00:20:46,478
with this kind of back and

685
00:20:46,478 --> 00:20:48,146
forth from the clinic to the lab,

686
00:20:48,847 --> 00:20:51,149
discovering, identifying a target,

687
00:20:51,149 --> 00:20:52,718
once you've figured out the target,

688
00:20:52,718 --> 00:20:53,418
then you figure out

689
00:20:53,418 --> 00:20:54,920
the disease mechanisms,

690
00:20:54,920 --> 00:20:56,288
the immunopathogenic mechanisms.

691
00:20:56,855 --> 00:21:00,292
And that then leads to novel targets.

692
00:21:01,126 --> 00:21:04,129
And so then we moved into trials,

693
00:21:04,763 --> 00:21:05,864
and then have been

694
00:21:05,864 --> 00:21:07,132
leading many, many trials

695
00:21:07,199 --> 00:21:08,600
looking at novel drugs

696
00:21:08,600 --> 00:21:10,135
that target the mechanisms

697
00:21:10,369 --> 00:21:11,136
that are involved in those

698
00:21:11,136 --> 00:21:13,672
specific, very defined diseases.

699
00:21:14,473 --> 00:21:16,074
And ultimately leading to

700
00:21:16,074 --> 00:21:18,143
significantly improved outcomes

701
00:21:18,143 --> 00:21:19,911
for patients with very, very bizarre

702
00:21:20,345 --> 00:21:21,446
inflammatory brain diseases.

703
00:21:21,947 --> 00:21:24,416
So if you have some person come to you

704
00:21:24,416 --> 00:21:26,852
with an as yet undescribed,

705
00:21:26,852 --> 00:21:28,787
but clearly autoimmune fluctuates,

706
00:21:28,787 --> 00:21:29,488
there may be triggers

707
00:21:29,488 --> 00:21:30,555
that you can identify

708
00:21:31,256 --> 00:21:32,791
disease causing neurologic disorders.

709
00:21:33,225 --> 00:21:34,326
They come in, you may or

710
00:21:34,326 --> 00:21:35,827
may not find abnormalities

711
00:21:36,161 --> 00:21:37,763
in their MRI that point

712
00:21:37,763 --> 00:21:38,797
to there being a problem.

713
00:21:39,564 --> 00:21:41,733
Right now, for individual people,

714
00:21:41,733 --> 00:21:43,435
you're trying to discover new therapies?

715
00:21:44,169 --> 00:21:45,370
Yes. Or is it that you cluster people

716
00:21:45,370 --> 00:21:47,306
and then look for therapy within that?

717
00:21:47,372 --> 00:21:49,274
So you can cluster people in varied ways.

718
00:21:49,574 --> 00:21:51,276
So for example, one of the

719
00:21:51,276 --> 00:21:52,377
ways we cluster the people

720
00:21:52,377 --> 00:21:53,712
is based on the staining pattern.

721
00:21:54,546 --> 00:21:56,481
So patient comes in with a phenotype,

722
00:21:56,915 --> 00:21:58,050
you find a staining

723
00:21:58,050 --> 00:21:59,284
pattern of the immunoglobulin,

724
00:21:59,284 --> 00:22:00,252
that mouse tissue.

725
00:22:01,086 --> 00:22:02,254
And then a year later,

726
00:22:02,254 --> 00:22:03,021
you see another patient

727
00:22:03,021 --> 00:22:03,989
with a similar phenotype,

728
00:22:04,256 --> 00:22:05,057
and lo and behold, they

729
00:22:05,057 --> 00:22:06,825
have the exact same IgG

730
00:22:06,825 --> 00:22:07,993
that's binding to the mouse

731
00:22:07,993 --> 00:22:09,227
tissue in the same pattern.

732
00:22:09,528 --> 00:22:10,696
So you cluster them there.

733
00:22:11,396 --> 00:22:14,466
Once you identify more than five patients

734
00:22:14,866 --> 00:22:16,001
with a similar phenotype,

735
00:22:16,835 --> 00:22:19,204
and they all have the same IgG biomarker,

736
00:22:19,604 --> 00:22:20,872
the next step then is to figure out

737
00:22:20,872 --> 00:22:22,841
well, what does that IgG bind to?

738
00:22:23,275 --> 00:22:23,875
What's its target?

739
00:22:24,443 --> 00:22:25,744
Once you found out the target,

740
00:22:26,111 --> 00:22:26,945
then you have a novel

741
00:22:26,945 --> 00:22:28,980
biomarker of that specific disease.

742
00:22:29,715 --> 00:22:32,284
Then you take that IgG into the lab

743
00:22:32,284 --> 00:22:33,185
and you try to figure out

744
00:22:33,185 --> 00:22:35,187
how does it cause pathogenesis?

745
00:22:35,454 --> 00:22:36,555
How does it injure the cell?

746
00:22:37,389 --> 00:22:38,657
Once you figure out the pathways

747
00:22:38,890 --> 00:22:40,092
by which it injures the cell,

748
00:22:40,425 --> 00:22:41,393
then you've identified

749
00:22:41,393 --> 00:22:42,594
potential novel targets.

750
00:22:42,994 --> 00:22:44,730
Sure, and you guys have done this?

751
00:22:44,830 --> 00:22:45,664
Many times, yeah.

752
00:22:45,797 --> 00:22:47,833
So for example, in the water channel,

753
00:22:47,833 --> 00:22:49,234
what happened was we realized,

754
00:22:50,235 --> 00:22:51,670
and this was work even before the

755
00:22:51,670 --> 00:22:52,738
discovery of the target,

756
00:22:53,705 --> 00:22:55,407
Claudia Lucanetti had shown that

757
00:22:55,674 --> 00:22:56,341
in the

758
00:22:56,341 --> 00:22:58,410
immunopathological studies of people

759
00:22:58,410 --> 00:22:59,244
that had died of this

760
00:22:59,244 --> 00:23:00,712
very rare form of MS,

761
00:23:01,046 --> 00:23:02,114
in the lesions, there

762
00:23:02,114 --> 00:23:03,215
was complement deposition.

763
00:23:03,882 --> 00:23:05,851
So indicating that this was probably

764
00:23:06,151 --> 00:23:07,853
an antibody mediated disease and

765
00:23:07,853 --> 00:23:08,620
complement activating.

766
00:23:09,287 --> 00:23:10,255
But once we figured out

767
00:23:10,255 --> 00:23:11,490
the antibody that targets

768
00:23:11,790 --> 00:23:14,326
the water channel on the astrocyte,

769
00:23:15,060 --> 00:23:16,828
we did a variety of different studies

770
00:23:17,162 --> 00:23:19,531
led by Shannon Hinson and Van der Lenen

771
00:23:19,831 --> 00:23:20,699
that demonstrated that

772
00:23:20,699 --> 00:23:21,767
when the antibody binds

773
00:23:21,767 --> 00:23:22,634
to the water channel,

774
00:23:22,634 --> 00:23:23,602
it activates complement

775
00:23:23,935 --> 00:23:24,803
and it kills the cell.

776
00:23:25,771 --> 00:23:29,141
So then in 2012, we did a phase two trial

777
00:23:29,608 --> 00:23:30,175
of a complement

778
00:23:30,175 --> 00:23:32,210
inhibitor and it was dramatic.

779
00:23:32,811 --> 00:23:34,413
And then we did a phase three trial

780
00:23:35,013 --> 00:23:35,914
and showed that we

781
00:23:35,914 --> 00:23:37,149
could reduce the likelihood

782
00:23:37,816 --> 00:23:39,818
by blocking complement, we

783
00:23:39,818 --> 00:23:40,919
could reduce the likelihood

784
00:23:40,919 --> 00:23:41,820
of a clinical relapse

785
00:23:41,820 --> 00:23:43,088
of that disease by 96%.

786
00:23:44,656 --> 00:23:46,391
So that's an

787
00:23:46,391 --> 00:23:48,794
incredible impact for a disease

788
00:23:48,994 --> 00:23:51,229
where these patients become blind

789
00:23:51,630 --> 00:23:52,330
or they develop

790
00:23:52,330 --> 00:23:55,133
paraplegia because they get attacks

791
00:23:55,133 --> 00:23:56,468
of optic neuritis or

792
00:23:56,468 --> 00:23:57,602
attacks of inflammation

793
00:23:57,602 --> 00:23:59,404
of the spinal cord to

794
00:23:59,404 --> 00:24:01,406
come in and develop a drug

795
00:24:01,406 --> 00:24:03,108
based on the immunopathogenic mechanism

796
00:24:03,508 --> 00:24:05,277
that came from those discoveries

797
00:24:06,077 --> 00:24:06,978
and end up with a drug

798
00:24:06,978 --> 00:24:08,313
that reduces the chances

799
00:24:08,313 --> 00:24:10,415
of an attack by 96%,

800
00:24:10,849 --> 00:24:12,250
essentially nearly moves

801
00:24:12,250 --> 00:24:13,285
the patient into near cure.

802
00:24:14,386 --> 00:24:17,556
And so then another disease, MoGAD,

803
00:24:17,789 --> 00:24:20,459
we've just demonstrated the early results

804
00:24:20,459 --> 00:24:22,794
look very positive for an alternative

805
00:24:22,794 --> 00:24:24,229
target approach there.

806
00:24:24,329 --> 00:24:24,896
What's MoGAD?

807
00:24:25,764 --> 00:24:27,966
So MoGAD is, so if you

808
00:24:27,966 --> 00:24:29,868
can imagine that an NMO,

809
00:24:29,868 --> 00:24:30,535
this disease with

810
00:24:30,535 --> 00:24:32,537
relapsing attacks of optic nerve,

811
00:24:32,604 --> 00:24:34,206
inflammation and spinal cord inflammation

812
00:24:34,206 --> 00:24:35,106
that causes people to

813
00:24:35,106 --> 00:24:37,409
go blind and paraplegic,

814
00:24:37,709 --> 00:24:38,810
so that's caused by an

815
00:24:38,810 --> 00:24:39,611
antibody that targets

816
00:24:39,611 --> 00:24:41,346
a water channel on an astrocyte.

817
00:24:41,980 --> 00:24:43,515
Well, you can just imagine,

818
00:24:44,516 --> 00:24:46,785
well, you've got billions of astrocytes

819
00:24:46,785 --> 00:24:47,452
with billions of

820
00:24:47,452 --> 00:24:48,587
targets and you've got lots

821
00:24:48,587 --> 00:24:49,754
and lots of B cells, so

822
00:24:49,754 --> 00:24:51,623
it's not rocket science

823
00:24:51,623 --> 00:24:52,490
to imagine that there's

824
00:24:52,490 --> 00:24:53,825
another disease out there.

825
00:24:54,459 --> 00:24:56,695
And the next disease then in the field

826
00:24:56,795 --> 00:24:57,996
of inflammatory central

827
00:24:57,996 --> 00:24:59,030
nervous system demodination

828
00:24:59,364 --> 00:25:00,765
other than MS was MoGAD,

829
00:25:01,266 --> 00:25:02,367
where the antibody is

830
00:25:02,367 --> 00:25:04,469
targeting myelin oligodendrocyte

831
00:25:04,469 --> 00:25:06,705
glycoprotein on the oligodendrocyte.

832
00:25:07,606 --> 00:25:08,874
And similar disease,

833
00:25:09,508 --> 00:25:10,742
patients get optic nerve disease,

834
00:25:11,076 --> 00:25:11,810
they get spinal cord

835
00:25:11,810 --> 00:25:14,346
disease, they look like MS,

836
00:25:14,913 --> 00:25:15,313
but they have

837
00:25:15,313 --> 00:25:16,948
antibodies that are targeting

838
00:25:17,215 --> 00:25:19,784
the MoG protein on the oligodendrocyte.

839
00:25:20,285 --> 00:25:21,786
And in fact, they activate complement.

840
00:25:22,721 --> 00:25:25,123
And their mechanism of injury to the cell

841
00:25:25,123 --> 00:25:26,291
is very, very similar

842
00:25:26,291 --> 00:25:28,159
to water channel antibody

843
00:25:28,426 --> 00:25:29,127
positive disease.

844
00:25:29,861 --> 00:25:31,730
And so similar drugs are now being tried

845
00:25:31,963 --> 00:25:35,600
in that disease as were tried in NMOSD.

846
00:25:36,134 --> 00:25:38,370
Okay, that's kind of interesting.

847
00:25:38,370 --> 00:25:39,571
Have you ever, have you

848
00:25:39,571 --> 00:25:41,273
guys ever tried to take

849
00:25:41,706 --> 00:25:44,342
take these diseases and refashion them

850
00:25:44,576 --> 00:25:45,544
for immunotherapies for

851
00:25:45,544 --> 00:25:46,811
things like brain tumors,

852
00:25:47,546 --> 00:25:50,715
or I hear oligo and I'm a simple man.

853
00:25:51,049 --> 00:25:51,249
I think

854
00:25:51,249 --> 00:25:53,752
oligodendrocyte, take it out, right?

855
00:25:53,785 --> 00:25:54,486
I love the idea.

856
00:25:54,920 --> 00:25:56,087
So we have thought about that.

857
00:25:56,354 --> 00:25:57,756
So essentially there's a couple of things

858
00:25:57,889 --> 00:25:58,390
to think about.

859
00:25:59,157 --> 00:26:01,626
So the first thing is,

860
00:26:03,929 --> 00:26:06,264
we suspect that people that have tumors

861
00:26:06,932 --> 00:26:08,867
that express neural targets

862
00:26:10,168 --> 00:26:12,904
that then develop neurological disease

863
00:26:13,104 --> 00:26:14,272
because they develop an

864
00:26:14,272 --> 00:26:15,607
immune response to the tumor,

865
00:26:15,607 --> 00:26:17,075
but the target antigen in

866
00:26:17,075 --> 00:26:18,510
the tumor is a neural protein.

867
00:26:19,110 --> 00:26:20,845
And now there's a T cell

868
00:26:20,845 --> 00:26:22,147
response against the tumor,

869
00:26:22,347 --> 00:26:23,949
say in the lung, but

870
00:26:23,949 --> 00:26:25,216
now the immune system

871
00:26:25,417 --> 00:26:26,284
is now also being

872
00:26:26,284 --> 00:26:28,486
directed up to the brain tissue

873
00:26:28,486 --> 00:26:30,055
where that neural

874
00:26:30,055 --> 00:26:31,489
antigen is also expressed

875
00:26:31,923 --> 00:26:33,625
as a perinoplastic neurological disease.

876
00:26:34,225 --> 00:26:35,927
And what we noted was that

877
00:26:35,927 --> 00:26:37,395
patients with those diseases,

878
00:26:37,696 --> 00:26:38,029
they actually

879
00:26:38,029 --> 00:26:39,731
generally we think do better

880
00:26:40,065 --> 00:26:41,866
from their lung cancer perspective

881
00:26:42,133 --> 00:26:42,701
because they have a

882
00:26:42,701 --> 00:26:44,102
very robust T cell response

883
00:26:44,569 --> 00:26:45,537
to the lung cancer.

884
00:26:45,537 --> 00:26:46,371
And we also know that

885
00:26:46,371 --> 00:26:47,806
in the concept of cancer,

886
00:26:48,173 --> 00:26:49,674
if you use a checkpoint inhibitor

887
00:26:50,575 --> 00:26:51,543
for the treatment of cancer,

888
00:26:51,743 --> 00:26:52,744
you can actually make the

889
00:26:52,744 --> 00:26:53,812
brain disease a lot worse.

890
00:26:54,746 --> 00:26:58,616
So the idea that you could actually use

891
00:26:59,951 --> 00:27:02,487
the response to the

892
00:27:02,487 --> 00:27:04,589
neural proteins in a tumor

893
00:27:05,090 --> 00:27:08,293
and actually develop potential CARs,

894
00:27:09,294 --> 00:27:10,095
then you could

895
00:27:10,095 --> 00:27:11,730
actually treat tumors better.

896
00:27:12,163 --> 00:27:13,331
So in other words, you're really

897
00:27:13,331 --> 00:27:15,233
essentially creating

898
00:27:15,834 --> 00:27:17,736
an autoimmune neurological disorder

899
00:27:18,870 --> 00:27:20,038
to kind of kill the cancer.

900
00:27:20,305 --> 00:27:23,274
And I think that's a very reasonable

901
00:27:23,274 --> 00:27:24,109
thing to think about.

902
00:27:25,076 --> 00:27:26,044
And the other thing is

903
00:27:26,044 --> 00:27:27,212
on the other side of that

904
00:27:27,779 --> 00:27:29,648
is at the moment we're

905
00:27:29,648 --> 00:27:33,551
using CAR T therapies, okay,

906
00:27:35,086 --> 00:27:37,689
to take out, could you for our audience

907
00:27:37,689 --> 00:27:39,824
just explain what a CAR T therapy is?

908
00:27:40,225 --> 00:27:41,760
Yeah, so CAR is a

909
00:27:41,760 --> 00:27:43,428
chimeric antigen receptor.

910
00:27:43,428 --> 00:27:45,363
So essentially it's like

911
00:27:45,363 --> 00:27:47,832
having a GPS system in your car.

