Verana Health's CEO on replicating studies with real-world data, diversity and patient focus

By Liza Laws

- Last updated on GMT

Interview: Verana Health's CEO, Sujay Jadhav on diversity and data

Related tags Real world data Data management Clinical trials Artificial intelligence Patient centricity Research Patient recruitment

With the FDA issuing guidance on more diversity within clinical trials, it is a subject many companies are being encouraged to focus on, each with their own approach.

OSP was very fortunate to spend some time with CEO of Verana Health, Sujay Jadhav who explained how the company’s existing exclusive arrangement with a number of societies puts them ahead of the game in three therapeutic areas. They have access to 90 million deidentified patients.

OSP: Could you give us a precis of your background and how you came to be CEO at Verana Health?

SV:​ I spent 25 years in enterprise software selling into the life sciences and I cut my teeth in the industry with a company called Model N, I was one of the first five there. In essence, that was a revenue management software company that helped big pharma, a medical device company has grown from gross revenue down to net revenue. I was helping pharma on the commercial side of the house optimising that process and it was a 14-year journey. They survived two economic nuclear storms in 2001 and 2008.

We took it public in 2013 and it continues to be public today. Then I jumped in a company called goBalto, a clinical trials software company, and that was focused on the early part of the clinical trial process - of study, startup, the locations – getting them ready from an administrative perspective. At goBalto I was just commercializing, and I managed to scale that and then eventually that was sold to Oracle. That was what really got me into the clinical trial arena.

OSP: So, tell me about Verana Health, what makes you stand out?

SV:​ In essence, we're focused on elevating quality, real world data. Our differentiated approach is that we partner with the societies in each of the three therapeutic areas that we focus on. Right now, that is ophthalmology, neurology and urology.

We’re very therapeutic focused, in terms our overall approach when we partner with our societies it's an exclusive arrangement. Each of these societies have a registry which members and providers give data to, so the societies get an output to help them reporting to the Merit-Based Incentive Payment System (MIPS)  and the Centers for Medicare & Medicaid Services' (CMS) submission, but overall it is understanding quality of care.

So, we provide that service for the society, the registry and the members and providers. And for that, we then have access to the data. We provide insights to life sciences companies with that particular data. Due to our exclusive arramgement, we probably have the largest accumulation of providers in each of these three therapeutic areas.

OSP: This is a unique but seemingly very productive way to access data, can you explain what you do with it once you have accumulated it all?

SV: ​Yes, this way does give us access to a very large volume of data overall within the therapeutic areas and it is electronic health data (EHR), real-world data and we tap into close to now 70 different types of EHRs – we have a massive network. We look at both the unstructured data including physician’s notes or images and structured data and then we leverage natural language processing on the notes. We have trained up machine learning models, and then they output that in a more structured fashion we then output what we call Qdata modules - that are in essence cohorts of patients with a particular disease area.

So as an example, in neurology, we have a multiple sclerosis Qdata module tapping out to all the neurologists out there for their data and we have tens of thousands of patients which have multiple sclerosis, all deidentified before life sciences companies use that Qdata module to provide insights across the overall lifecycle.

OSP: You mentioned deidentifying patients because that's obviously a big concern. Is data privacy becoming a more prominent focus?

SV: ​I think, in order to have these arrangements with the societies - an accumulation of providers and specialists - you have to understand they are very sensitive around patient data in ensuring and making sure that there's good quality controls including security controls. The arrangements we have with the society are very stringent and we have access to the identifiable data because we provide it back to the physician and then the physician is allowed to have access to help identify patients.

OSP: Have there been any sticky points on your journey and how have you overcome them?

SV: ​Real world data is out there and every, every second company talks about it. From a regulatory perspective I think the regulatory authorities have taken a very cautious approach to leveraging it the right way.

We have been replicating studies on drugs that have already been approved by the FDA (US Food and Drug Administration), mimicking it exactly. The advantages of this are that you can minimize the number of arms you have, particularly the placebo arm and use real-world data. This is understood a lot quicker – you know the effects of a particular drug as well as leveraging the data. We have done a number of these.

These kinds of studies can show the regulatory authorities that the real-world data is accurate.

One of the things we still do even though we have a very technical focus, there's still a need to have manual, final review. I think this is an area that is evolving. The quicker that everyone gets comfortable about that, we'll see the very large benefits out of it including clinical trial times, that may be, instead of taking 10 years, that timing is going to be dramatically less.

With the type of physician network, we have which is a combination of sophisticated physicians, physicians associated with medical centers all used to research but also a number in provider practices where research has never been conducted. Getting that group comfortable with participating research is important.

Sujay Javhad (1)

OSP: Two strong themes I have picked up on while at DIA include AI and machine learning but also, following the FDA guidance, diversity is being bandied around a lot too, how is Verana tackling this?

SV: ​Yes, diversity in in trials is a big thing right now and a lot of it is because a lot of the trials are done via sites or AMCs and generally these attract a profile but in a lot of cases that does conflict with certain diverse populations out there. This is one area that we're focused on is a non-profit. The registry we work with consists of all providers, so it doesn't matter whether you're a very small practice or very large practice. We have a lot of community-based practices in our network. We have 90 million deidentified patients and we have a lot of community based practices, which gives us access to a more diverse population - that's an area that we're focused on a in trial work. 

The disease areas we focus on are ophthalmology, neurology, and urology. In the African American community, prostate and bladder cancer are prominent diseases, in terms of research we are ripe for that because we have access to that patient population. The reason we have access is because they go to their local provider which is where the trust is. And we have access to that. I bring that up to address the original question and with the AMCs and sites, and providers that have done research a lot and the ones that have never done it before. One of the areas that we want to focus on including is getting the research naive, who have never done a trial before involved.  

OSP: Historically trial participants have been dominated by white males – how do you bring sponsors attention to this?

SV: ​It’s interesting and feels like the sponsors really want this, we don’t even have to convince them. Once we give access to our set of data, they say ‘boom, let’s bring in more diverse populations.’

We have just launched a product called VeraSite, which is a selection tool which we have initially launched in ophthalmology where we have 70 million deidentified patients. We are only US centric right now but here we have close to 70% of all ophthalmologists as part of our network.

This product allows sponsors and life sciences companies to give us their inclusion/exclusion criteria in essence, we can then understand which providers have the types of patient populations and then target them for clinical trials.

Roughly every other week we get a data feed into it, so we understand exactly where the patient is at any point in time. In some trials, you only have one- or two-week window of opportunity to recruit the patient.

We can use the patient population we have which is very accurate and the VeraSite tool accesses our network creates an understanding of which sites which physicians have which patient population and whether they’re fully deidentified. You find a doctor who has 20 patients that fit a particular trial, we then surface that up to them pointing out the patients are suitable which is particularly useful if they are research naïve, it allows the doctor to get in on a trial that would be good for his patients too.

There are two sides we've got the deidentified space for the life sciences companies where we can identify patients in various locations for those used to research and then because we have the relationship with the physicians and close to 20,000 providers out there, we can serve as help for the patients, to make it easy for doctors allowing them to get on with work rather than sifting through patient notes to see if they are eligible. 

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