WEBVTT
00:00:00.670 --> 00:00:04.440
Bringing a cell or gene therapy to market is an art.
00:00:05.070 --> 00:00:14.160
Hear rista thought leaders as they draw on their specialized expertise to offer insight on timely relevant clinical development topics.
00:00:15.449 --> 00:00:25.239
Welcome to Art Podcasts, advancing Revolutionary Therapies, a podcast presented by the Center of Excellence for Cell and Gene Therapies at rista.
00:00:25.649 --> 00:00:33.920
Today's podcast is a clip of key insights from our recent webinar on the role of natural history studies in rare disease trials.
00:00:34.759 --> 00:00:47.640
Here Rachel Smith, portfolio director at Rista review considerations for setting up natural history studies and the value they bring to rare and ultra rare clinical research despite the challenges in their design.
00:00:48.130 --> 00:00:54.240
If you'd like to listen to the webinar in its entirety, please search our knowledge base@veristat.com.
00:00:55.450 --> 00:01:01.679
So everyone in this room will be familiar with the challenges when it comes to rare and ultra rare disease research.
00:01:01.939 --> 00:01:10.640
The first point is we're talking about really, really small sample sizes, really small patient numbers, and the patients are generally spread across the world.
00:01:10.641 --> 00:01:13.079
We might only have one or two patients per country.
00:01:13.799 --> 00:01:13.799
Now.
00:01:13.801 --> 00:01:18.000
It's not realistic to actually set up a clinical trial in every single country in the world.
00:01:18.560 --> 00:01:18.920
They're not gonna happen.
00:01:19.209 --> 00:01:20.959
So how do we access those patients?
00:01:21.239 --> 00:01:23.040
That's a significant challenge for us.
00:01:23.500 --> 00:01:31.959
And then we tend to have a real lack of knowledge around the disease itself, the severity, the progression, um, the standard of care.
00:01:32.319 --> 00:01:38.560
There might be variability from hospital to hospital, from country to country, and how these types of diseases are actually managed and treated.
00:01:39.019 --> 00:01:48.319
And then from a endpoint in outcome perspective, we quite often with these types of diseases, because they're so rare, we end up using proxy endpoints.
00:01:48.480 --> 00:01:57.280
So proxy assessments, assessments that are really aimed at wider diseases, larger diseases, diseases that might be related, but not, obviously not the same.
00:01:57.329 --> 00:02:05.040
So when we are talking about rare disease research, how do we decide which endpoints are we gonna use, particularly when there are none?
00:02:05.519 --> 00:02:10.960
Uh, when we're talking about these types of trials as well, we're not talking about wanting to cure patients necessarily.
00:02:11.120 --> 00:02:14.520
We're talking about wanting to give them improvements in their quality of life.
00:02:14.520 --> 00:02:16.240
And what does that mean to the patient?
00:02:16.241 --> 00:02:19.800
Does it mean just being able to pick up a spoon to be able to feed themselves?
00:02:19.800 --> 00:02:26.120
We're not talking about maybe huge changes in their lives, but what is meaningful for this patient, um, in this rare disease setting?
00:02:26.419 --> 00:02:32.039
And this is why a natural history study is useful because it allows us to identify the patients.
00:02:32.129 --> 00:02:38.759
It allows us to identify or even develop our own clinical endpoints, so assessments or biomarkers.
00:02:38.900 --> 00:02:46.719
And then when we're moving to essentially go into market, it also allows us to have a controller, a comparative dataset.
00:02:46.840 --> 00:02:55.400
Quite often in these types of studies, in these types of disease areas, we're looking at really innovative therapies like cell gene immunological therapies.
00:02:55.401 --> 00:03:02.199
And so it's often not ethical to actually have this gold standard double blind placebo controlled trials.
00:03:02.330 --> 00:03:04.599
So how do we mitigate against that?
00:03:04.960 --> 00:03:08.159
Um, we can use this data, um, to be able to access a control.
00:03:08.340 --> 00:03:11.800
And once you've decided to do a natural history study, then how do you design it?
00:03:11.889 --> 00:03:23.840
So do you go with the retrospective approach where you collect data historically, but you might end up with the risk of having missing data incomplete or variable inconsistent data sets with a huge amount of bias?
00:03:24.250 --> 00:03:43.319
Or do you have the perspective approach where you enroll patients and can maybe follow the disease progression and collect more data, but is it then a risk for your clinical trial, clinical program and potentially moving into interventional studies where you are looking to actually improve on these patients' conditions and you just can't afford to let these patients progress with their disease?