912
00:27:48,733 --> 00:27:49,334
So you're driving

913
00:27:49,334 --> 00:27:50,769
along in your car, okay,

914
00:27:50,969 --> 00:27:52,137
and you don't know where you're going.

915
00:27:52,504 --> 00:27:54,072
So you put in your GPS system,

916
00:27:54,372 --> 00:27:55,206
you put in the address

917
00:27:55,206 --> 00:27:56,107
and it takes you right

918
00:27:56,107 --> 00:27:56,908
to where you need to go.

919
00:27:57,609 --> 00:28:01,112
So this is basically taking a T cell,

920
00:28:01,680 --> 00:28:03,448
so from the individual themselves,

921
00:28:03,948 --> 00:28:05,050
and putting in that GPS

922
00:28:05,050 --> 00:28:07,952
system, the CAR into their cell,

923
00:28:08,753 --> 00:28:11,189
that T cell will then go to

924
00:28:11,189 --> 00:28:13,324
wherever that CAR tells it to go.

925
00:28:14,359 --> 00:28:15,727
So for an example,

926
00:28:16,161 --> 00:28:17,395
hematologic malignancies

927
00:28:17,629 --> 00:28:18,963
where you have abnormal

928
00:28:18,963 --> 00:28:21,032
growth of B cells, so lymphoma,

929
00:28:21,800 --> 00:28:22,934
you can now take a T

930
00:28:22,934 --> 00:28:23,835
cell from that person,

931
00:28:24,335 --> 00:28:26,271
put in a CAR that will target

932
00:28:26,271 --> 00:28:27,872
a protein that's on B cells.

933
00:28:29,240 --> 00:28:31,543
And then so you take the T

934
00:28:31,543 --> 00:28:32,811
cells out of the patient,

935
00:28:33,411 --> 00:28:34,612
you transduce them,

936
00:28:35,346 --> 00:28:36,347
viral vectors or whatever,

937
00:28:36,347 --> 00:28:38,149
you put the CAR in, grow them,

938
00:28:38,450 --> 00:28:39,551
pop them back in the patient,

939
00:28:40,185 --> 00:28:41,953
those CAR T cells now will go

940
00:28:41,953 --> 00:28:44,189
and kill every single B cell

941
00:28:44,189 --> 00:28:46,357
that expresses the protein that's

942
00:28:46,357 --> 00:28:47,559
targeted by that CAR.

943
00:28:48,493 --> 00:28:49,194
And that has been

944
00:28:49,194 --> 00:28:50,495
revolutionary for people

945
00:28:50,662 --> 00:28:51,930
that essentially have

946
00:28:51,930 --> 00:28:53,698
failed all therapies

947
00:28:53,898 --> 00:28:55,166
for hematologic malignancy,

948
00:28:55,500 --> 00:28:57,602
suddenly now people are being cured.

949
00:28:58,470 --> 00:28:59,604
Well, you can imagine

950
00:28:59,604 --> 00:29:00,472
that you could use that

951
00:29:00,472 --> 00:29:02,774
in an immune mediated disease, okay?

952
00:29:02,774 --> 00:29:03,708
So there's been work done

953
00:29:03,708 --> 00:29:05,577
in people that are dying

954
00:29:05,744 --> 00:29:07,445
from lupus without ad lupus.

955
00:29:07,946 --> 00:29:08,913
You go in and take out

956
00:29:08,913 --> 00:29:11,549
their CD19 positive B cells,

957
00:29:12,117 --> 00:29:12,917
these patients are

958
00:29:12,917 --> 00:29:14,953
going from being nearly

959
00:29:15,420 --> 00:29:17,722
at the point of death to making

960
00:29:17,722 --> 00:29:18,857
significant recovery.

961
00:29:20,225 --> 00:29:21,292
The same in the field

962
00:29:21,292 --> 00:29:22,494
where the immune system

963
00:29:22,494 --> 00:29:23,628
is targeting the brain.

964
00:29:24,729 --> 00:29:26,865
In our field, we know what the target is.

965
00:29:27,365 --> 00:29:29,968
So we have just, anastasia cetera,

966
00:29:29,968 --> 00:29:32,904
it was just helped in

967
00:29:32,904 --> 00:29:34,873
a trial of CD19 CAR T

968
00:29:34,873 --> 00:29:36,141
for Stiff Person Syndrome,

969
00:29:36,508 --> 00:29:39,077
which is a disorder where you have an

970
00:29:39,077 --> 00:29:40,345
immune mediated target

971
00:29:40,478 --> 00:29:42,046
of your inhibitory nervous system

972
00:29:42,046 --> 00:29:44,048
and you get very hyper excitable patients

973
00:29:44,249 --> 00:29:45,950
that are in severe spasms

974
00:29:45,950 --> 00:29:47,752
and pain, very, very disabled.

975
00:29:48,253 --> 00:29:49,187
And it seems to work.

976
00:29:49,988 --> 00:29:51,256
But the concept of

977
00:29:51,256 --> 00:29:52,490
when you know the target

978
00:29:52,490 --> 00:29:53,491
of the immune cell,

979
00:29:54,225 --> 00:29:56,227
then you could actually develop a CAR

980
00:29:56,694 --> 00:29:59,264
that would just take out the B cell

981
00:29:59,597 --> 00:30:00,965
that's expressing the antibody

982
00:30:01,166 --> 00:30:02,934
that's targeting that specific target.

983
00:30:04,002 --> 00:30:06,171
Or you could potentially develop a CAR

984
00:30:06,638 --> 00:30:07,305
that would just take

985
00:30:07,305 --> 00:30:08,873
out the cytotoxic T cell

986
00:30:09,941 --> 00:30:11,910
based on that T cell receptor phenotype.

987
00:30:12,810 --> 00:30:13,812
So now I'm talking

988
00:30:13,812 --> 00:30:14,813
about what could happen

989
00:30:14,813 --> 00:30:15,914
in five to 10 years.

990
00:30:16,815 --> 00:30:18,917
So at the moment we have crude CARs

991
00:30:19,150 --> 00:30:21,586
that'll just take out a lot

992
00:30:21,586 --> 00:30:23,087
of B cells or a lot of T cells.

993
00:30:23,488 --> 00:30:24,656
But the future for the

994
00:30:24,656 --> 00:30:27,258
field of immunology in CAR T

995
00:30:27,258 --> 00:30:29,127
I think will allow us to

996
00:30:29,127 --> 00:30:30,728
develop much more specific

997
00:30:32,397 --> 00:30:33,698
opportunities to just

998
00:30:33,698 --> 00:30:34,766
take out the bad ones,

999
00:30:35,066 --> 00:30:36,568
the bad immune cells.

1000
00:30:37,168 --> 00:30:38,169
And that could have

1001
00:30:38,169 --> 00:30:39,404
significant impact to the field.

1002
00:30:40,939 --> 00:30:41,139
Thanks.

1003
00:30:42,240 --> 00:30:44,876
Something I think that's interesting

1004
00:30:44,876 --> 00:30:46,144
is when people talk about,

1005
00:30:46,644 --> 00:30:47,145
I mean you're one of

1006
00:30:47,145 --> 00:30:47,946
these rare individuals

1007
00:30:47,946 --> 00:30:49,714
that have had some

1008
00:30:49,714 --> 00:30:51,349
scientific finding in the lab

1009
00:30:52,083 --> 00:30:53,918
and identified patients

1010
00:30:53,918 --> 00:30:55,286
whom that was relevant for

1011
00:30:55,653 --> 00:30:56,754
and then a therapy that

1012
00:30:56,754 --> 00:30:57,789
saved the same patients

1013
00:30:57,789 --> 00:30:58,957
that you ultimately

1014
00:30:58,957 --> 00:31:00,558
came to treat clinically.

1015
00:31:01,426 --> 00:31:03,228
You know there's a vision of

1016
00:31:04,696 --> 00:31:06,397
somebody who happens to notice something

1017
00:31:06,397 --> 00:31:07,198
and they're basically

1018
00:31:07,198 --> 00:31:08,366
geeks for the subject.

1019
00:31:08,366 --> 00:31:09,734
And that's great, right?

1020
00:31:10,435 --> 00:31:11,269
And then they kind of

1021
00:31:11,269 --> 00:31:12,036
just follow something

1022
00:31:12,070 --> 00:31:14,172
doggedly over years and are able to

1023
00:31:15,573 --> 00:31:16,574
make that whole journey.

1024
00:31:16,574 --> 00:31:17,141
Although I think in

1025
00:31:17,141 --> 00:31:18,309
practice most people don't have

1026
00:31:18,309 --> 00:31:19,744
the wide skill set that's needed.

1027
00:31:20,545 --> 00:31:21,913
Separately there are also these large

1028
00:31:21,913 --> 00:31:22,914
teams of individuals

1029
00:31:23,514 --> 00:31:24,616
where it's kind of

1030
00:31:24,616 --> 00:31:26,251
like a Manhattan Project

1031
00:31:26,384 --> 00:31:30,321
for a particular disease model

1032
00:31:30,321 --> 00:31:31,990
or a particular type of pathology

1033
00:31:31,990 --> 00:31:33,291
that then results in a therapy.

1034
00:31:33,625 --> 00:31:34,926
And it seems like you're describing,

1035
00:31:35,293 --> 00:31:35,827
you've talked about

1036
00:31:35,827 --> 00:31:36,728
these different individuals

1037
00:31:36,728 --> 00:31:37,295
that you've worked

1038
00:31:37,295 --> 00:31:38,396
with like Dr. Lucianetti,

1039
00:31:38,963 --> 00:31:40,064
as if they are all

1040
00:31:40,064 --> 00:31:41,866
sort of different groups

1041
00:31:41,866 --> 00:31:42,967
that are working together.

1042
00:31:43,635 --> 00:31:44,836
So it sounds like the way

1043
00:31:44,836 --> 00:31:45,970
that you guys have done this

1044
00:31:45,970 --> 00:31:47,538
is that you have maybe,

1045
00:31:48,106 --> 00:31:48,940
and correct me if I'm wrong,

1046
00:31:48,940 --> 00:31:50,375
but some kind of Balkanized system

1047
00:31:50,375 --> 00:31:51,309
where people all

1048
00:31:51,309 --> 00:31:52,343
interact with one another

1049
00:31:52,744 --> 00:31:54,012
but have their own specializations

1050
00:31:54,012 --> 00:31:55,747
and then you're able to kind of

1051
00:31:56,414 --> 00:31:58,082
pass tokens back and forth of knowledge

1052
00:31:58,082 --> 00:31:59,951
that ultimately have led to treating

1053
00:31:59,951 --> 00:32:01,286
these different types of diseases.

1054
00:32:01,552 --> 00:32:02,153
Is that right?

1055
00:32:02,153 --> 00:32:03,488
Yeah, no, I mean I just love the way

1056
00:32:03,488 --> 00:32:05,256
you just phrase that question.

1057
00:32:05,690 --> 00:32:06,891
Because at the end of the day,

1058
00:32:07,558 --> 00:32:08,559
the first thing that happened

1059
00:32:08,559 --> 00:32:10,728
was back at the early discovery

1060
00:32:10,728 --> 00:32:12,764
was what we did at Mayo was we created

1061
00:32:13,364 --> 00:32:16,067
a Mayo Clinic, NMO enterprise,

1062
00:32:16,367 --> 00:32:17,602
or a group of

1063
00:32:17,602 --> 00:32:19,871
individuals that all had interests

1064
00:32:19,871 --> 00:32:22,040
but all came to the disease from a

1065
00:32:22,040 --> 00:32:22,774
different perspective.

1066
00:32:23,508 --> 00:32:26,377
So for example, you had Brian Weinshanker

1067
00:32:26,544 --> 00:32:28,046
and Dean Wingerchuk who were

1068
00:32:28,346 --> 00:32:30,181
the diagnostic criteria people.

1069
00:32:30,181 --> 00:32:31,950
They were the epidemiological people.

1070
00:32:32,350 --> 00:32:33,051
They studied the

1071
00:32:33,051 --> 00:32:34,352
epidemiology of the disease.

1072
00:32:34,552 --> 00:32:35,486
You had Claudia Lucianetti

1073
00:32:35,953 --> 00:32:36,554
who studied the

1074
00:32:36,554 --> 00:32:37,989
immunopathology of the disease.

1075
00:32:38,623 --> 00:32:39,791
You had Van der Lennen

1076
00:32:39,791 --> 00:32:40,892
who was an immunologist

1077
00:32:41,125 --> 00:32:42,226
and a basic science immunologist

1078
00:32:42,226 --> 00:32:43,428
who discovered the pattern

1079
00:32:43,428 --> 00:32:45,196
and ultimately the antibody.

1080
00:32:45,797 --> 00:32:46,664
You had me who was

1081
00:32:46,664 --> 00:32:48,232
kind of bringing the lab

1082
00:32:48,232 --> 00:32:49,400
and the clinic together

1083
00:32:50,335 --> 00:32:50,969
and then potentially

1084
00:32:50,969 --> 00:32:52,403
driving forward with trials.

1085
00:32:53,237 --> 00:32:54,906
You had PhD

1086
00:32:54,906 --> 00:32:57,875
scientists trying to understand

1087
00:32:57,875 --> 00:33:00,878
the mechanisms by which the disease

1088
00:33:01,079 --> 00:33:02,447
ultimately causes injury.

1089
00:33:03,147 --> 00:33:04,549
And regardless of the fact

1090
00:33:04,549 --> 00:33:05,883
that all of those individuals

1091
00:33:06,184 --> 00:33:07,585
were all coming together as a team,

1092
00:33:08,987 --> 00:33:12,123
it still took 25 years to go

1093
00:33:12,123 --> 00:33:13,658
from the biomarker discovery

1094
00:33:13,991 --> 00:33:16,094
to an FDA approved near cure.

1095
00:33:16,728 --> 00:33:17,829
Getting at your question,

1096
00:33:18,096 --> 00:33:20,031
what I really like doing as a chair

1097
00:33:20,932 --> 00:33:22,734
is the opportunity to say,

1098
00:33:23,534 --> 00:33:24,969
we have the brains at Mayo

1099
00:33:26,037 --> 00:33:28,906
but the question is how do we create

1100
00:33:28,906 --> 00:33:30,975
teams around problems

1101
00:33:31,642 --> 00:33:33,478
and do it in less than 25 years?

1102
00:33:33,845 --> 00:33:34,278
Yeah. Okay?

1103
00:33:35,480 --> 00:33:37,115
So for example, with

1104
00:33:37,115 --> 00:33:40,385
respect to the work that you do

1105
00:33:40,651 --> 00:33:43,588
and Brian and your teams do,

1106
00:33:44,088 --> 00:33:45,089
it became very evident

1107
00:33:45,089 --> 00:33:46,758
to me very, very early on

1108
00:33:47,325 --> 00:33:48,526
that this was a scenario

1109
00:33:48,526 --> 00:33:50,895
where we have at Mayo Clinic

1110
00:33:50,895 --> 00:33:52,897
an incredible group of individuals

1111
00:33:54,165 --> 00:33:55,266
with the potential to

1112
00:33:55,266 --> 00:33:57,135
make seismic advances

1113
00:33:58,002 --> 00:34:00,104
in the field of neuromodulation.

1114
00:34:00,638 --> 00:34:03,107
But the way that I

1115
00:34:03,107 --> 00:34:04,308
would see of doing that

1116
00:34:04,475 --> 00:34:06,511
and accelerating that is

1117
00:34:06,511 --> 00:34:09,047
really to create an infrastructure

1118
00:34:09,747 --> 00:34:11,983
within which that can really happen.

1119
00:34:12,383 --> 00:34:13,351
And I think that that's

1120
00:34:13,351 --> 00:34:15,853
what we really need to do.

1121
00:34:16,387 --> 00:34:18,689
What happened in neuromodology at Mayo

1122
00:34:18,689 --> 00:34:20,124
was we had a lot of

1123
00:34:20,124 --> 00:34:21,559
people working in their labs

1124
00:34:22,226 --> 00:34:22,894
with their own

1125
00:34:22,894 --> 00:34:24,829
technicians, with their own fellows,

1126
00:34:24,829 --> 00:34:25,396
with their own,

1127
00:34:25,863 --> 00:34:27,331
everyone was doing great work.

1128
00:34:28,166 --> 00:34:29,700
But then what happened was

1129
00:34:30,034 --> 00:34:30,968
through the Center for

1130
00:34:30,968 --> 00:34:31,936
MS and Automuneralogy,

1131
00:34:32,036 --> 00:34:33,204
we tried to bring everybody

1132
00:34:33,204 --> 00:34:34,605
into kind of the same fold.

1133
00:34:35,072 --> 00:34:36,441
So for example, on a

1134
00:34:36,441 --> 00:34:37,708
Wednesday, every Wednesday,

1135
00:34:37,975 --> 00:34:39,310
I meet with every

1136
00:34:39,310 --> 00:34:41,746
research fellow in neuromodology,

1137
00:34:42,447 --> 00:34:43,915
even if they're not my research fellow.

1138
00:34:43,915 --> 00:34:45,183
Still do. Yeah, still do.

1139
00:34:45,750 --> 00:34:46,751
Just to know what they're doing.

