Join us in this episode of CertaraTalks as Roman Casciano and Ananth Kadambi discuss the key highlights from ISPOR Europe 2023. Watch below for insights and key takeaways around topics like the European health data space and the use of AI for health technology assessment.
Transcript
Hello, and welcome to Certara Talks.
I’m Doctor Suzanne Minton, and I’m a director of content strategy at Certara . Today, I’m talking to two of my colleagues, Roman, and Ananth And I’ll turn it over to you gentlemen, to introduce yourselves. Why don’t you please start with you at month?
Sure. Thank you. Suzanne. So I’m Ananth Khudambi. I’m the vice president of real world evidence and modeling solutions, which is one half of the evidence and access business unit within Certara .
My, I’m relatively new to Certara. I’ve been here about five months now. But I spent a long career in pharmaceutical, consulting across many applications, including health economic modeling, real world evidence, health technology assessment, and so forth. And the work our team does within Certara is really, complimentary to the work my colleague Roman, who introduces us to do some stuff next, does on the consulting side.
Fantastic. What about you, Roman?
Thanks, Ananth. Hi, Roman Casiano.
I am a senior vice president here, and Tritara, and I had the value and access consulting business, which, as an aunt alluded to, we’re sort of the, let’s say, users of the scientific evidence that, his team is generating on a day to day basis to help companies get access for their products, demonstrate value for money and so on. So let’s call it the strategic arm. Of the of the of the heavily scientific team.
I’ve been with Certara for five plus years.
Since we were acquired in twenty eighteen, and I was part of the original company, the analytic group that was brought over at that time. So, yeah, nice to be talking with you today and, looking forward to the discussion.
Fantastic. Looking forward to talking with both of you. So I hear that you both just got back recently from the ISpor EU meeting in Copenhagen, Denmark. So I thought we could take a few minutes and and talk about the highlights. So, Roman, starting with you, I had heard that the EU Joint Clinical Assessment was a big focus of the meeting. Can you tell us what some of your takeaways were on this topic?
Sure.
And not only was it a big focus. I think it was probably central focus.
At least from a policy perspective, it was all over the meeting. I think there were at least fifteen different sessions and, you know, dozens of posters, on the topic.
I guess the big takeaway is, everybody’s a little bit uncertain as to, you know, what what it’s gonna mean, some comparing it to, you know, central regulatory evaluation in, in Europe, and and that is the that is the hope. I think where, there’s a lot of question marks because the the process has been pretty well laid out, and it’s it’s happening.
And, twenty twenty five, it’s already starting with oncology and, and, ATMPs.
But, the the the uncertainties that were being discussed were really relating to, you know, what what’s gonna happen on the heels of the joint clinical assessment at the country level.
The, as you may know, the the central, evaluation, the joint clinical assessment is that. It’s a joint clinical assessment. So the negotiations, the access that happens at the country level and all that is still up to the countries, pricing and and so on. So how do they take, what’s coming out of the joint clinical assessment into consideration locally Does it conflict with some of their current process? How do they have to, tweak their current local processes to deal with it. This to me is the biggest kind of open question.
Not a lot of the sessions tackle that topic, a lot were around the process and so on. But I found that the best sessions really ventured into that direction, like, what’s gonna happen in in Italy with the the current evaluation, which somehow overlaps with the joint clinical assessment in terms of the scope of what’s covered. You certainly wouldn’t expect that the Italian who are part of the joint clinical assessment process would be able to kind of overrule what’s decided or stated in the joint clinical assessment which they which they bought into. So that to me was the most interesting aspect of of the the kind of policy realm, that that I I saw at the at the meeting.
That’s great to know, Roman. And now let’s turn it over to you, Ananth. You mentioned in your introduction that Your expertise is in real world evidence and modeling and simulation. Can you and we know that the role of real world evidence in drug development has, been evolving a lot over recent years and can con continues to evolve.
Can you talk about how this was a theme at this meeting?
Yeah. Sure. I think the the main, eye popping event on this was, a lot of discussion. In fact, I think there was a, a plannery session, if I’m not mistaken on the European health data space, and the implications of that space in terms of improving collaborative efforts across, stakeholders in Europe. To access and use real world data.
So the framework I think is still under development, if I’m not mistaken, but the the policy will be rolled out fair in fairly short order. And I think everyone is trying to get prepared, to operate within that landscape, and set themselves up for success.
So I think the other key thing on the RWE side, was, I would say an ongoing debate, if you will, amongst some of the stakeholders, and this was touched upon in numerous, forums and pan panel discussions as well. But, an ongoing debate as to who should really drive the Real World Evans application, both in the health technology assessment setting, as well as potentially in regulatory applications.
The other theme that came up, repeatedly was, the use of RWE to develop external comparator arms which is a a general area that a focus where we know that data from randomized clinical trials are lacking in this respect and gaining comparative effectiveness, see, efficacy, or effectiveness measures, if you will, is is very difficult in those settings. And so there were a number of talks devoted to, published applications of RWE to develop external comparator arms.