00:03:43.620 --> 00:03:56.599
And then when it comes to the sampling method, do you go with a cross-sectional approach where you look at various stages of the disease, but potentially run the risk of missing critical data in the transitional period or critical data from disease subtype?
00:03:56.600 --> 00:04:10.000
Or do you go with a longitudinal approach where again, you're enrolling patients maybe at disease diagnosis and looking at the disease progression over time, but you run the risk of having really, really long studies and time is a premium, um, in this industry.
00:04:10.001 --> 00:04:12.639
So how can you most effectively collect this data?
00:04:13.039 --> 00:04:14.719
Um, and again, you can use a combined approach.
00:04:15.289 --> 00:04:21.720
So then the challenges with these natural history studies in your rare diseases are very much related to the fact that it's a rare disease.
00:04:21.721 --> 00:04:29.399
So the, the challenges I went through earlier, but also because these endpoints aren't defined, how do you define them in these natural history studies?
00:04:29.399 --> 00:04:31.360
And how frequently do you do this assessment?
00:04:31.750 --> 00:04:33.560
What functional as assessments do you choose?
00:04:33.560 --> 00:04:34.720
What biomarkers do you choose?
00:04:34.721 --> 00:04:36.120
How do you assess quality of life?
00:04:36.120 --> 00:04:37.759
And then what patients do you include?
00:04:37.959 --> 00:04:53.920
Do you include a broader data set, broader population than you would in conventional trial where you would have might maybe quite stringent or quite strict eligibility criteria, but you are able to collect in these natural history trials more, more data on the fringe patients, on the patients that wouldn't be enrolled or these subgroups as well.
00:04:53.939 --> 00:04:57.199
And then the bigger challenge, how do we find the patients?
00:04:57.201 --> 00:04:58.560
How do we engage with them?
00:04:58.560 --> 00:05:07.959
How do we ensure that they are understanding perceived benefit of participating and not seeing it as an added burden to their everyday disease and everyday management?
00:05:08.680 --> 00:05:10.040
Don't miss an episode.
00:05:10.720 --> 00:05:17.600
Subscribe on your favorite podcast player and look for our other cell and gene podcasts@cellandgene.expert.
00:00:00.670 --> 00:00:04.440
Bringing a cell or gene therapy to market is an art.
00:00:05.070 --> 00:00:14.160
Hear rista thought leaders as they draw on their specialized expertise to offer insight on timely relevant clinical development topics.
00:00:15.449 --> 00:00:25.239
Welcome to Art Podcasts, advancing Revolutionary Therapies, a podcast presented by the Center of Excellence for Cell and Gene Therapies at rista.
00:00:25.649 --> 00:00:33.920
Today's podcast is a clip of key insights from our recent webinar on the role of natural history studies in rare disease trials.
00:00:34.759 --> 00:00:47.640
Here Rachel Smith, portfolio director at Rista review considerations for setting up natural history studies and the value they bring to rare and ultra rare clinical research despite the challenges in their design.
00:00:48.130 --> 00:00:54.240
If you'd like to listen to the webinar in its entirety, please search our knowledge base@veristat.com.
00:00:55.450 --> 00:01:01.679
So everyone in this room will be familiar with the challenges when it comes to rare and ultra rare disease research.
00:01:01.939 --> 00:01:10.640
The first point is we're talking about really, really small sample sizes, really small patient numbers, and the patients are generally spread across the world.
00:01:10.641 --> 00:01:13.079
We might only have one or two patients per country.
00:01:13.799 --> 00:01:13.799
Now.
00:01:13.801 --> 00:01:18.000
It's not realistic to actually set up a clinical trial in every single country in the world.
00:01:18.560 --> 00:01:18.920
They're not gonna happen.
00:01:19.209 --> 00:01:20.959
So how do we access those patients?
00:01:21.239 --> 00:01:23.040
That's a significant challenge for us.
00:01:23.500 --> 00:01:31.959
And then we tend to have a real lack of knowledge around the disease itself, the severity, the progression, um, the standard of care.
00:01:32.319 --> 00:01:38.560
There might be variability from hospital to hospital, from country to country, and how these types of diseases are actually managed and treated.
00:01:39.019 --> 00:01:48.319
And then from a endpoint in outcome perspective, we quite often with these types of diseases, because they're so rare, we end up using proxy endpoints.