1140
00:34:47,952 --> 00:34:49,854
And really to try to

1141
00:34:49,854 --> 00:34:51,589
break down the walls of labs

1142
00:34:52,223 --> 00:34:53,724
so that actually people

1143
00:34:53,724 --> 00:34:55,293
are now sharing lab space.

1144
00:34:55,593 --> 00:34:58,362
There's a free flow of fellows,

1145
00:34:59,030 --> 00:35:00,531
residents, PhD students,

1146
00:35:01,566 --> 00:35:02,600
kind of moving

1147
00:35:02,600 --> 00:35:04,502
throughout the whole program,

1148
00:35:05,036 --> 00:35:06,537
as well as data

1149
00:35:06,537 --> 00:35:08,606
scientists who are coming in

1150
00:35:09,106 --> 00:35:10,274
and rather than a data

1151
00:35:10,274 --> 00:35:12,443
scientist working in one person's lab

1152
00:35:13,110 --> 00:35:14,612
and then another data scientist working

1153
00:35:14,612 --> 00:35:15,947
in another person's lab,

1154
00:35:16,714 --> 00:35:17,682
to try and create a

1155
00:35:17,682 --> 00:35:18,816
core of data scientists

1156
00:35:18,816 --> 00:35:20,084
that are all working together

1157
00:35:20,718 --> 00:35:22,086
and that can kind of

1158
00:35:22,086 --> 00:35:24,589
move fluidly throughout.

1159
00:35:24,589 --> 00:35:26,757
I think that allows, that will allow

1160
00:35:26,757 --> 00:35:27,825
dramatic acceleration

1161
00:35:28,559 --> 00:35:30,895
in the program that has

1162
00:35:30,895 --> 00:35:31,829
been developed at Mayo.

1163
00:35:31,829 --> 00:35:33,731
As you know, Dr. Geller raised the day

1164
00:35:33,731 --> 00:35:36,467
when she came as neurosurgical chair.

1165
00:35:37,268 --> 00:35:38,536
And my boss. Your boss.

1166
00:35:38,769 --> 00:35:40,805
And when we met the first time,

1167
00:35:41,439 --> 00:35:43,074
there was a very clear realization

1168
00:35:43,407 --> 00:35:46,944
that in this field of neuromodulation,

1169
00:35:47,411 --> 00:35:48,946
we have an opportunity to

1170
00:35:48,946 --> 00:35:52,150
not necessarily make anybody

1171
00:35:52,250 --> 00:35:53,217
specifically better,

1172
00:35:53,684 --> 00:35:55,953
but potentially create the opportunity

1173
00:35:56,254 --> 00:35:57,555
for rapid acceleration.

1174
00:35:58,189 --> 00:35:58,756
That's what's really

1175
00:35:58,756 --> 00:36:00,024
exciting because, you know,

1176
00:36:00,191 --> 00:36:02,593
it's all well and good to say, you know,

1177
00:36:04,061 --> 00:36:04,829
you know, we brought

1178
00:36:04,829 --> 00:36:06,330
something from a discovery

1179
00:36:06,564 --> 00:36:09,400
to a very good treatment, but

1180
00:36:09,400 --> 00:36:11,035
still 25 years of your life.

1181
00:36:11,669 --> 00:36:12,069
Yeah. I mean,

1182
00:36:12,069 --> 00:36:14,105
we should be really moving quicker.

1183
00:36:14,572 --> 00:36:15,273
And the other thing

1184
00:36:15,273 --> 00:36:16,707
that's very evident, I think,

1185
00:36:17,308 --> 00:36:20,545
is the incredible enthusiasm

1186
00:36:20,811 --> 00:36:22,480
and the desire to move things rapidly.

1187
00:36:22,747 --> 00:36:24,048
Sure. But in order to move things

1188
00:36:24,148 --> 00:36:26,851
rapidly, you need to have team science,

1189
00:36:27,084 --> 00:36:28,653
infrastructure, and funding.

1190
00:36:29,153 --> 00:36:30,121
Yeah, well, so coming

1191
00:36:30,121 --> 00:36:31,422
to the subject of funding

1192
00:36:31,756 --> 00:36:33,958
and its role in research,

1193
00:36:33,958 --> 00:36:34,592
obviously there's some

1194
00:36:34,592 --> 00:36:37,228
challenges with the NIH right now.

1195
00:36:37,228 --> 00:36:38,529
Hopefully by the time this

1196
00:36:38,529 --> 00:36:40,131
airs, those will be resolved,

1197
00:36:40,131 --> 00:36:41,499
but they may or may not be.

1198
00:36:41,933 --> 00:36:43,100
But the example that you gave

1199
00:36:43,100 --> 00:36:43,634
where you're talking

1200
00:36:43,634 --> 00:36:44,869
about neuromyloistoptica,

1201
00:36:45,469 --> 00:36:46,304
this really doesn't

1202
00:36:46,304 --> 00:36:47,705
affect a lot of people

1203
00:36:48,072 --> 00:36:48,906
as a percentage of

1204
00:36:48,906 --> 00:36:49,907
the general population.

1205
00:36:50,575 --> 00:36:51,976
And yet you had a team of people

1206
00:36:51,976 --> 00:36:53,344
where they were all working on it,

1207
00:36:53,444 --> 00:36:55,012
and they had some kind of support

1208
00:36:55,012 --> 00:36:55,580
within the same

1209
00:36:55,580 --> 00:36:57,715
institution to study and treat,

1210
00:36:58,049 --> 00:36:59,850
ultimately to look epidemiologically

1211
00:37:00,051 --> 00:37:02,920
at a relatively narrow indication.

1212
00:37:03,888 --> 00:37:05,523
And because that was

1213
00:37:05,523 --> 00:37:06,390
understood very well,

1214
00:37:06,390 --> 00:37:06,958
it sounds like there are a

1215
00:37:06,958 --> 00:37:07,825
lot of general principles

1216
00:37:07,825 --> 00:37:08,960
that have allowed for a

1217
00:37:08,960 --> 00:37:09,827
lot of other therapies.

1218
00:37:10,428 --> 00:37:11,729
And something that I wonder about,

1219
00:37:11,729 --> 00:37:12,230
and something that

1220
00:37:12,230 --> 00:37:13,064
seems to be a challenge,

1221
00:37:13,431 --> 00:37:14,465
is something I would

1222
00:37:14,465 --> 00:37:15,666
hope we could do at Mayo,

1223
00:37:15,666 --> 00:37:17,368
is to identify a few

1224
00:37:17,368 --> 00:37:20,104
great model situations.

1225
00:37:20,838 --> 00:37:22,206
ALS is another one.

1226
00:37:22,506 --> 00:37:23,207
Even though they affect

1227
00:37:23,207 --> 00:37:24,609
people relatively rarely,

1228
00:37:25,076 --> 00:37:25,743
as a percentage of

1229
00:37:25,743 --> 00:37:26,611
the general population,

1230
00:37:27,144 --> 00:37:28,813
there are certain aspects of them

1231
00:37:28,879 --> 00:37:30,147
that may allow us to

1232
00:37:30,147 --> 00:37:31,315
have very general therapies.

1233
00:37:31,949 --> 00:37:33,184
But it's hard to make those arguments

1234
00:37:33,417 --> 00:37:34,819
when you're going to funding agencies

1235
00:37:34,819 --> 00:37:36,454
where they say, well, the impact of that

1236
00:37:36,487 --> 00:37:38,823
compared with, say, epilepsy affects

1237
00:37:39,690 --> 00:37:41,826
much larger percentage of the population.

1238
00:37:42,426 --> 00:37:43,494
Now the problem there, of course,

1239
00:37:43,494 --> 00:37:45,963
is that epilepsy is a remarkably

1240
00:37:45,963 --> 00:37:46,998
heterogeneous disease.

1241
00:37:47,298 --> 00:37:48,966
That there are many, many,

1242
00:37:48,966 --> 00:37:50,067
many different types of things

1243
00:37:50,067 --> 00:37:51,135
that cause epilepsy.

1244
00:37:51,769 --> 00:37:52,136
And when you're

1245
00:37:52,136 --> 00:37:53,738
talking to funding agencies,

1246
00:37:53,738 --> 00:37:55,573
and you're talking to leadership,

1247
00:37:55,940 --> 00:37:57,275
and you're talking to potential donors,

1248
00:37:58,209 --> 00:37:59,710
you run into this problem of,

1249
00:38:00,177 --> 00:38:00,611
when you're trying to

1250
00:38:00,611 --> 00:38:01,612
describe the impact,

1251
00:38:01,612 --> 00:38:03,247
it's always comparing it

1252
00:38:03,247 --> 00:38:04,315
against what are perceived

1253
00:38:04,315 --> 00:38:05,583
to be very large diseases,

1254
00:38:05,583 --> 00:38:06,284
even though they may

1255
00:38:06,284 --> 00:38:09,220
have relatively very varied

1256
00:38:09,687 --> 00:38:10,721
and very heterogeneous

1257
00:38:10,721 --> 00:38:11,956
underlying mechanisms.

1258
00:38:12,657 --> 00:38:13,524
It's just hard to make that

1259
00:38:13,524 --> 00:38:14,825
case for the well-controlled,

1260
00:38:15,493 --> 00:38:17,995
because a well-controlled clinical milieu

1261
00:38:18,162 --> 00:38:21,098
to have scientific discoveries in

1262
00:38:21,432 --> 00:38:23,968
actually is, in many ways,

1263
00:38:25,336 --> 00:38:26,704
a better situation as

1264
00:38:26,704 --> 00:38:27,772
a clinician scientist

1265
00:38:27,938 --> 00:38:30,408
to make an impact because you can

1266
00:38:30,408 --> 00:38:31,309
constrain the problem

1267
00:38:31,642 --> 00:38:33,444
to a set of essential scientific

1268
00:38:33,444 --> 00:38:35,212
questions you can address,

1269
00:38:35,713 --> 00:38:37,014
a set of strategies that

1270
00:38:37,014 --> 00:38:38,516
are gonna be fairly similar

1271
00:38:38,616 --> 00:38:40,651
across that population of people.

1272
00:38:41,252 --> 00:38:41,852
And it's something I

1273
00:38:41,852 --> 00:38:42,787
think we certainly hope

1274
00:38:42,787 --> 00:38:43,554
to leverage at Mayo

1275
00:38:43,554 --> 00:38:44,255
is the fact that people

1276
00:38:44,255 --> 00:38:45,156
will come here from a

1277
00:38:45,156 --> 00:38:46,023
lot of different places

1278
00:38:46,590 --> 00:38:48,326
because we concentrate expertise

1279
00:38:48,626 --> 00:38:50,227
in things that are relatively focused.

1280
00:38:51,095 --> 00:38:51,929
I suppose what I would

1281
00:38:51,929 --> 00:38:52,997
say to that would be,

1282
00:38:53,731 --> 00:38:54,465
first of all, I think

1283
00:38:54,465 --> 00:38:55,466
what Mayo does great

1284
00:38:55,466 --> 00:38:57,435
is we see the rare, we know the rare,

1285
00:38:58,002 --> 00:38:59,670
and we're very good at helping the rare.

1286
00:39:00,237 --> 00:39:02,106
But I would say that what we

1287
00:39:02,106 --> 00:39:03,207
really are talking about here

1288
00:39:03,207 --> 00:39:04,175
is the power of rare.

1289
00:39:05,476 --> 00:39:10,381
And that's why, the very reason why,

1290
00:39:10,381 --> 00:39:11,949
you need to have an

1291
00:39:11,949 --> 00:39:14,051
infrastructure built around the program.

1292
00:39:15,386 --> 00:39:16,687
Because within the program,

1293
00:39:17,188 --> 00:39:18,356
sometimes all you're

1294
00:39:18,356 --> 00:39:19,490
doing is rare disease,

1295
00:39:19,757 --> 00:39:21,192
but when you put all the

1296
00:39:21,192 --> 00:39:22,259
rare diseases together,

1297
00:39:22,626 --> 00:39:23,494
they're not so rare.

1298
00:39:24,228 --> 00:39:27,164
In fact, if you look at the diseases

1299
00:39:27,365 --> 00:39:27,965
that people are

1300
00:39:27,965 --> 00:39:29,333
coming to Mayo Clinic with,

1301
00:39:29,834 --> 00:39:31,302
I guarantee you if you

1302
00:39:31,302 --> 00:39:33,104
add up all the rares,

1303
00:39:33,871 --> 00:39:35,439
they will make up a significant

1304
00:39:35,439 --> 00:39:36,707
proportion of the patients.

1305
00:39:37,675 --> 00:39:38,576
Now, to give you an

1306
00:39:38,576 --> 00:39:40,644
example, NMOSD is rare,

1307
00:39:41,479 --> 00:39:43,914
but it was thought to be very, very rare.

1308
00:39:44,849 --> 00:39:46,016
And then when we figured out and

1309
00:39:46,016 --> 00:39:47,051
discovered the biomarker,

1310
00:39:47,151 --> 00:39:48,686
we could do biomarker-based,

1311
00:39:48,919 --> 00:39:49,954
population-based studies.

1312
00:39:50,955 --> 00:39:51,822
And what did we find?

1313
00:39:52,523 --> 00:39:53,591
It wasn't so rare.

1314
00:39:54,391 --> 00:39:55,893
So what we did was we took

1315
00:39:55,893 --> 00:39:57,595
every patient in Homestead County

1316
00:39:58,129 --> 00:39:59,130
that had any form of

1317
00:39:59,130 --> 00:40:00,064
inflammatory brain disease,

1318
00:40:00,064 --> 00:40:00,865
and we tested them for

1319
00:40:00,865 --> 00:40:01,766
the water channel antibody,

1320
00:40:01,766 --> 00:40:02,933
which happens to be 100%

1321
00:40:03,400 --> 00:40:04,902
sensitive and 100% specific.

1322
00:40:06,270 --> 00:40:09,607
Then we went to the French West Indies

1323
00:40:09,807 --> 00:40:11,041
where a neurologist

1324
00:40:11,041 --> 00:40:12,610
happens to just travel around

1325
00:40:13,010 --> 00:40:14,678
seeing his patients and collecting bloods

1326
00:40:14,678 --> 00:40:15,813
on every single patient he sees,

1327
00:40:16,147 --> 00:40:16,647
because he was a

1328
00:40:16,647 --> 00:40:18,182
fourth-thinking guy, just on his own.

1329
00:40:18,816 --> 00:40:19,483
And he had collected

1330
00:40:19,483 --> 00:40:20,785
bloods on every patient

1331
00:40:20,785 --> 00:40:22,319
with inflammatory brain disease on the

1332
00:40:22,319 --> 00:40:23,254
island of Martinique.

1333
00:40:24,088 --> 00:40:25,356
These are Afro-Caribbeans,

1334
00:40:25,689 --> 00:40:26,690
and we tested them all

1335
00:40:26,690 --> 00:40:27,892
for water channel antibody,

1336
00:40:27,892 --> 00:40:30,795
and we found that in Afro-Caribbeans,

1337
00:40:32,563 --> 00:40:33,964
10 patients in every

1338
00:40:33,964 --> 00:40:36,167
100,000 had the disease, okay?

1339
00:40:36,867 --> 00:40:38,636
So you then start to

1340
00:40:38,636 --> 00:40:40,204
study the disease in Africans,

1341
00:40:40,671 --> 00:40:42,106
and you find out that actually,

1342
00:40:42,540 --> 00:40:43,507
it's about four times

1343
00:40:43,507 --> 00:40:44,375
more common in Africans

1344
00:40:44,642 --> 00:40:45,176
than in whites.

1345
00:40:46,710 --> 00:40:48,846
And globally, there's probably about a

1346
00:40:48,846 --> 00:40:49,580
half a million people

1347
00:40:49,580 --> 00:40:50,214
with the disease.

1348
00:40:50,948 --> 00:40:51,849
Then you use the

1349
00:40:51,849 --> 00:40:53,651
infrastructure and the know-how

1350
00:40:53,651 --> 00:40:54,752
that you learned from that

1351
00:40:54,752 --> 00:40:56,253
disease to get to a treatment,

1352
00:40:56,554 --> 00:40:57,655
and you apply it to what?

1353
00:40:57,988 --> 00:40:58,689
Well, to MoGAD.

1354
00:40:59,690 --> 00:41:01,025
MoGAD is a neurodisease,

1355
00:41:01,525 --> 00:41:02,793
but we have just

1356
00:41:02,793 --> 00:41:04,228
completed a phase three trial

1357
00:41:04,695 --> 00:41:06,897
that potentially we hope is

1358
00:41:06,897 --> 00:41:08,165
going to show positive results.

1359
00:41:08,766 --> 00:41:09,633
And so now we're

1360
00:41:09,633 --> 00:41:12,102
beginning to apply the know-how

1361
00:41:12,503 --> 00:41:14,004
of one rare disease to

1362
00:41:14,004 --> 00:41:15,039
another rare disease,

1363
00:41:15,339 --> 00:41:15,940
and what you're gonna

1364
00:41:15,940 --> 00:41:17,474
start seeing is that the rate

1365
00:41:17,908 --> 00:41:18,876
or the time that it takes

1366
00:41:18,876 --> 00:41:19,910
to go from the discovery

1367
00:41:20,110 --> 00:41:22,112
to the cure or a

1368
00:41:22,112 --> 00:41:24,281
treatment is gonna start dropping

1369
00:41:24,281 --> 00:41:25,049
and dropping and dropping.