And also some talks about, real world data quality and, and all in the context of the HDH HHDS space.
Got it. That’s great to know. We talked a fair bit about Europe. This is a European conference.
But we know in the US, The inflation reduction act, the IRA, which was signed into law by president Biden last year, has been a big and continuing area of focus for drug developers.
Roman, can you tell us about this topic and how it was presented at this conference?
Sure. Actually, I was a little, surprised there wasn’t more about, IRA. Though it’s a European health meeting in theory, it’s an international meeting. And And I think that the IRA, you know, we’ll we’ll likely have pretty substantial international consequences One of the one of the topics that did get covered, and it’s it’s related to the IRA is this sort of question about the US adaptation of, let’s call it nice, like, analytical methods cost effectiveness analysis etcetera.
And it it’s it was an interesting, panel, was participate, you know, Adrian Talas was leading the panel and and, some participants included, the former head of Icers, the Pearson, and, and, Pete Kolchinsky, who who kind of gave a, a sort of contrarian position, which I really felt was was nicely stated, because there’s a lot of talk about whether IRA should, in fact, allow for or include traditional cost effectiveness analysis as a measure of value. And you may be aware, it’s been specifically ruled out to use the quality or quality, like measures.
And there’s certainly a lot of, debate about whether that was too strong of a statement in the in the in the documentation.
Interestingly in this panel, they they they sort of turned the situation on its head. You know, a lot of times it’s talked about like, oh, well, what would be the benefit in turn in the US in terms of you know, pricing and budgets if we were to adopt, at that more CEA style, Doctor Colchinsky sort of put it on its head and said, well, would Europe be ready for a world in which the US valued medicines according to the kind of nice paradigm or or, you know, ICE’s paradigm.
And, you know, he took a strong position that that, in fact, that would be problematic because it would devalue innovation across the board. And despite the fact that sometimes access gets delayed in places like the UK because of cost effect in this analysis, eventually, even if it’s after generic, you know, encroachment, eventually that those technologies have gotten developed and and the the populations do get access. So I really like that panel. It was sort of, like, is the world ready for the US to use a kind of tighter evaluation method on on health care technologies.
And, you know, I walked away thinking. I’m not sure we are ready for that. So That was a great little session and, you know, something that to to keep an eye on in terms of the IRA and how that gets adopted.
Fantastic. Thanks for for sharing that with us. I’m thinking one last thing I’d wanna talk about with you and on is In twenty twenty three, I feel like the word of the year has been artificial intelligence, and we can’t you can’t go anywhere without seeing it. Right? It’s everywhere. And, so Can you talk a little bit about, what folks were saying at this conference about the use of AI for health technology assessment?
Sure. Absolutely.
Know, as with the last few years at, at these conferences, AI or artificial intelligence and machine learning, there are a number of buzzwords out there in the field have been hot topics discussion, and it was one of, I would say, the secondary foci of of the SISPR, in the sense that there were a lumbar, a number of discussions that revolved around how we embrace the so called revolution of of AI.
So I think the lead with the the takeaway, which is that, the consensus was that, well, Anne might have a future in supporting health technology assessment, It’s not, it’s not gonna experience, excuse me, it’s not gonna replace the experience of, of experienced scientists whose job it is to, develop fit for purpose solutions to the challenges that are faced during the HTA process.
But there are some very specific ways that AI has been shown to be used. And there were a number of posters on, for example, the use of, artificial intelligence to, support systematic literature reviews. And serve as a secondary screener, for, for the literature review applications.
The other thing that caught my interest is there were a number of sessions on machine learn learning learning and and LLM, which are, methodologies to rapidly sift through a large observational databases and essentially develop applications that are targeted to, help physicians diagnose and treat specific patients, as well as to help pharmaceutical companies potentially, investigate the value of their of their drug in in potential subpopulations as they look for drug indications, and ways to extend their label, if you will.
So all in all, I think it was, a really focused way. I think my personal perspective on this is AI is sort of a, a solution in search of problems to solve, and we’re getting to a point where people are actually finding concrete problems for which it is applicable, but more importantly than that, they’re realizing that it’s not a, a panacea for every challenge that’s faced out in the industry.
So if that that’s what I’ll I’ll leave you with.
Yeah. That’s great. So the a the AI is here. It’s got potential uses, but we’re still gonna be able to keep our jobs.
We haven’t been replaced by the robots quite There was a even a session on that.
It’s something to the effect of of, are we only losing our jobs in, in HTA? And that was, that was funny. The the takeaway was, of course, not. Yeah.
Yeah. Great. Well, that’s great to know. And, Roman, Ananth, it was a pleasure talking with both of you.
For our viewers, if you wanna know more about the work that Roman and Ananth are doing at Certara, visit us at our website. I’m Doctor. Suzanne Minton, and you’ve been watching Certara Talk. I’ll see you next time