00:01:48.480 --> 00:01:57.280
So proxy assessments, assessments that are really aimed at wider diseases, larger diseases, diseases that might be related, but not, obviously not the same.
00:01:57.329 --> 00:02:05.040
So when we are talking about rare disease research, how do we decide which endpoints are we gonna use, particularly when there are none?
00:02:05.519 --> 00:02:10.960
Uh, when we're talking about these types of trials as well, we're not talking about wanting to cure patients necessarily.
00:02:11.120 --> 00:02:14.520
We're talking about wanting to give them improvements in their quality of life.
00:02:14.520 --> 00:02:16.240
And what does that mean to the patient?
00:02:16.241 --> 00:02:19.800
Does it mean just being able to pick up a spoon to be able to feed themselves?
00:02:19.800 --> 00:02:26.120
We're not talking about maybe huge changes in their lives, but what is meaningful for this patient, um, in this rare disease setting?
00:02:26.419 --> 00:02:32.039
And this is why a natural history study is useful because it allows us to identify the patients.
00:02:32.129 --> 00:02:38.759
It allows us to identify or even develop our own clinical endpoints, so assessments or biomarkers.
00:02:38.900 --> 00:02:46.719
And then when we're moving to essentially go into market, it also allows us to have a controller, a comparative dataset.
00:02:46.840 --> 00:02:55.400
Quite often in these types of studies, in these types of disease areas, we're looking at really innovative therapies like cell gene immunological therapies.
00:02:55.401 --> 00:03:02.199
And so it's often not ethical to actually have this gold standard double blind placebo controlled trials.
00:03:02.330 --> 00:03:04.599
So how do we mitigate against that?
00:03:04.960 --> 00:03:08.159
Um, we can use this data, um, to be able to access a control.
00:03:08.340 --> 00:03:11.800
And once you've decided to do a natural history study, then how do you design it?
00:03:11.889 --> 00:03:23.840
So do you go with the retrospective approach where you collect data historically, but you might end up with the risk of having missing data incomplete or variable inconsistent data sets with a huge amount of bias?
00:03:24.250 --> 00:03:43.319
Or do you have the perspective approach where you enroll patients and can maybe follow the disease progression and collect more data, but is it then a risk for your clinical trial, clinical program and potentially moving into interventional studies where you are looking to actually improve on these patients' conditions and you just can't afford to let these patients progress with their disease?
00:03:43.620 --> 00:03:56.599
And then when it comes to the sampling method, do you go with a cross-sectional approach where you look at various stages of the disease, but potentially run the risk of missing critical data in the transitional period or critical data from disease subtype?
00:03:56.600 --> 00:04:10.000
Or do you go with a longitudinal approach where again, you're enrolling patients maybe at disease diagnosis and looking at the disease progression over time, but you run the risk of having really, really long studies and time is a premium, um, in this industry.
00:04:10.001 --> 00:04:12.639
So how can you most effectively collect this data?
00:04:13.039 --> 00:04:14.719
Um, and again, you can use a combined approach.
00:04:15.289 --> 00:04:21.720
So then the challenges with these natural history studies in your rare diseases are very much related to the fact that it's a rare disease.
00:04:21.721 --> 00:04:29.399
So the, the challenges I went through earlier, but also because these endpoints aren't defined, how do you define them in these natural history studies?
00:04:29.399 --> 00:04:31.360
And how frequently do you do this assessment?
00:04:31.750 --> 00:04:33.560
What functional as assessments do you choose?
00:04:33.560 --> 00:04:34.720
What biomarkers do you choose?
00:04:34.721 --> 00:04:36.120
How do you assess quality of life?
00:04:36.120 --> 00:04:37.759
And then what patients do you include?
00:04:37.959 --> 00:04:53.920
Do you include a broader data set, broader population than you would in conventional trial where you would have might maybe quite stringent or quite strict eligibility criteria, but you are able to collect in these natural history trials more, more data on the fringe patients, on the patients that wouldn't be enrolled or these subgroups as well.
00:04:53.939 --> 00:04:57.199
And then the bigger challenge, how do we find the patients?
00:04:57.201 --> 00:04:58.560
How do we engage with them?
00:04:58.560 --> 00:05:07.959
How do we ensure that they are understanding perceived benefit of participating and not seeing it as an added burden to their everyday disease and everyday management?
00:05:08.680 --> 00:05:10.040
Don't miss an episode.
00:05:10.720 --> 00:05:17.600
Subscribe on your favorite podcast player and look for our other cell and gene podcasts@cellandgene.expert.