1370
00:41:25,449 --> 00:41:27,384
The same with these very unusual

1371
00:41:27,885 --> 00:41:29,286
pediatric genetic diseases.

1372
00:41:29,487 --> 00:41:30,354
I mean, what we need is

1373
00:41:30,354 --> 00:41:31,388
we need an infrastructure

1374
00:41:31,655 --> 00:41:36,894
around very rare genetic diseases

1375
00:41:37,995 --> 00:41:39,363
so that we can have a

1376
00:41:39,363 --> 00:41:40,531
pipeline of patients

1377
00:41:40,731 --> 00:41:44,468
that are coming in with rare disease X,

1378
00:41:45,302 --> 00:41:48,839
pipeline of N of one gene therapeutics.

1379
00:41:49,740 --> 00:41:53,310
And as you build that infrastructure,

1380
00:41:53,310 --> 00:41:54,144
you'll be able to do that.

1381
00:41:54,645 --> 00:41:56,514
And also the concept of repurposing.

1382
00:41:56,914 --> 00:41:58,148
I mean, you're putting an

1383
00:41:58,148 --> 00:41:59,183
electrode into a patient

1384
00:41:59,183 --> 00:41:59,884
that has epilepsy.

1385
00:42:00,251 --> 00:42:01,585
You're assisting with

1386
00:42:01,585 --> 00:42:04,822
the electrode implantation

1387
00:42:04,889 --> 00:42:06,290
for moving disorders,

1388
00:42:06,523 --> 00:42:07,658
Parkinson's disease, whatever.

1389
00:42:08,592 --> 00:42:10,361
But you know that once

1390
00:42:10,361 --> 00:42:12,563
you've got that smoothly running

1391
00:42:12,963 --> 00:42:14,732
and it's just a, now we

1392
00:42:14,732 --> 00:42:15,633
just do it on everybody

1393
00:42:15,633 --> 00:42:16,634
that has that disease,

1394
00:42:17,034 --> 00:42:17,835
then what you're gonna do

1395
00:42:17,835 --> 00:42:18,669
is you're gonna start saying,

1396
00:42:18,669 --> 00:42:19,470
well, what happens if I

1397
00:42:19,470 --> 00:42:20,304
put that into a patient

1398
00:42:20,304 --> 00:42:21,071
that has insomnia?

1399
00:42:22,072 --> 00:42:22,306
Sure.

1400
00:42:22,306 --> 00:42:23,774
What happens if I put that into a patient

1401
00:42:23,774 --> 00:42:26,911
that has a neurodegenerative disease?

1402
00:42:27,545 --> 00:42:28,712
What happens if I put that patient

1403
00:42:28,712 --> 00:42:30,481
into a patient with a dystonia?

1404
00:42:31,715 --> 00:42:33,117
Suddenly now you're into the rare,

1405
00:42:33,384 --> 00:42:36,353
but you're using a fix that

1406
00:42:36,353 --> 00:42:37,488
you're very familiar with.

1407
00:42:37,755 --> 00:42:38,789
And then you start to

1408
00:42:38,789 --> 00:42:40,391
rapidly and accelerate,

1409
00:42:40,391 --> 00:42:41,325
I think, treatment options

1410
00:42:41,325 --> 00:42:42,359
for those types of patients.

1411
00:42:43,227 --> 00:42:45,529
And sort of, and don't let

1412
00:42:45,529 --> 00:42:46,463
me ask all the questions.

1413
00:42:46,463 --> 00:42:46,964
I'm sorry.

1414
00:42:47,631 --> 00:42:49,733
But as the leaders of

1415
00:42:49,733 --> 00:42:52,469
neurology and research

1416
00:42:52,603 --> 00:42:53,604
within neurology and

1417
00:42:53,604 --> 00:42:55,639
innovation in sort of clinical

1418
00:42:55,639 --> 00:42:57,007
and neurological sciences here,

1419
00:42:57,575 --> 00:42:59,209
to what degree do you feel

1420
00:42:59,209 --> 00:43:01,145
that things should be top down,

1421
00:43:01,145 --> 00:43:02,846
meaning you identify priorities

1422
00:43:04,715 --> 00:43:05,549
that you feel that the

1423
00:43:05,549 --> 00:43:06,450
institution should have

1424
00:43:06,617 --> 00:43:09,019
within your sphere of influence

1425
00:43:09,954 --> 00:43:11,956
versus waiting for

1426
00:43:11,956 --> 00:43:14,091
interesting opportunities

1427
00:43:14,091 --> 00:43:17,394
to come bottom up from the scientists

1428
00:43:17,728 --> 00:43:19,163
and clinicians here at Mayo.

1429
00:43:20,164 --> 00:43:21,332
What does that balance look

1430
00:43:21,332 --> 00:43:23,200
like for you guys as a team?

1431
00:43:25,169 --> 00:43:25,769
Yeah, I mean, I think that

1432
00:43:25,769 --> 00:43:27,705
is always kind of a tension

1433
00:43:28,505 --> 00:43:31,208
in leadership because I think many of the

1434
00:43:31,208 --> 00:43:32,643
most brilliant ideas

1435
00:43:32,643 --> 00:43:33,777
and brilliant innovations

1436
00:43:33,777 --> 00:43:35,145
are coming from the bottom up.

1437
00:43:35,646 --> 00:43:37,948
People who have deep content expertise

1438
00:43:38,282 --> 00:43:40,351
and have been studying it for years

1439
00:43:41,051 --> 00:43:42,152
and can make the

1440
00:43:42,152 --> 00:43:43,654
breakthroughs and bring them through.

1441
00:43:44,288 --> 00:43:45,289
I think one thing

1442
00:43:45,289 --> 00:43:46,924
that Mayo does very well

1443
00:43:47,291 --> 00:43:48,258
is that because

1444
00:43:48,258 --> 00:43:50,561
there's kind of the ecosystem

1445
00:43:51,095 --> 00:43:53,130
of basic scientists,

1446
00:43:53,664 --> 00:43:54,832
translational scientists,

1447
00:43:55,165 --> 00:43:56,834
clinicians, clinical trialists,

1448
00:43:57,234 --> 00:43:58,902
that I think we're, as

1449
00:43:58,902 --> 00:44:00,404
it was shown with NMO,

1450
00:44:01,005 --> 00:44:02,706
there's a way to very quickly bring

1451
00:44:02,706 --> 00:44:04,108
things to the clinic

1452
00:44:04,408 --> 00:44:05,843
once the discoveries are made,

1453
00:44:06,243 --> 00:44:09,146
but that still is a bottom up approach.

1454
00:44:09,947 --> 00:44:11,015
I mean, I do think that

1455
00:44:11,015 --> 00:44:13,350
when there are scenarios

1456
00:44:13,684 --> 00:44:15,719
where we clearly have

1457
00:44:15,719 --> 00:44:18,489
strengths that need to be amplified,

1458
00:44:18,756 --> 00:44:20,624
that need to be accelerated,

1459
00:44:21,191 --> 00:44:22,793
that's where I think the top down

1460
00:44:22,793 --> 00:44:24,128
approach comes better,

1461
00:44:24,662 --> 00:44:27,765
where, for example, with neuromodulation

1462
00:44:27,765 --> 00:44:28,932
and the Bionic Initiative,

1463
00:44:29,466 --> 00:44:32,803
we have a key number of people and groups

1464
00:44:33,070 --> 00:44:34,471
who've been working on their own,

1465
00:44:34,471 --> 00:44:35,272
kind of hustling and

1466
00:44:35,272 --> 00:44:37,274
doing great work on their own,

1467
00:44:37,675 --> 00:44:39,610
and leadership saw that

1468
00:44:39,610 --> 00:44:41,845
that would go much faster

1469
00:44:42,079 --> 00:44:43,380
if we were able to put

1470
00:44:43,380 --> 00:44:44,715
the infrastructure around it

1471
00:44:45,049 --> 00:44:46,316
and give it the funding and

1472
00:44:46,316 --> 00:44:48,252
get it moving all together

1473
00:44:48,252 --> 00:44:49,153
and working together

1474
00:44:49,153 --> 00:44:50,587
for a singular purpose

1475
00:44:50,788 --> 00:44:52,823
and maybe spend a little less time

1476
00:44:52,823 --> 00:44:53,991
hustling on your own

1477
00:44:53,991 --> 00:44:56,293
and maybe focusing the

1478
00:44:56,293 --> 00:44:58,128
spear a little bit more directly

1479
00:44:58,595 --> 00:44:59,163
toward the future.

1480
00:45:00,264 --> 00:45:02,666
But I think you can only do that

1481
00:45:02,666 --> 00:45:03,767
if you have the people

1482
00:45:03,767 --> 00:45:04,768
there to do it already.

1483
00:45:05,536 --> 00:45:08,305
So, obviously with neuromodulation,

1484
00:45:08,539 --> 00:45:10,574
it's been decades of

1485
00:45:10,574 --> 00:45:12,476
hiring the right people,

1486
00:45:12,476 --> 00:45:13,143
training the right

1487
00:45:13,143 --> 00:45:14,711
people, building the teams

1488
00:45:15,813 --> 00:45:18,215
to where it's now ready to go full tilt.

1489
00:45:19,149 --> 00:45:20,384
You can't just kind of come

1490
00:45:20,384 --> 00:45:21,452
in and say, all right, here,

1491
00:45:22,086 --> 00:45:23,220
we need to become the

1492
00:45:23,220 --> 00:45:25,756
world's expert in X, Y, or Z,

1493
00:45:25,756 --> 00:45:27,191
and we don't have anybody to do it.

1494
00:45:27,891 --> 00:45:30,194
It takes a while to move that forward.

1495
00:45:30,561 --> 00:45:32,596
I will say getting Keith Coffin,

1496
00:45:33,197 --> 00:45:34,765
who went from having some

1497
00:45:34,765 --> 00:45:35,966
pediatric dystonia patients

1498
00:45:35,966 --> 00:45:36,967
to having many and being

1499
00:45:36,967 --> 00:45:37,901
able to leverage expertise

1500
00:45:38,035 --> 00:45:39,236
by sort of poaching

1501
00:45:39,236 --> 00:45:40,404
that one key individual.

1502
00:45:41,105 --> 00:45:42,606
No, I really agree with

1503
00:45:42,606 --> 00:45:43,674
what Nathan said there.

1504
00:45:43,874 --> 00:45:45,876
I think it becomes very

1505
00:45:45,876 --> 00:45:47,211
evident when you're buried

1506
00:45:47,411 --> 00:45:49,413
in a program of research,

1507
00:45:50,347 --> 00:45:51,515
the pieces of the

1508
00:45:51,515 --> 00:45:52,316
puzzle that are missing.

1509
00:45:53,684 --> 00:45:55,385
At the end of the day, you

1510
00:45:55,385 --> 00:45:56,520
have to build your program

1511
00:45:56,753 --> 00:45:58,055
around the people that you have,

1512
00:45:58,055 --> 00:45:59,089
because it's the

1513
00:45:59,089 --> 00:46:00,858
people that do all the work.

1514
00:46:01,759 --> 00:46:05,129
But you can be in a scenario where you

1515
00:46:05,129 --> 00:46:07,297
are missing a piece.

1516
00:46:08,599 --> 00:46:09,500
I'll give you an example.

1517
00:46:09,766 --> 00:46:10,734
In the world that we were

1518
00:46:10,734 --> 00:46:12,436
working in in neuromodology,

1519
00:46:14,004 --> 00:46:15,305
it was evident that we

1520
00:46:15,305 --> 00:46:17,107
were missing a B cell expert.

1521
00:46:17,674 --> 00:46:19,943
And so what we did was we went out

1522
00:46:20,077 --> 00:46:23,347
and we recruited Sarasharani from Oxford,

1523
00:46:23,847 --> 00:46:26,216
who is the head of

1524
00:46:26,216 --> 00:46:27,451
neuromodology at Oxford.

1525
00:46:27,851 --> 00:46:30,754
We recruited him, but he wasn't willing

1526
00:46:30,754 --> 00:46:32,055
to come to Minnesota

1527
00:46:32,055 --> 00:46:34,691
because he wanted the warmth.

1528
00:46:37,127 --> 00:46:38,428
So we recruited him to

1529
00:46:38,428 --> 00:46:39,563
Jacksonville, Florida,

1530
00:46:39,830 --> 00:46:40,731
where he's doing great.

1531
00:46:41,231 --> 00:46:41,932
And we interact with

1532
00:46:41,932 --> 00:46:43,033
him on a monthly basis.

1533
00:46:43,033 --> 00:46:44,134
We have blood samples and

1534
00:46:44,134 --> 00:46:45,769
samples going up and down

1535
00:46:45,869 --> 00:46:48,272
and combined papers and

1536
00:46:48,272 --> 00:46:49,673
research papers and collaboration.

1537
00:46:50,774 --> 00:46:53,243
And so I think that's where

1538
00:46:53,243 --> 00:46:54,745
leadership can, I think, help,

1539
00:46:54,745 --> 00:46:59,616
because there's great stuff going on,

1540
00:46:59,616 --> 00:47:00,751
but it can become very

1541
00:47:00,751 --> 00:47:03,320
evident that if we had that cog

1542
00:47:03,887 --> 00:47:05,389
in the watch, then the

1543
00:47:05,389 --> 00:47:06,523
watch would work perfectly

1544
00:47:07,291 --> 00:47:08,525
and everybody would benefit.

1545
00:47:08,959 --> 00:47:10,427
One of the things that I really dislike

1546
00:47:10,761 --> 00:47:12,529
about the potential of

1547
00:47:12,529 --> 00:47:15,365
leadership is the tendency sometimes

1548
00:47:15,566 --> 00:47:18,035
for leaders to decide on what

1549
00:47:18,035 --> 00:47:19,603
they think is best for people.

1550
00:47:20,537 --> 00:47:21,772
And then try to force

1551
00:47:21,772 --> 00:47:23,707
a circle into a square.

1552
00:47:24,775 --> 00:47:25,842
That's highly problematic.

1553
00:47:26,443 --> 00:47:27,911
And so I think that, and I

1554
00:47:27,911 --> 00:47:29,213
think you'd agree with me,

1555
00:47:29,213 --> 00:47:32,115
that the job of research

1556
00:47:32,115 --> 00:47:33,884
leadership is to, first of all,

1557
00:47:33,884 --> 00:47:35,652
identify the strengths of the

1558
00:47:35,652 --> 00:47:36,920
individuals in the department,

1559
00:47:38,088 --> 00:47:43,260
to have a broad vision for where we want

1560
00:47:43,260 --> 00:47:44,361
to go in the future,

1561
00:47:46,129 --> 00:47:47,831
and figure out who in

1562
00:47:47,831 --> 00:47:49,867
the department is aligned

1563
00:47:50,133 --> 00:47:52,069
with that vision, and then

1564
00:47:52,069 --> 00:47:53,537
try to figure out what is it

1565
00:47:53,537 --> 00:47:55,405
that they need to do what

1566
00:47:55,405 --> 00:47:56,607
they need to do quicker.

1567
00:47:57,507 --> 00:48:00,410
Because for me, we have a lot of really,

1568
00:48:00,410 --> 00:48:01,311
really brilliant people,

1569
00:48:01,612 --> 00:48:02,746
but we need to accelerate.

1570
00:48:03,580 --> 00:48:06,250
And it's the-- and why

1571
00:48:06,250 --> 00:48:07,317
do we want to accelerate?

1572
00:48:07,317 --> 00:48:08,986
Because I'm sick of

1573
00:48:08,986 --> 00:48:11,121
sitting in the room with patients

1574
00:48:11,755 --> 00:48:14,424
who have bad disease and

1575
00:48:14,424 --> 00:48:15,692
not being able to provide them

1576
00:48:15,692 --> 00:48:17,127
with what I would want

1577
00:48:17,127 --> 00:48:18,128
if I was sitting there.

1578
00:48:18,829 --> 00:48:22,132
And so there is an anxiety

1579
00:48:22,132 --> 00:48:25,335
and a need to move quicker.

1580
00:48:26,003 --> 00:48:28,472
That's what I think leadership has to do.

1581
00:48:28,472 --> 00:48:30,440
We have to make sure

1582
00:48:30,440 --> 00:48:31,942
that the individuals that

1583
00:48:31,942 --> 00:48:32,809
are working in the

1584
00:48:32,809 --> 00:48:34,244
department are working and aligned

1585
00:48:34,444 --> 00:48:35,178
with the vision.

1586
00:48:35,178 --> 00:48:36,079
And the vision for our

1587
00:48:36,079 --> 00:48:37,114
department in neurology

1588
00:48:37,414 --> 00:48:38,415
is very simple.

1589
00:48:38,415 --> 00:48:39,216
It's connected to cure.

1590
00:48:39,850 --> 00:48:40,784
Anything that moves a

1591
00:48:40,784 --> 00:48:42,085
patient towards a better treatment

1592
00:48:42,319 --> 00:48:43,820
outcome is priority.

1593
00:48:44,721 --> 00:48:45,756
And actually, then if you

1594
00:48:45,756 --> 00:48:46,657
go through each individual

1595
00:48:47,057 --> 00:48:48,292
in the department,

1596
00:48:48,292 --> 00:48:49,293
you'll find that everybody

1597
00:48:49,293 --> 00:48:50,927
is connected to cure in some way.

1598
00:48:51,495 --> 00:48:52,329
And the question is just

1599
00:48:52,329 --> 00:48:53,563
how do you augment that?

1600
00:48:54,831 --> 00:48:56,466
And there are many ways of doing that.

1601
00:48:56,466 --> 00:48:58,235
But it's a tough job.

1602
00:48:58,802 --> 00:48:59,236
Would you agree?

1603
00:49:01,371 --> 00:49:03,206
It has its challenges.

1604
00:49:04,107 --> 00:49:05,108
We have a lot of good people.

1605
00:49:05,575 --> 00:49:09,680
I think the other part is trying to

1606
00:49:09,680 --> 00:49:11,515
foster junior faculty

1607
00:49:12,282 --> 00:49:16,186
and provide the protection

1608
00:49:16,186 --> 00:49:18,422
to have the brilliant thoughts

1609
00:49:18,422 --> 00:49:19,923
in the development of the program,

1610
00:49:21,091 --> 00:49:21,925
whether that's time

1611
00:49:21,925 --> 00:49:22,926
protection, whether that's

1612
00:49:22,926 --> 00:49:23,994
financial protection.

1613
00:49:24,995 --> 00:49:31,435
And be fairly equal initially.

1614
00:49:31,802 --> 00:49:35,272
And then as people start to show how

1615
00:49:35,272 --> 00:49:37,507
they're going to be successful, start

1616
00:49:37,574 --> 00:49:39,009
to move the chips

1617
00:49:39,009 --> 00:49:41,311
around and try to accelerate

1618
00:49:41,578 --> 00:49:43,947
the people who are showing that they have

1619
00:49:43,947 --> 00:49:44,915
the fire in the belly

1620
00:49:44,948 --> 00:49:46,650
to move things forward quicker.

1621
00:49:47,784 --> 00:49:51,121
How about-- and I kind of--

1622
00:49:51,121 --> 00:49:53,590
am I only thinking of myself like this

1623
00:49:53,590 --> 00:49:55,592
and certain other people

1624
00:49:55,592 --> 00:49:57,394
that I may know-- as folks

1625
00:49:57,394 --> 00:49:58,895
who are driven by problems

1626
00:49:58,895 --> 00:50:01,665
that they come into in the course of

1627
00:50:01,665 --> 00:50:02,666
their clinical practice,

1628
00:50:03,333 --> 00:50:04,468
and they're at home

1629
00:50:04,468 --> 00:50:06,003
developing some solution.

1630
00:50:06,236 --> 00:50:07,170
Like they might develop a new

1631
00:50:07,170 --> 00:50:10,307
software program for the EMG

1632
00:50:10,340 --> 00:50:12,609
lab and movement like Brian has.

1633
00:50:13,410 --> 00:50:16,146
But at the end of the day, they don't

1634
00:50:16,146 --> 00:50:17,848
want to lead a large

1635
00:50:17,848 --> 00:50:19,583
multidisciplinary initiative

1636
00:50:19,583 --> 00:50:20,784
and have people below them.

1637
00:50:20,784 --> 00:50:21,651
What they want to do is

1638
00:50:21,651 --> 00:50:23,487
they're driven for the pat--

1639
00:50:23,487 --> 00:50:24,888
their passion for the patient.

1640
00:50:25,389 --> 00:50:29,292
And they want to be the person who

1641
00:50:29,292 --> 00:50:30,961
identifies some particular problem

1642
00:50:30,961 --> 00:50:32,696
that they have and then

1643
00:50:32,696 --> 00:50:35,232
target that one thing.

1644
00:50:35,732 --> 00:50:37,868
But the problem that you run into is that

1645
00:50:37,868 --> 00:50:39,469
you want to empower those people

1646
00:50:39,703 --> 00:50:41,438
to-- and I feel like I'm using catchword

1647
00:50:41,438 --> 00:50:42,372
after catchword, right?

1648
00:50:42,572 --> 00:50:44,641
But you want to empower those people to

1649
00:50:44,641 --> 00:50:47,110
leverage this moment of insight

1650
00:50:47,110 --> 00:50:48,245
that they may have on

1651
00:50:48,245 --> 00:50:49,112
an intermittent basis

1652
00:50:49,146 --> 00:50:51,048
because they're passionate about the

1653
00:50:51,048 --> 00:50:53,884
substance of the clinical questions

1654
00:50:53,884 --> 00:50:54,985
that they have and then

1655
00:50:54,985 --> 00:50:58,088
applying their unique tools.

1656
00:50:58,388 --> 00:50:59,756
So the way that they think

1657
00:50:59,756 --> 00:51:01,525
about operating ham radio

1658
00:51:01,625 --> 00:51:05,495
may help them come up with a better way

1659
00:51:05,495 --> 00:51:06,696
to program a DBS device.

1660
00:51:07,063 --> 00:51:10,233
But how do you have a system that works

1661
00:51:10,233 --> 00:51:11,968
reliably as a department

1662
00:51:12,436 --> 00:51:13,737
where you have people that are

1663
00:51:13,737 --> 00:51:15,872
consistently delivering clinical care

1664
00:51:15,872 --> 00:51:18,041
but then in an intermittent fashion, they

1665
00:51:18,041 --> 00:51:20,710
may need more time to do that key thing.

1666
00:51:21,011 --> 00:51:22,179
And they're not trying to

1667
00:51:22,179 --> 00:51:24,448
do maybe something that's

1668
00:51:24,448 --> 00:51:25,248
much larger and much

1669
00:51:25,248 --> 00:51:26,783
different than they otherwise did.

1670
00:51:26,783 --> 00:51:28,985
I'm very much grateful and in awe of

1671
00:51:28,985 --> 00:51:30,053
people that are in leadership

1672
00:51:30,053 --> 00:51:31,988
like you guys are, but I wouldn't want

1673
00:51:31,988 --> 00:51:34,825
that myself because it's just not

1674
00:51:34,825 --> 00:51:35,692
what motivates me.

1675
00:51:36,026 --> 00:51:37,427
But if you had some situation where

1676
00:51:37,427 --> 00:51:38,562
you're supposed to be pushed into that

1677
00:51:39,596 --> 00:51:41,665
in order to go to that next step because

1678
00:51:41,665 --> 00:51:42,866
that's the standard mold

1679
00:51:43,333 --> 00:51:46,403
that in many institutions, leaders see

1680
00:51:46,403 --> 00:51:48,772
and funding agencies support.

1681
00:51:49,506 --> 00:51:50,907
But if you look at the history of

1682
00:51:50,907 --> 00:51:52,609
breakthroughs in science and medicine,

1683
00:51:53,643 --> 00:51:55,612
they are often made by the people who--

1684
00:51:56,046 --> 00:51:57,547
their goal isn't to make breakthroughs

1685
00:51:57,547 --> 00:51:58,548
in science and medicine.

1686
00:51:58,548 --> 00:51:59,950
Their goal is to take

1687
00:51:59,950 --> 00:52:00,817
care of patients and they

1688
00:52:00,817 --> 00:52:02,419
happen to come across something that's

1689
00:52:02,419 --> 00:52:03,186
particularly interesting.

1690
00:52:03,820 --> 00:52:05,322
And then they need the time and the

1691
00:52:05,322 --> 00:52:06,723
resources to focus on that.

1692
00:52:07,124 --> 00:52:08,225
How do you guys make that happen?

1693
00:52:09,126 --> 00:52:11,228
How do you empower the unpredictable?

1694
00:52:13,230 --> 00:52:14,464
I think that's a really good question.

1695
00:52:14,965 --> 00:52:16,733
I don't think there's a perfect answer

1696
00:52:16,733 --> 00:52:18,568
because there are many,

1697
00:52:18,568 --> 00:52:20,303
many examples of like Nobel

1698
00:52:20,303 --> 00:52:23,940
laureates who just were

1699
00:52:23,940 --> 00:52:26,910
surprised by their success.

1700
00:52:28,345 --> 00:52:30,647
And it's very difficult because we're in

1701
00:52:30,647 --> 00:52:32,616
a situation where we

1702
00:52:32,616 --> 00:52:34,784
are kind of wanting the

1703
00:52:34,851 --> 00:52:37,521
researcher to kind of know what the

1704
00:52:37,521 --> 00:52:39,523
future holds, which is

1705
00:52:39,523 --> 00:52:40,790
very, very difficult to do.

1706
00:52:42,325 --> 00:52:44,060
So how do you manage that?

1707
00:52:44,060 --> 00:52:46,763
You've got this great idea, you want time

1708
00:52:46,763 --> 00:52:48,632
to pursue it, but it

1709
00:52:48,632 --> 00:52:51,368
is possible that that

1710
00:52:51,368 --> 00:52:56,606
great idea potentially may not be as good

1711
00:52:56,606 --> 00:52:58,341
an idea as you think it might be.

1712
00:52:59,209 --> 00:53:00,277
Or it might be the

1713
00:53:00,277 --> 00:53:02,212
next Nobel Prize winner.

1714
00:53:02,979 --> 00:53:03,580
You don't know.

1715
00:53:03,813 --> 00:53:05,949
That's why I think the benefit of having

1716
00:53:05,949 --> 00:53:08,151
a structured

1717
00:53:08,151 --> 00:53:10,453
interactive program is really,

1718
00:53:10,487 --> 00:53:12,923
very helpful because it's very helpful to

1719
00:53:12,923 --> 00:53:14,391
have somebody go,

1720
00:53:15,091 --> 00:53:15,926
"You know, I think that's

1721
00:53:15,926 --> 00:53:16,726
a really bad idea."

1722
00:53:18,161 --> 00:53:20,130
Or "Holy cow, I've

1723
00:53:20,130 --> 00:53:21,565
never thought about that.

1724
00:53:21,731 --> 00:53:22,232
That's brilliant."

1725
00:53:23,400 --> 00:53:25,168
Depending on the response that you get

1726
00:53:25,168 --> 00:53:26,937
from others, that

1727
00:53:26,937 --> 00:53:28,238
sometimes can help things move

1728
00:53:28,371 --> 00:53:28,605
along.

1729
00:53:29,005 --> 00:53:30,173
It's very, very hard to

1730
00:53:30,173 --> 00:53:32,842
know which horse to back.

1731
00:53:33,410 --> 00:53:35,412
There are many people, I've certainly

1732
00:53:35,412 --> 00:53:36,546
come across many people

1733
00:53:36,546 --> 00:53:39,449
in my career who thought

1734
00:53:39,950 --> 00:53:40,984
they were really onto a

1735
00:53:40,984 --> 00:53:43,186
big thing and they weren't.

1736
00:53:44,221 --> 00:53:45,956
They spent a lot of their careers

1737
00:53:45,956 --> 00:53:48,124
following something that

1738
00:53:48,124 --> 00:53:49,859
didn't ultimately pan out.

1739
00:53:51,061 --> 00:53:53,663
And then you meet people who have, I

1740
00:53:53,663 --> 00:53:56,032
think, discovered things or

1741
00:53:56,032 --> 00:53:58,168
developed novel technologies

1742
00:53:58,168 --> 00:53:59,202
that now we are actually

1743
00:53:59,202 --> 00:54:00,437
using in our clinical practice.

1744
00:54:01,304 --> 00:54:02,939
And generally, I would say those

1745
00:54:02,939 --> 00:54:04,207
individuals are people that

1746
00:54:04,207 --> 00:54:05,642
are very interactive, very

1747
00:54:05,709 --> 00:54:09,446
collaborative and have a lot of pots on

1748
00:54:09,446 --> 00:54:11,281
the boil and don't

1749
00:54:11,281 --> 00:54:12,249
have all their eggs in one

1750
00:54:12,249 --> 00:54:12,649
basket.

1751
00:54:14,050 --> 00:54:14,851
So I don't know.

1752
00:54:14,851 --> 00:54:17,220
I think that's a difficult situation.

1753
00:54:17,754 --> 00:54:19,589
I do think that there are many, many

1754
00:54:19,589 --> 00:54:20,824
brilliant people, I think,

1755
00:54:20,824 --> 00:54:24,361
who can become siloed and

1756
00:54:24,361 --> 00:54:26,062
kind of attached to their own ideas.

1757
00:54:26,796 --> 00:54:28,732
And that's why for those types of

1758
00:54:28,732 --> 00:54:31,401
individuals, I think they probably

1759
00:54:31,401 --> 00:54:32,936
benefit very well from

1760
00:54:33,503 --> 00:54:36,139
getting input from others that are honest

1761
00:54:36,139 --> 00:54:37,707
to try and help them move forward.

1762
00:54:38,308 --> 00:54:42,145
But I'm sure that it's highly possible

1763
00:54:42,145 --> 00:54:45,248
that the people that

1764
00:54:45,248 --> 00:54:47,183
discovered DNA might have

1765
00:54:47,183 --> 00:54:48,985
gone into their buddy next door and said,

1766
00:54:48,985 --> 00:54:49,719
what do you think of this?

1767
00:54:49,719 --> 00:54:50,920
They went, oh, I

1768
00:54:50,920 --> 00:54:52,222
wouldn't spend time on that.

1769
00:54:52,822 --> 00:54:54,591
I think it's hard to find that balance.

1770
00:54:54,791 --> 00:54:55,792
I don't think there's a

1771
00:54:55,792 --> 00:54:56,960
good answer to the question.

1772
00:54:57,260 --> 00:54:59,195
But I do think if you step back and say

1773
00:54:59,195 --> 00:55:01,398
generally, in terms of

1774
00:55:01,398 --> 00:55:02,966
things that ultimately become

1775
00:55:02,999 --> 00:55:05,135
successful, I think it's generally done

1776
00:55:05,135 --> 00:55:06,870
in a multidisciplinary

1777
00:55:06,870 --> 00:55:08,204
collaborative environment

1778
00:55:08,405 --> 00:55:11,441
where you have expertise in many, many

1779
00:55:11,441 --> 00:55:13,176
different areas all kind

1780
00:55:13,176 --> 00:55:14,844
of coming together around a

1781
00:55:14,844 --> 00:55:15,245
problem.

1782
00:55:15,245 --> 00:55:15,612
I don't know.

1783
00:55:15,612 --> 00:55:16,279
What do you think?

1784
00:55:16,713 --> 00:55:18,948
No, I think that's absolutely critical.

1785
00:55:19,215 --> 00:55:21,551
But the other thing I think is that there

1786
00:55:21,551 --> 00:55:23,853
needs to be kind of a

1787
00:55:23,853 --> 00:55:25,221
system of communication

1788
00:55:25,822 --> 00:55:26,956
that comes up to leadership.

1789
00:55:27,724 --> 00:55:29,259
So you're talking about

1790
00:55:29,259 --> 00:55:31,227
which horse to bet on.

1791
00:55:31,761 --> 00:55:33,029
If you don't know what the horses are,

1792
00:55:33,530 --> 00:55:34,331
you don't know how to bet.

1793
00:55:34,964 --> 00:55:39,169
And so having maybe-- I mean, what we

1794
00:55:39,169 --> 00:55:39,869
have in the department is

1795
00:55:39,869 --> 00:55:41,371
we have some very low-level

1796
00:55:41,371 --> 00:55:43,673
seed funding that is very easy to get.

1797
00:55:44,107 --> 00:55:46,643
You don't have to write an R01 or much of

1798
00:55:46,643 --> 00:55:47,977
anything to get

1799
00:55:47,977 --> 00:55:51,081
resources to help with statistics

1800
00:55:51,181 --> 00:55:54,584
or coordinator time or even a

1801
00:55:54,584 --> 00:55:55,652
little bit of your own time.

1802
00:55:56,252 --> 00:55:58,455
And then there's a little higher level

1803
00:55:58,455 --> 00:55:59,322
where you have to

1804
00:55:59,322 --> 00:56:00,890
maybe write a page or two.

1805
00:56:01,124 --> 00:56:03,259
And then it keeps going up as you get

1806
00:56:03,259 --> 00:56:04,494
kind of more invested in it.

1807
00:56:04,928 --> 00:56:07,664
And each of those levels, that has to

1808
00:56:07,664 --> 00:56:08,198
come up through

1809
00:56:08,198 --> 00:56:09,265
leadership for us to ultimately

1810
00:56:09,265 --> 00:56:09,866
say yes.

1811
00:56:09,866 --> 00:56:12,402
So at least we know kind of what is going

1812
00:56:12,402 --> 00:56:13,169
on in the department.

1813
00:56:13,636 --> 00:56:15,205
And other ways of communication are

1814
00:56:15,205 --> 00:56:16,706
through the divisions and

1815
00:56:16,706 --> 00:56:18,274
through to the chairs that

1816
00:56:18,274 --> 00:56:18,508
way.

1817
00:56:18,908 --> 00:56:20,243
And then I think the other part is to

1818
00:56:20,243 --> 00:56:21,711
have an institutional

1819
00:56:21,711 --> 00:56:23,747
infrastructure in place to

1820
00:56:23,747 --> 00:56:27,450
be able to capitalize on ideas quickly.

1821
00:56:28,251 --> 00:56:31,521
So having some sort of intellectual

1822
00:56:31,521 --> 00:56:33,089
property, Mayo Clinic

1823
00:56:33,089 --> 00:56:35,358
Ventures, things that are hopefully

1824
00:56:35,392 --> 00:56:38,128
nimble and able to respond to your ideas

1825
00:56:38,128 --> 00:56:39,829
and be able to either

1826
00:56:39,829 --> 00:56:41,598
resource them or at least

1827
00:56:41,831 --> 00:56:44,134
kind of give you the path forward that

1828
00:56:44,134 --> 00:56:45,668
you may not be interested in yourself.

1829
00:56:46,136 --> 00:56:49,072
How about-- and this is maybe the tougher

1830
00:56:49,072 --> 00:56:51,508
question-- how about the opposite?

1831
00:56:51,808 --> 00:56:53,610
How about people that you have come in

1832
00:56:53,610 --> 00:56:55,145
who market themselves

1833
00:56:55,145 --> 00:56:57,046
from the start as, let's

1834
00:56:57,080 --> 00:56:58,248
say, clinician scientists?

1835
00:56:59,082 --> 00:57:00,850
And at the end of the day, after five

1836
00:57:00,850 --> 00:57:01,918
years, you find out that

1837
00:57:01,918 --> 00:57:02,852
what they're great is, is

1838
00:57:02,852 --> 00:57:04,220
they're great at coming in and marketing

1839
00:57:04,220 --> 00:57:05,989
themselves as clinician scientists.

1840
00:57:06,523 --> 00:57:08,458
They can tell you a great personal story.

1841
00:57:09,292 --> 00:57:10,994
And every time, it's a personal story

1842
00:57:10,994 --> 00:57:11,761
that's inspirational.

1843
00:57:12,362 --> 00:57:15,832
But at the end of the day, they're maybe

1844
00:57:15,832 --> 00:57:17,734
taking care of a lot fewer patients.

1845
00:57:18,468 --> 00:57:22,605
And they really aren't into the substance

1846
00:57:22,605 --> 00:57:23,907
of the thing that the

1847
00:57:23,907 --> 00:57:25,041
science that's related

1848
00:57:25,108 --> 00:57:25,909
to the clinical care

1849
00:57:25,909 --> 00:57:26,943
they deliver is about.

1850
00:57:26,943 --> 00:57:28,545
What they're into is their own story.

1851
00:57:28,912 --> 00:57:30,447
But they built themselves up this way.

1852
00:57:31,281 --> 00:57:31,815
And that's their

1853
00:57:31,815 --> 00:57:33,183
identity within the department.

1854
00:57:33,783 --> 00:57:35,585
But they can still be very good doctors.

1855
00:57:35,785 --> 00:57:37,720
But that's the narrative that's

1856
00:57:37,720 --> 00:57:38,621
associated with them.

1857
00:57:39,389 --> 00:57:41,891
The right term shouldn't be like a

1858
00:57:41,891 --> 00:57:43,860
graceful declination of

1859
00:57:43,860 --> 00:57:45,061
the degree to which they fit

1860
00:57:45,061 --> 00:57:45,662
that label.

1861
00:57:45,962 --> 00:57:47,730
But is there a way to make it so that--

1862
00:57:48,031 --> 00:57:48,832
in particular, I think

1863
00:57:48,832 --> 00:57:50,567
institutions may identify

1864
00:57:51,100 --> 00:57:52,635
folks who come up through residency.

1865
00:57:53,503 --> 00:57:54,404
Out of residency, they're

1866
00:57:54,404 --> 00:57:56,606
supposed to be the next big thing.

1867
00:57:56,606 --> 00:57:57,106
But what they're good

1868
00:57:57,106 --> 00:57:58,808
at is a sales pitch.

1869
00:57:59,309 --> 00:58:01,277
But at the end of the day, they're not

1870
00:58:01,277 --> 00:58:02,445
staying up late at night

1871
00:58:02,445 --> 00:58:04,848
thinking about the oddity

1872
00:58:04,848 --> 00:58:07,817
in that patient they saw that day and how

1873
00:58:07,817 --> 00:58:08,718
that may be related

1874
00:58:08,718 --> 00:58:10,386
to-- like you said, to

1875
00:58:10,386 --> 00:58:13,823
some other disease that had some

1876
00:58:13,823 --> 00:58:15,058
similarities and maybe a

1877
00:58:15,058 --> 00:58:16,259
similar approach could be taken.

1878
00:58:16,559 --> 00:58:18,862
What they're doing is they're invested in

1879
00:58:18,862 --> 00:58:19,362
something that has

1880
00:58:19,362 --> 00:58:20,029
nothing to do with their

1881
00:58:20,096 --> 00:58:20,530
practice.

1882
00:58:21,097 --> 00:58:21,965
They built themselves up

1883
00:58:21,965 --> 00:58:23,466
with a great personal story.

1884
00:58:23,466 --> 00:58:24,734
And I think that there's a lot of that.

1885
00:58:24,734 --> 00:58:26,903
And I think as clinician scientists, this

1886
00:58:26,903 --> 00:58:30,139
is always something that they essentially

1887
00:58:30,206 --> 00:58:31,241
train people to do now.

1888
00:58:31,774 --> 00:58:34,377
But there should also be room-- while you

1889
00:58:34,377 --> 00:58:35,311
want to empower some

1890
00:58:35,311 --> 00:58:36,012
people that aren't doing

1891
00:58:36,012 --> 00:58:38,681
as much, are there mechanisms to sort of

1892
00:58:38,681 --> 00:58:39,716
bring things down for the

1893
00:58:39,716 --> 00:58:41,284
folks that are commanding

1894
00:58:41,284 --> 00:58:43,286
maybe a lot of resources, but not

1895
00:58:43,286 --> 00:58:45,555
necessarily having that

1896
00:58:45,555 --> 00:58:47,056
commitment to the dual role that

1897
00:58:47,690 --> 00:58:48,925
was sort of the plan when they started?

1898
00:58:49,626 --> 00:58:51,561
I would have to say, just to cut in here,

1899
00:58:51,561 --> 00:58:52,228
that fortunately we

1900
00:58:52,228 --> 00:58:52,996
don't have that problem

1901
00:58:52,996 --> 00:58:53,796
in neurology.

1902
00:58:53,796 --> 00:58:55,098
I don't know what Kai's talking about.

1903
00:58:55,565 --> 00:58:56,065
He must have--

1904
00:58:56,065 --> 00:58:56,566
I don't know how any

1905
00:58:56,566 --> 00:58:57,367
particular people are lying.

1906
00:58:57,367 --> 00:58:57,767
He must have

1907
00:58:57,767 --> 00:58:59,269
something that he knows about.

1908
00:58:59,269 --> 00:59:00,803
I'm not totally agree with that.

1909
00:59:01,070 --> 00:59:01,871
Nothing's subtle here.

1910
00:59:02,071 --> 00:59:02,772
Nothing's subtle here.

1911
00:59:02,772 --> 00:59:03,506
We'll cut that part.

1912
00:59:03,740 --> 00:59:04,741
We don't have to cut that part.

1913
00:59:04,741 --> 00:59:05,675
I really think that let's

1914
00:59:05,675 --> 00:59:06,843
talk about another department.

1915
00:59:07,310 --> 00:59:07,510
Yes.

1916
00:59:07,777 --> 00:59:09,612
But I'd be happy to weigh in on that one.

1917
00:59:10,213 --> 00:59:12,348
What I will say to that is I think that

1918
00:59:12,348 --> 00:59:13,349
everybody is different.

1919
00:59:14,117 --> 00:59:16,419
And everybody brings

1920
00:59:16,419 --> 00:59:17,387
something to the table.

1921
00:59:17,787 --> 00:59:21,291
I think individuals who speak to speak,

1922
00:59:21,291 --> 00:59:22,358
if you want to go that

1923
00:59:22,358 --> 00:59:24,160
way, at the end of the

1924
00:59:24,160 --> 00:59:27,530
day, it becomes clear at the end of the

1925
00:59:27,530 --> 00:59:28,364
day what's happening.

1926
00:59:28,631 --> 00:59:30,600
And so whether that individual goes back

1927
00:59:30,600 --> 00:59:32,902
to seeing patients or

1928
00:59:32,902 --> 00:59:35,672
whatever, generally you'll

1929
00:59:35,672 --> 00:59:37,440
find that people over the years

1930
00:59:37,440 --> 00:59:39,475
ultimately figure out where

1931
00:59:39,475 --> 00:59:41,477
they best lie, where they're

1932
00:59:41,477 --> 00:59:41,978
best fit.

1933
00:59:42,345 --> 00:59:44,047
There are a lot of people that started

1934
00:59:44,047 --> 00:59:44,948
off thinking, I'm going

1935
00:59:44,948 --> 00:59:45,882
to be a clinician scientist

1936
00:59:46,182 --> 00:59:48,017
and now they're running trials and they

1937
00:59:48,017 --> 00:59:49,018
love running trials and

1938
00:59:49,018 --> 00:59:49,719
they're very happy they

1939
00:59:49,719 --> 00:59:51,521
don't have to worry about the stress of

1940
00:59:51,521 --> 00:59:52,522
getting an NIH grant.

1941
00:59:53,022 --> 00:59:55,291
There are people that I would consider

1942
00:59:55,291 --> 00:59:56,392
really, really brilliant

1943
00:59:56,392 --> 00:59:58,094
scientists who cannot get

1944
00:59:58,227 --> 00:59:58,895
NIH funding.

1945
00:59:59,128 --> 00:59:59,329
Why?

1946
00:59:59,729 --> 01:00:01,264
Because they're out of the box thinkers.

1947
01:00:01,597 --> 01:00:04,400
They want to go and do it and accelerate

1948
01:00:04,400 --> 01:00:06,603
things and let's just go do this.

1949
01:00:07,203 --> 01:00:09,906
They're probably right, but National

1950
01:00:09,906 --> 01:00:10,740
Institute of Health is

1951
01:00:10,740 --> 01:00:11,808
not interested in that.

1952
01:00:12,608 --> 01:00:14,344
I think it can be difficult and I think

1953
01:00:14,344 --> 01:00:15,912
one of the jobs I think

1954
01:00:15,912 --> 01:00:16,746
of leadership is trying

1955
01:00:16,746 --> 01:00:19,549
to help people figure out where they best

1956
01:00:19,549 --> 01:00:21,284
lie, where are their talents.

1957
01:00:21,651 --> 01:00:23,119
If they're employed

1958
01:00:23,119 --> 01:00:24,887
at Mayo, they're good.

1959
01:00:26,623 --> 01:00:27,290
They're going to be excellent.

1960
01:00:27,590 --> 01:00:27,991
I think that.

1961
01:00:28,291 --> 01:00:28,725
I mean, yeah.

1962
01:00:29,258 --> 01:00:30,626
I think we try to do that.

1963
01:00:31,194 --> 01:00:32,895
From a research perspective, Nathan

1964
01:00:32,895 --> 01:00:34,130
spends a lot of his time

1965
01:00:34,130 --> 01:00:35,732
helping people navigate

1966
01:00:36,499 --> 01:00:39,302
research at the institutional level, at

1967
01:00:39,302 --> 01:00:40,370
the national level,

1968
01:00:41,371 --> 01:00:42,872
from a space perspective,

1969
01:00:43,206 --> 01:00:44,641
from an advice perspective.

1970
01:00:45,575 --> 01:00:46,542
You try to help people

1971
01:00:46,542 --> 01:00:48,411
with respect to that.

1972
01:00:49,212 --> 01:00:52,015
Also helping and developing a structured

1973
01:00:52,015 --> 01:00:52,949
mentorship program, which

1974
01:00:52,949 --> 01:00:55,385
we've done, so that the younger

1975
01:00:55,385 --> 01:00:56,786
investigators who can get

1976
01:00:56,786 --> 01:00:58,588
lost, it's all well and good.

1977
01:00:58,588 --> 01:00:59,489
You finish a residency

1978
01:00:59,489 --> 01:01:01,424
and you think, we know this.

1979
01:01:01,424 --> 01:01:02,592
You interview people for

1980
01:01:02,592 --> 01:01:04,060
residency and they're talking.

1981
01:01:04,761 --> 01:01:07,330
I'm going to work 80-20.

1982
01:01:07,830 --> 01:01:09,332
I'm going to get two grants.

1983
01:01:09,532 --> 01:01:12,835
I'm going to get a K. There is a sudden

1984
01:01:12,835 --> 01:01:15,271
reality of it's actually

1985
01:01:15,271 --> 01:01:16,739
very hard to get an NIH

1986
01:01:16,739 --> 01:01:17,140
grant.

1987
01:01:18,908 --> 01:01:20,410
At the end of the day, some people then

1988
01:01:20,410 --> 01:01:22,745
realize that actually I'm happy.

1989
01:01:22,745 --> 01:01:25,014
I'm not going to spend six months of my

1990
01:01:25,014 --> 01:01:26,182
life not seeing my

1991
01:01:26,182 --> 01:01:27,984
family writing a grant where

1992
01:01:28,284 --> 01:01:32,455
I suddenly get 18%, which is better than

1993
01:01:32,455 --> 01:01:35,525
82% of the other

1994
01:01:35,525 --> 01:01:36,559
people, but I'm not going

1995
01:01:36,559 --> 01:01:37,060
to get funded.

1996
01:01:37,260 --> 01:01:38,361
I mean, that can be hard.

1997
01:01:39,162 --> 01:01:43,199
I just think that if an individual is in

1998
01:01:43,199 --> 01:01:43,800
that scenario,

1999
01:01:44,067 --> 01:01:47,103
hopefully they need to get some

2000
01:01:47,103 --> 01:01:49,238
good advice to try and help them find the

2001
01:01:49,238 --> 01:01:52,308
best place for them for their careers.

2002
01:01:53,109 --> 01:01:55,311
Why was it a meeting and ran into

2003
01:01:55,311 --> 01:01:57,246
somebody, let's say very

2004
01:01:57,246 --> 01:01:59,148
high, I don't want to say

2005
01:01:59,148 --> 01:02:00,850
who they are, very high up in the NIH

2006
01:02:00,850 --> 01:02:02,151
that I've known for many

2007
01:02:02,151 --> 01:02:03,419
years, who basically told

2008
01:02:03,419 --> 01:02:06,789
me in this environment with things as

2009
01:02:06,789 --> 01:02:08,357
they are, you have 5%

2010
01:02:08,691 --> 01:02:09,726
or less chance of getting

2011
01:02:09,726 --> 01:02:10,393
a grant funded.

2012
01:02:11,060 --> 01:02:12,261
Maybe you should wait a little while

2013
01:02:12,261 --> 01:02:13,062
before you kind of

2014
01:02:13,062 --> 01:02:14,097
reenter the grant game.

2015
01:02:14,430 --> 01:02:15,531
That's the person who

2016
01:02:15,531 --> 01:02:17,500
their job has been to.

2017
01:02:18,201 --> 01:02:19,469
Previously, they were always telling me,

2018
01:02:19,469 --> 01:02:19,969
"Oh yeah, you should

2019
01:02:19,969 --> 01:02:20,670
submit your next thing.

2020
01:02:20,670 --> 01:02:21,671
You should submit your next thing."

2021
01:02:22,004 --> 01:02:23,740
Now they're saying, "Well, I don't know

2022
01:02:23,740 --> 01:02:24,607
how these things are

2023
01:02:24,607 --> 01:02:25,875
going to recover or if

2024
01:02:25,875 --> 01:02:26,742
they're going to recover."

2025
01:02:27,143 --> 01:02:29,779
I'm not necessarily asking for an opinion

2026
01:02:29,779 --> 01:02:30,847
about that, but for

2027
01:02:30,847 --> 01:02:32,348
you guys, what's the plan

2028
01:02:32,448 --> 01:02:34,851
if this model that's existed in the

2029
01:02:34,851 --> 01:02:36,686
post-World War II era of government

2030
01:02:36,686 --> 01:02:38,888
funding through meritorious

2031
01:02:38,888 --> 01:02:41,457
and you could argue what the merit is,

2032
01:02:41,457 --> 01:02:42,725
but if this environment

2033
01:02:42,725 --> 01:02:43,826
doesn't exist anymore,

2034
01:02:45,328 --> 01:02:48,464
how are institutions that do biomedical

2035
01:02:48,464 --> 01:02:49,899
research, how are their

2036
01:02:49,899 --> 01:02:51,100
scientists going to be able

2037
01:02:51,134 --> 01:02:51,768
to keep functioning?

2038
01:02:52,201 --> 01:02:53,002
How is innovation

2039
01:02:53,002 --> 01:02:54,003
going to keep happening?

2040
01:02:54,003 --> 01:02:55,471
Is it going to have to all

2041
01:02:55,471 --> 01:02:56,873
move over to the industry side?

2042
01:02:56,873 --> 01:02:58,841
If so, should medical institutions

2043
01:02:58,841 --> 01:02:59,809
partner with industry?

2044
01:03:00,510 --> 01:03:03,312
Usually for very good ethical reasons,

2045
01:03:03,312 --> 01:03:04,247
there's been a line there.

2046
01:03:04,547 --> 01:03:04,947
What happens?

2047
01:03:05,281 --> 01:03:08,251
Yeah, for me, a couple of things.

2048
01:03:08,484 --> 01:03:11,154
I think first of all, if people are doing

2049
01:03:11,154 --> 01:03:13,890
good work, then they should be supported.

2050
01:03:16,259 --> 01:03:18,761
They should underestimate the quality of

2051
01:03:18,761 --> 01:03:19,629
the work that can come

2052
01:03:19,629 --> 01:03:21,464
from low-level funding.

2053
01:03:22,031 --> 01:03:23,699
In fact, I would say that a lot of the

2054
01:03:23,699 --> 01:03:25,635
best discoveries and

2055
01:03:25,635 --> 01:03:28,070
work at Mayo Clinic has come

2056
01:03:28,070 --> 01:03:31,207
from not huge, hugely funded entities.

2057
01:03:32,441 --> 01:03:34,143
Sometimes the funding comes after the

2058
01:03:34,143 --> 01:03:35,178
major discovery is made.

2059
01:03:36,012 --> 01:03:38,748
I do think that, and I think Mayo has

2060
01:03:38,748 --> 01:03:39,415
done a good job of

2061
01:03:39,415 --> 01:03:41,117
this, is diversification.

2062
01:03:41,884 --> 01:03:44,787
Greg Gores, the last chair of head of

2063
01:03:44,787 --> 01:03:46,689
research at Mayo, was very

2064
01:03:46,689 --> 01:03:49,225
good and had foresight and

2065
01:03:49,225 --> 01:03:50,593
diversified the portfolio.

2066
01:03:51,027 --> 01:03:53,262
But yes, I think at the current time, it

2067
01:03:53,262 --> 01:03:54,630
would appear that NIH

2068
01:03:54,630 --> 01:03:55,831
funding is going to drop.

2069
01:03:56,265 --> 01:03:59,902
We don't know by how much, but I still

2070
01:03:59,902 --> 01:04:01,103
think that good research

2071
01:04:01,103 --> 01:04:03,072
will continue to exist,

2072
01:04:03,773 --> 01:04:05,074
and the people that are doing it will

2073
01:04:05,074 --> 01:04:06,209
continue to get support.

2074
01:04:06,542 --> 01:04:07,243
But I agree.

2075
01:04:07,643 --> 01:04:09,045
We will see through potentially different

2076
01:04:09,045 --> 01:04:11,647
mechanisms, and those mechanisms will be

2077
01:04:13,082 --> 01:04:14,984
people that really believe in the disease

2078
01:04:14,984 --> 01:04:16,919
and want to accelerate it and are willing

2079
01:04:16,919 --> 01:04:19,121
to provide benefactor

2080
01:04:19,121 --> 01:04:21,224
funding through development, etc.

2081
01:04:22,225 --> 01:04:25,127
Closer interaction with industry partners

2082
01:04:25,127 --> 01:04:30,299
and visionary startups and companies that

2083
01:04:30,299 --> 01:04:31,567
see the vision.

2084
01:04:32,802 --> 01:04:34,470
For example, the work that you're doing,

2085
01:04:34,737 --> 01:04:36,706
I don't think it takes a rocket scientist

2086
01:04:36,906 --> 01:04:39,742
to know that having artificial

2087
01:04:39,742 --> 01:04:43,312
intelligence assess and develop

2088
01:04:43,312 --> 01:04:44,547
algorithmic approaches

2089
01:04:44,547 --> 01:04:48,784
to predicting what electrical data coming

2090
01:04:48,784 --> 01:04:50,019
out from the brain is

2091
01:04:50,019 --> 01:04:50,786
going to have an impact.

2092
01:04:51,020 --> 01:04:53,756
We know that this is going to be big.

2093
01:04:55,057 --> 01:04:57,994
Maybe the way to do this is different.

2094
01:04:58,294 --> 01:05:02,365
It's to say to a company that there is a

2095
01:05:02,365 --> 01:05:04,934
huge future in this, and

2096
01:05:04,934 --> 01:05:06,569
maybe you need to decide

2097
01:05:06,569 --> 01:05:08,738
to put some of the dollars that you have

2098
01:05:08,738 --> 01:05:12,308
into working with Mayo

2099
01:05:12,308 --> 01:05:14,710
or working with other

2100
01:05:14,710 --> 01:05:18,214
institutions to accelerate the science so

2101
01:05:18,214 --> 01:05:18,981
that at the end of

2102
01:05:18,981 --> 01:05:19,682
the day, because at the

2103
01:05:19,682 --> 01:05:24,520
end of the day, the drugs or the devices

2104
01:05:24,520 --> 01:05:25,087
that are going to

2105
01:05:25,087 --> 01:05:26,522
impact patients are not going

2106
01:05:26,522 --> 01:05:29,725
to come from you guys and

2107
01:05:29,725 --> 01:05:30,927
the Mayo Clinic on its own.

2108
01:05:31,394 --> 01:05:33,829
It has to have that

2109
01:05:33,829 --> 01:05:35,231
commercial relationship.

2110
01:05:35,264 --> 01:05:36,732
I think that the way we

2111
01:05:36,732 --> 01:05:38,301
do science is changing.

2112
01:05:40,736 --> 01:05:41,504
I don't know what you think.

2113
01:05:42,271 --> 01:05:42,772
I think

2114
01:05:42,772 --> 01:05:44,840
diversification is obviously the key.

2115
01:05:45,675 --> 01:05:49,312
Things are just very uncertain right now.

2116
01:05:50,479 --> 01:05:54,050
I think fortunately, it looks like in

2117
01:05:54,050 --> 01:05:55,451
2026, the funding for

2118
01:05:55,451 --> 01:05:57,286
NIH is going to be stable,

2119
01:05:58,120 --> 01:05:59,956
maybe even a little bit improved, which

2120
01:05:59,956 --> 01:06:01,057
is obviously a much

2121
01:06:01,057 --> 01:06:02,224
different scenario than we

2122
01:06:02,224 --> 01:06:03,526
were talking about a year ago.

2123
01:06:05,127 --> 01:06:07,396
But I think it's really been a wake-up

2124
01:06:07,396 --> 01:06:08,764
call for institutions on

2125
01:06:08,764 --> 01:06:11,467
how to manage potentially

2126
01:06:11,467 --> 01:06:14,503
a drastically cut NIH system.

2127
01:06:15,271 --> 01:06:16,439
It's not just the dollars

2128
01:06:16,439 --> 01:06:17,606
that actually do the research.

2129
01:06:19,108 --> 01:06:21,310
From the institutional standpoint, it

2130
01:06:21,310 --> 01:06:22,244
actually is more

2131
01:06:22,244 --> 01:06:24,880
frightening the indirect support of

2132
01:06:24,880 --> 01:06:27,450
the F&A fees that come with the NIH

2133
01:06:27,450 --> 01:06:29,819
dollars that basically fund

2134
01:06:29,819 --> 01:06:31,187
most of the infrastructure

2135
01:06:31,287 --> 01:06:33,122
that we have to do the science here.

2136
01:06:33,889 --> 01:06:36,826
We need to have regulatory oversight of

2137
01:06:36,826 --> 01:06:38,761
what's done both at the

2138
01:06:38,761 --> 01:06:40,863
patient level, the clinical

2139
01:06:41,163 --> 01:06:43,833
level, device level, giving us

2140
01:06:43,833 --> 01:06:45,034
infrastructure to be able to

2141
01:06:45,034 --> 01:06:46,335
move things through the FDA

2142
01:06:46,335 --> 01:06:46,769
correctly.

2143
01:06:47,770 --> 01:06:51,107
I mean, 40% of the indirect dollars that

2144
01:06:51,107 --> 01:06:52,041
come into Mayo Clinic

2145
01:06:52,041 --> 01:06:53,642
actually end up paying to

2146
01:06:53,642 --> 01:06:55,444
keep the lights on, literally, the

2147
01:06:55,444 --> 01:06:57,780
buildings and the infrastructure there.

2148
01:06:59,382 --> 01:07:01,050
Obviously, those dollars have to come

2149
01:07:01,050 --> 01:07:02,551
from somewhere to keep the lights on.

2150
01:07:03,219 --> 01:07:05,821
I think Mayo's fortunately been in a very

2151
01:07:05,821 --> 01:07:07,023
good position as being

2152
01:07:07,023 --> 01:07:08,491
a very strong clinical

2153
01:07:09,225 --> 01:07:11,127
practice to be able to fund

2154
01:07:11,127 --> 01:07:13,796
other aspects of our mission.

2155
01:07:14,330 --> 01:07:15,865
I think other institutions are going to

2156
01:07:15,865 --> 01:07:16,766
be in a much more

2157
01:07:16,766 --> 01:07:18,267
difficult place because they're

2158
01:07:18,267 --> 01:07:19,869
much more reliant on those dollars.

2159
01:07:20,603 --> 01:07:22,104
Something I'd really like to ask you guys

2160
01:07:22,104 --> 01:07:23,739
about is you both

2161
01:07:23,739 --> 01:07:26,509
wear at least three hats

2162
01:07:26,709 --> 01:07:28,644
so professionally, and then of course you

2163
01:07:28,644 --> 01:07:30,112
have your outside

2164
01:07:30,112 --> 01:07:31,380
lives as well, but you're

2165
01:07:31,514 --> 01:07:34,183
functioning as clinicians, functioning as

2166
01:07:34,183 --> 01:07:35,518
scientists, and also

2167
01:07:35,518 --> 01:07:36,552
functioning as leaders.

2168
01:07:37,319 --> 01:07:41,357
How do you take the things that made you

2169
01:07:41,357 --> 01:07:43,826
good as scientists,

2170
01:07:44,293 --> 01:07:45,194
so your own initiative?

2171
01:07:45,628 --> 01:07:48,130
I think for all of us, we are at least in

2172
01:07:48,130 --> 01:07:49,565
part fueled by our own egos.

2173
01:07:49,765 --> 01:07:50,399
I certainly am.

2174
01:07:50,766 --> 01:07:51,534
I think that's normal.

2175
01:07:52,001 --> 01:07:54,136
How do you put some of that to the side

2176
01:07:54,136 --> 01:07:55,671
in order to function as a

2177
01:07:55,671 --> 01:07:56,705
leader and try to promote

2178
01:07:57,540 --> 01:07:58,240
beyond yourselves?

2179
01:07:58,240 --> 01:07:59,508
Do you find that difficult?

2180
01:07:59,542 --> 01:08:02,044
Maybe some people are natural at that,

2181
01:08:02,044 --> 01:08:03,612
but are you guys natural at that?

2182
01:08:04,046 --> 01:08:08,384
What's the thought process behind the

2183
01:08:08,384 --> 01:08:09,085
things that have always

2184
01:08:09,085 --> 01:08:10,686
been your sphere of personal

2185
01:08:10,686 --> 01:08:13,189
development and the intellectual

2186
01:08:13,189 --> 01:08:15,057
contributions that you make as an

2187
01:08:15,057 --> 01:08:17,359
individual or has a transition

2188
01:08:17,359 --> 01:08:19,595
or just add something different on as you

2189
01:08:19,595 --> 01:08:23,866
now are trying to really fuel a whole set

2190
01:08:23,899 --> 01:08:27,002
of individuals and enable them to pursue

2191
01:08:27,002 --> 01:08:29,405
the things that they feel intellectually

2192
01:08:29,605 --> 01:08:31,474
and personally are important for them to

2193
01:08:31,474 --> 01:08:33,409
do, and much of your

2194
01:08:33,409 --> 01:08:34,710
role as leaders must be to

2195
01:08:35,044 --> 01:08:35,945
help make that happen.

2196
01:08:36,579 --> 01:08:38,380
Where does that trade off lie?

2197
01:08:39,548 --> 01:08:40,850
For most people, they can't turn the

2198
01:08:40,850 --> 01:08:42,218
scientist's button off in their head.

2199
01:08:43,085 --> 01:08:45,221
You come home and for Dora and I, this is

2200
01:08:45,221 --> 01:08:46,822
like a conversation.

2201
01:08:47,523 --> 01:08:48,924
I just thought of this idea.

2202
01:08:48,924 --> 01:08:50,025
It just doesn't go off.

2203
01:08:50,559 --> 01:08:52,261
For you guys, you really now have to

2204
01:08:52,261 --> 01:08:54,530
adopt this role where you

2205
01:08:54,530 --> 01:08:56,732
are fueling the curiosity

2206
01:08:56,966 --> 01:08:57,500
of others.

2207
01:08:58,067 --> 01:08:58,567
How does that work?

2208
01:09:01,203 --> 01:09:03,706
I suppose for me, the leadership roles

2209
01:09:03,706 --> 01:09:04,840
that I've really had

2210
01:09:04,840 --> 01:09:07,843
before taking on the chair

2211
01:09:07,843 --> 01:09:10,012
role were really more laboratory-based.

2212
01:09:10,279 --> 01:09:11,347
They were more around science.

2213
01:09:11,914 --> 01:09:13,549
I don't know if I would

2214
01:09:13,549 --> 01:09:14,950
necessarily say leadership.

2215
01:09:15,584 --> 01:09:17,186
We were a team of people who were

2216
01:09:17,186 --> 01:09:19,488
passionate around science

2217
01:09:19,488 --> 01:09:22,691
and around moving a new feel

2218
01:09:22,691 --> 01:09:23,225
for it.

2219
01:09:23,726 --> 01:09:24,994
I really enjoyed that.

2220
01:09:26,629 --> 01:09:29,131
My favorite part of being a fellow and a

2221
01:09:29,131 --> 01:09:30,166
young consultant was the

2222
01:09:30,166 --> 01:09:31,467
opportunity to get into

2223
01:09:31,467 --> 01:09:35,371
the weeds of research and really take a

2224
01:09:35,371 --> 01:09:36,539
concept and move it forward.

2225
01:09:37,206 --> 01:09:38,974
I think eventually you get to a point

2226
01:09:38,974 --> 01:09:40,943
where you've basically

2227
01:09:40,943 --> 01:09:44,246
mentored people that essentially

2228
01:09:44,346 --> 01:09:47,383
are perfectly capable of doing what you

2229
01:09:47,383 --> 01:09:48,684
had done and probably

2230
01:09:48,684 --> 01:09:49,585
are doing it better.

2231
01:09:51,020 --> 01:09:53,222
I think novel technologies come in and

2232
01:09:53,222 --> 01:09:54,890
then allow quite a

2233
01:09:54,890 --> 01:09:57,359
dramatic acceleration in the

2234
01:09:57,359 --> 01:09:58,627
opportunities to discover.

2235
01:09:59,361 --> 01:10:01,130
For example, some of the things we were

2236
01:10:01,130 --> 01:10:02,798
talking about earlier, we

2237
01:10:02,798 --> 01:10:04,800
now have opportunities to

2238
01:10:05,434 --> 01:10:08,103
use phage display where you can

2239
01:10:08,103 --> 01:10:10,506
essentially screen a serum

2240
01:10:10,506 --> 01:10:14,210
sample very, very quickly for

2241
01:10:15,644 --> 01:10:17,479
the ability for that antibody to target

2242
01:10:17,479 --> 01:10:19,081
any protein in the

2243
01:10:19,081 --> 01:10:21,383
entire human proteome using

2244
01:10:21,383 --> 01:10:23,886
millions of phages that have little

2245
01:10:23,886 --> 01:10:25,454
pieces of human DNA in

2246
01:10:25,454 --> 01:10:28,190
them that are expressing the

2247
01:10:28,524 --> 01:10:29,425
little pieces of the

2248
01:10:29,425 --> 01:10:30,559
entire human proteome.

2249
01:10:31,493 --> 01:10:36,332
We've used that to discover an antibody

2250
01:10:36,332 --> 01:10:38,601
biomarker in collaboration

2251
01:10:38,601 --> 01:10:40,836
with UCSF, but that was actually

2252
01:10:40,836 --> 01:10:43,672
led by Div Dubey who then took that

2253
01:10:43,672 --> 01:10:46,809
technology from UCSF and the

2254
01:10:46,809 --> 01:10:49,011
Zuckerberg Biohub and brought

2255
01:10:49,011 --> 01:10:49,478
it to mail.

2256
01:10:50,012 --> 01:10:53,315
Now you're discovering using a mechanism,

2257
01:10:53,315 --> 01:10:54,183
a methodology that's

2258
01:10:54,183 --> 01:10:55,384
been brought in by somebody

2259
01:10:55,784 --> 01:10:57,119
who was a fellow and is now

2260
01:10:57,119 --> 01:10:58,520
running that program themselves.

2261
01:10:59,588 --> 01:11:00,990
The same happens to a lot of other

2262
01:11:00,990 --> 01:11:02,424
technologies that come into the lab.

2263
01:11:03,025 --> 01:11:05,794
At some point, you sit back and say, "All

2264
01:11:05,794 --> 01:11:06,729
of this discovery is

2265
01:11:06,729 --> 01:11:08,364
now being done by other

2266
01:11:08,364 --> 01:11:08,697
people.

2267
01:11:09,198 --> 01:11:10,666
The program is vibrant."

2268
01:11:11,867 --> 01:11:14,670
Yes, at one point, there was Vanda and

2269
01:11:14,670 --> 01:11:16,505
myself, and now there's

2270
01:11:16,505 --> 01:11:18,340
Vanda and myself and loads

2271
01:11:18,340 --> 01:11:19,008
of other people.

2272
01:11:19,642 --> 01:11:20,709
The program is robust

2273
01:11:20,709 --> 01:11:21,710
and that's what I love.

2274
01:11:22,144 --> 01:11:24,780
I'm very happy to step back and just see

2275
01:11:24,780 --> 01:11:26,181
the vibrant

2276
01:11:26,181 --> 01:11:28,751
productivity of individuals who at

2277
01:11:28,851 --> 01:11:29,752
one point were fellows.

2278
01:11:30,252 --> 01:11:30,819
They're doing great.

2279
01:11:32,121 --> 01:11:34,056
So then the question is, how do you live

2280
01:11:34,056 --> 01:11:35,057
with the fact that it's

2281
01:11:35,057 --> 01:11:37,459
not your baby, it's not

2282
01:11:37,459 --> 01:11:38,427
your thing anymore?

2283
01:11:38,861 --> 01:11:40,129
I don't have a problem with that.

2284
01:11:41,030 --> 01:11:43,999
I still like to talk science.

2285
01:11:44,533 --> 01:11:47,202
I like the idea of having ideas, but I

2286
01:11:47,202 --> 01:11:48,003
have no problem with

2287
01:11:48,003 --> 01:11:49,505
having the idea, sharing it

2288
01:11:49,505 --> 01:11:50,172
with somebody and

2289
01:11:50,172 --> 01:11:51,173
letting them run with it.

2290
01:11:51,306 --> 01:11:55,110
Now in terms of switching from the

2291
01:11:55,110 --> 01:12:01,350
science to leadership, I don't know.

2292
01:12:01,950 --> 01:12:03,352
I tend to lead by just

2293
01:12:03,352 --> 01:12:05,354
group effort, team effort.

2294
01:12:06,388 --> 01:12:11,060
I think in our neurology department,

2295
01:12:11,060 --> 01:12:11,560
we've got really,

2296
01:12:11,560 --> 01:12:12,528
really brilliant people.

2297
01:12:13,228 --> 01:12:14,430
I don't know if

2298
01:12:14,430 --> 01:12:15,664
there's a lot of leadership.

2299
01:12:16,098 --> 01:12:17,900
I think that it's hard to

2300
01:12:17,900 --> 01:12:18,901
lead really brilliant people.

2301
01:12:19,802 --> 01:12:20,302
They don't really

2302
01:12:20,302 --> 01:12:21,403
need a lot of leadership.

2303
01:12:22,705 --> 01:12:24,573
What I prefer to do though is to think

2304
01:12:24,573 --> 01:12:26,275
about ways in which we

2305
01:12:26,275 --> 01:12:29,311
can really develop novel

2306
01:12:29,311 --> 01:12:32,981
programs around problems and identify

2307
01:12:32,981 --> 01:12:34,350
again, like we were

2308
01:12:34,350 --> 01:12:36,151
saying earlier, the pieces of

2309
01:12:36,151 --> 01:12:38,687
the clogs in that watch that are required

2310
01:12:38,687 --> 01:12:39,755
to make that happen

2311
01:12:39,755 --> 01:12:41,056
and move it forward and

2312
01:12:41,056 --> 01:12:41,824
accelerate it.

2313
01:12:42,257 --> 01:12:43,659
I take a lot of pleasure in that.

2314
01:12:44,727 --> 01:12:48,263
It does require stepping back and letting

2315
01:12:48,263 --> 01:12:49,164
essentially other

2316
01:12:49,164 --> 01:12:51,567
people do it, but that's

2317
01:12:51,567 --> 01:12:51,767
fine.

2318
01:12:52,167 --> 01:12:55,003
At some point, you do evolve.

2319
01:12:56,038 --> 01:12:56,839
It doesn't mean that I'm

2320
01:12:56,839 --> 01:12:57,773
not passionate about science.

2321
01:12:59,508 --> 01:13:00,843
I'm not the side PI

2322
01:13:00,843 --> 01:13:01,910
that's enrolling the patient.

2323
01:13:02,177 --> 01:13:03,545
Maybe I'm sitting on an advisory

2324
01:13:03,545 --> 01:13:04,446
committee for a drug

2325
01:13:04,446 --> 01:13:06,248
company and saying, "Maybe that's

2326
01:13:06,248 --> 01:13:07,483
the wrong design for the trial."

2327
01:13:08,484 --> 01:13:09,318
It's just a different

2328
01:13:09,318 --> 01:13:12,287
scene, but I still enjoy it.

2329
01:13:13,122 --> 01:13:13,422
I don't know.

2330
01:13:13,422 --> 01:13:13,856
What about you?

2331
01:13:14,523 --> 01:13:20,896
Yeah, I think for me, the things ... I

2332
01:13:20,896 --> 01:13:22,731
still have the science

2333
01:13:22,731 --> 01:13:25,701
brain that I need to ... it's

2334
01:13:25,701 --> 01:13:27,269
the itch that always needs scratching,

2335
01:13:28,670 --> 01:13:31,273
but I do that

2336
01:13:31,273 --> 01:13:35,010
compartmentalized in some ways from

2337
01:13:35,010 --> 01:13:36,311
a lot of the other stuff that I do.

2338
01:13:37,646 --> 01:13:39,548
It's compartmentalized many times during

2339
01:13:39,548 --> 01:13:41,417
the day, so it keeps coming back in.

2340
01:13:42,151 --> 01:13:44,987
I think really what I have always enjoyed

2341
01:13:44,987 --> 01:13:45,854
and I think what led

2342
01:13:45,854 --> 01:13:48,423
me into leadership is

2343
01:13:48,657 --> 01:13:51,193
finding synergies and win-wins.

2344
01:13:51,794 --> 01:13:53,662
I've always been a team player.

2345
01:13:53,662 --> 01:13:55,230
I love team sports.

2346
01:13:55,230 --> 01:13:59,501
I love the idea of that groups are better

2347
01:13:59,501 --> 01:14:01,236
than some of their individuals.

2348
01:14:02,137 --> 01:14:05,841
I think as I've been in this role and

2349
01:14:05,841 --> 01:14:06,408
I've been at this

2350
01:14:06,408 --> 01:14:08,310
institution long enough and I

2351
01:14:08,544 --> 01:14:12,748
know enough things that are going on that

2352
01:14:12,748 --> 01:14:14,583
I feel like I just

2353
01:14:14,583 --> 01:14:15,818
want to be able to share

2354
01:14:15,818 --> 01:14:18,120
that to accelerate other people's work,

2355
01:14:18,120 --> 01:14:20,689
like what office is

2356
01:14:20,689 --> 01:14:22,090
here, what person is there,

2357
01:14:22,090 --> 01:14:24,126
what lab is there, and try to bring

2358
01:14:24,126 --> 01:14:25,828
people to when they have

2359
01:14:25,828 --> 01:14:26,862
questions and they feel

2360
01:14:26,862 --> 01:14:29,465
like they're in a roadblock to get them

2361
01:14:29,465 --> 01:14:31,466
moving quicker and not

2362
01:14:31,466 --> 01:14:33,702
feel like they're lost in

2363
01:14:33,702 --> 01:14:36,238
a sea of bureaucracy.

2364
01:14:38,240 --> 01:14:39,141
Everything's at Mayo.

2365
01:14:39,675 --> 01:14:41,310
You just need to know how to get to it.

2366
01:14:41,310 --> 01:14:44,313
A lot of what I do is to try to do that.

2367
01:14:44,847 --> 01:14:51,086
But I also love the idea, I think as you

2368
01:14:51,086 --> 01:14:52,521
said, is coming up with

2369
01:14:52,521 --> 01:14:53,689
the idea in the direction

2370
01:14:53,689 --> 01:14:56,225
and say, "We need to go in this direction

2371
01:14:56,225 --> 01:14:57,726
from a research standpoint."

2372
01:14:59,228 --> 01:15:01,997
I may not know all of the methodologies

2373
01:15:01,997 --> 01:15:03,599
and all of the

2374
01:15:03,599 --> 01:15:05,234
rigorous science that needs to

2375
01:15:05,267 --> 01:15:09,605
get us there, but I know that you do and

2376
01:15:09,605 --> 01:15:11,707
I know that you do and

2377
01:15:11,707 --> 01:15:12,441
aren't we all excited

2378
01:15:12,541 --> 01:15:14,409
about this specific disease and to be

2379
01:15:14,409 --> 01:15:15,511
able to come up, say,

2380
01:15:15,511 --> 01:15:16,712
with treatments for ALS,

2381
01:15:17,179 --> 01:15:18,947
which is a horrible disease and we have

2382
01:15:18,947 --> 01:15:19,815
no great treatments

2383
01:15:19,815 --> 01:15:22,251
for, and get people excited

2384
01:15:22,351 --> 01:15:24,653
about trying to break through and come up

2385
01:15:24,653 --> 01:15:27,823
with new therapies for that and push them

2386
01:15:27,823 --> 01:15:30,592
all in the right direction and let them

2387
01:15:30,592 --> 01:15:32,561
flourish in the ideas that

2388
01:15:32,561 --> 01:15:34,263
they have, but always keep

2389
01:15:34,496 --> 01:15:38,200
bringing in the context and also what's

2390
01:15:38,200 --> 01:15:39,067
going on in the field

2391
01:15:39,067 --> 01:15:41,970
and being able to provide

2392
01:15:42,004 --> 01:15:44,139
more of a guidance and steering of the

2393
01:15:44,139 --> 01:15:46,308
ship rather than the

2394
01:15:46,308 --> 01:15:47,576
details on the ground.

2395
01:15:48,076 --> 01:15:49,711
I have things where I like to be, I have

2396
01:15:49,711 --> 01:15:50,412
control of all the

2397
01:15:50,412 --> 01:15:51,713
details, it's the little science

2398
01:15:51,713 --> 01:15:54,416
brain in me, but I also recognize that

2399
01:15:54,416 --> 01:15:55,450
there's some huge unmet

2400
01:15:55,450 --> 01:15:57,819
needs that I have skill set

2401
01:15:57,819 --> 01:15:59,288
to be able to try to move the field

2402
01:15:59,288 --> 01:16:00,556
forward even if I'm not the

2403
01:16:00,556 --> 01:16:02,224
one doing the basic science

2404
01:16:02,324 --> 01:16:02,624
myself.

2405
01:16:04,159 --> 01:16:06,228
And then you also are a

2406
01:16:06,228 --> 01:16:07,329
small business owner, right?

2407
01:16:07,329 --> 01:16:08,797
Can you tell us a little bit about that?

2408
01:16:09,498 --> 01:16:11,900
Yeah, it's small business owner is

2409
01:16:11,900 --> 01:16:13,135
probably a stretch for me

2410
01:16:13,135 --> 01:16:14,703
specifically, but my wife

2411
01:16:14,703 --> 01:16:18,140
is deeply involved in the coffee shops

2412
01:16:18,140 --> 01:16:20,108
that we have in town called Cafe Steam.

2413
01:16:20,876 --> 01:16:22,444
There's three owner groups.

2414
01:16:22,644 --> 01:16:23,178
Yeah, picture over here.

2415
01:16:23,478 --> 01:16:23,879
Yeah, absolutely.

2416
01:16:25,013 --> 01:16:28,016
We started that 11 years ago, put a lot

2417
01:16:28,016 --> 01:16:29,051
of elbow grease in at

2418
01:16:29,051 --> 01:16:30,385
the beginning of it.

2419
01:16:30,519 --> 01:16:33,155
It was successful because we have, again,

2420
01:16:33,155 --> 01:16:34,756
great people and

2421
01:16:34,756 --> 01:16:37,426
allowed them to kind of have

2422
01:16:37,426 --> 01:16:38,460
their vision flourish.

2423
01:16:39,328 --> 01:16:41,163
And I mostly just sat back and drank

2424
01:16:41,163 --> 01:16:43,966
coffee and commented on things.

2425
01:16:44,399 --> 01:16:45,901
And now we're opening our

2426
01:16:45,901 --> 01:16:47,669
fourth one up this spring.

2427
01:16:48,070 --> 01:16:49,004
Yeah, I'm excited about it.

2428
01:16:49,004 --> 01:16:50,472
It's right across from the hospital.

2429
01:16:50,472 --> 01:16:50,906
Yeah, absolutely.

2430
01:16:51,273 --> 01:16:52,808
But I mean, I think in the intellectual

2431
01:16:52,808 --> 01:16:55,177
world, coffee shops hold a special place.

2432
01:16:55,744 --> 01:16:58,180
The intellectual breakthroughs of the

2433
01:16:58,180 --> 01:16:58,747
late Enlightenment

2434
01:16:58,747 --> 01:17:01,450
period came from the idea of

2435
01:17:01,450 --> 01:17:02,050
salons and all this.

2436
01:17:02,050 --> 01:17:03,051
This was coffee houses.

2437
01:17:03,652 --> 01:17:04,486
Yeah, well, that's why we--

2438
01:17:04,486 --> 01:17:05,120
It wasn't bars, right?

2439
01:17:05,120 --> 01:17:09,992
It was-- and certainly for me, all of my

2440
01:17:09,992 --> 01:17:11,293
graduate work was in Seattle.

2441
01:17:11,994 --> 01:17:13,161
Sitting working in coffee

2442
01:17:13,161 --> 01:17:15,464
shops was where I did my best math.

2443
01:17:15,797 --> 01:17:17,299
We didn't feel like we had that in

2444
01:17:17,299 --> 01:17:18,600
Rochester when we moved here.

2445
01:17:18,600 --> 01:17:21,503
So this was the drive because just like

2446
01:17:21,503 --> 01:17:22,971
you, graduate school,

2447
01:17:22,971 --> 01:17:24,172
medical school, undergrad,

2448
01:17:24,406 --> 01:17:26,508
I spent hours and hours and hours in

2449
01:17:26,508 --> 01:17:27,442
coffee shops, either

2450
01:17:27,442 --> 01:17:30,345
reading by myself or arguing

2451
01:17:30,345 --> 01:17:31,713
with people about ideas.

2452
01:17:32,047 --> 01:17:32,547
I mean, it's just--

2453
01:17:32,881 --> 01:17:33,882
it's a place for that.

2454
01:17:33,882 --> 01:17:34,950
And there really wasn't that.

2455
01:17:34,950 --> 01:17:36,652
And I think that we do serve that

2456
01:17:36,652 --> 01:17:38,720
function, particularly in

2457
01:17:38,720 --> 01:17:40,389
the original coffee house

2458
01:17:40,389 --> 01:17:40,589
that's--

2459
01:17:40,589 --> 01:17:42,157
I spend a lot of time arguing with people

2460
01:17:42,157 --> 01:17:42,958
in their coffee shop.

2461
01:17:42,958 --> 01:17:43,325
Yeah, thank you.

2462
01:17:43,525 --> 01:17:43,925
Appreciate that.

2463
01:17:44,593 --> 01:17:44,659
Or what for.

2464
01:17:44,659 --> 01:17:45,594
You know, yell at my

2465
01:17:45,594 --> 01:17:46,728
children a little bit, whatever.

2466
01:17:47,295 --> 01:17:50,332
We really want to see the field of

2467
01:17:50,332 --> 01:17:53,268
neuromodulation grow and flourish.

2468
01:17:54,002 --> 01:17:55,170
And obviously, we're interviewing you

2469
01:17:55,170 --> 01:17:56,672
guys here from Rochester.

2470
01:17:57,072 --> 01:17:58,473
But it's sort of part

2471
01:17:58,473 --> 01:18:00,676
of a larger initiative.

2472
01:18:00,676 --> 01:18:02,244
This is going to be a-- this is going to

2473
01:18:02,244 --> 01:18:03,845
be a-- you know what I would love?

2474
01:18:03,845 --> 01:18:04,813
This is going to be a movie.

2475
01:18:05,113 --> 01:18:07,115
This is how-- this is like-- this is

2476
01:18:07,115 --> 01:18:08,450
going to be a one and a half hour movie.

2477
01:18:08,650 --> 01:18:09,051
Who's going to teach this?

2478
01:18:09,051 --> 01:18:10,819
It's going to take 30 seconds.

2479
01:18:11,286 --> 01:18:12,621
You need to cut this down.

2480
01:18:12,621 --> 01:18:14,423
30 seconds of my speed theater.

2481
01:18:14,423 --> 01:18:16,458
This is movie part one.

2482
01:18:17,092 --> 01:18:18,260
Coming back from movie part two.

2483
01:18:18,927 --> 01:18:19,361
All right.

2484
01:18:19,661 --> 01:18:20,328
I have to run.

2485
01:18:21,063 --> 01:18:21,663
Thank you for coming.