Q&A With Craig Gravina, CTO at ObvioHealth

Craig Gravina

MDT spoke with Craig Gravina, cto at ObvioHealth, a decentralized clinical trial provider that offers platforms and services to conduct clinical trials in both a digital and a hybrid environment. Gravina oversees all of the product development, technology, and R&D. The company recently launched a proprietary application programming interface (API) that reduces the burden on clinical trial patients when capturing adherence and efficacy data.

(MDT:) What are the challenges with running clinical trials in the digital therapeutic space?

Gravina: When we talk about our distributed clinical trials platform, that is in terms of the operation of a normal clinical trial. We’re doing all kinds of things to capture outcomes for efficacy and safety. What we’re working with specifically is ways to measure outcomes, adherence, efficacy, and safety for app based therapeutics. There’s a few challenges specific to running trials in this newly emerging digital therapeutic space. The challenges of measuring efficacy and adherence in a decentralized clinical trial, it is really the reliance on the patient reported outcomes, and the frequency and adherence to reporting those outcomes. That leads to solutions like remote patient monitoring and devices to measure vitals.

There’s also a whole aspect to our business in which we are going beyond what is typically called electronic patient recorded outcomes, and we call that digital instruments. It is a step beyond where we’re using images, sounds, and video to measure symptomology. An example would be passively listening to audio for explosive sounds to measure cough frequency. We’re doing a lot of work on that front in terms of better ways to capture symptomology and outcomes.

(MDT:) How can the use of apps impact the data collected during clinical trials?

Gravina: In relation to digital therapeutics in general, it presents a whole new set of challenges. Specifically, we’re typically dealing with an at-case environment, and a lot of the digital therapeutics use the app as the actual therapeutic work, or a core component of it.

For example, with a behavioral health digital therapeutic, it may just be the fact that you’re using it daily to capture diaries of how you’re feeling, that by virtue of monitoring your health, your health gets better. In a typical decentralized trial, there is a study app that tells patients to take their medication and report the outcomes. If we do that same approach for a digital therapeutic, where we are biasing the actual efficacy of the therapeutic because we’re saying “hey, it’s time to go use your digital therapeutic.” If it’s not a compelling enough user experience, patients aren’t going to use it and therefore, the efficacy may not be valid.

There’s a challenge of saying “is the study app the point of driving the trial activities, or can you rely on the participant to use the app and capture data that’s coming from that.” That was one of the fundamental challenges that we solved by having this concept of a set of digital therapeutic APIs that could provide us with outcomes data passively in the background without us having to nudge the participant to have to use the device or app.

(MDT:) How does your API solve for these issues?

Gravina: Another challenge is the fact that a lot of the therapeutics use the same questionnaires for gathering information on patient reported outcomes. In a behavioral health environment, you’re mostly likely going to be asking people to fill out a PHQ9 or a GAD7 to measure depression, anxiety, etc. In their app, they may be reporting that back to the patient so that they can monitor their own recovery. You’d wind up with duplication of effort from the participant if they are also answering those questionnaires in the study app. We’re essentially capturing when there is a duplication of study activities or instrumentation directly from the app. A lot of the outcomes that are being captured to prove efficacy or monitor safety can happen in the background passively through this set of APIs.

(MDT:) How does the API improve tracking adherence?

Gravina: The third challenge is in adherence. Knowing that the person used the app and getting the data from the API is more reliable than asking the participant if they used the app today. The adherence is a lot more complex in an app as opposed to taking a pill or medication. Patients need to use the app in an effective way that counts as adherence to the therapeutic and that can encompass a lot of different things. There is different criteria that, based on user behavior with the digital therapeutic, may or may not be used to monitor and measure adherence in a more effective way.

These are things that I think are relatively unknown in the industry. Biasing the use of a therapeutic can be really impactful and as digital therapeutics gain ground and there begins to be more clinical trials associated with them, these are challenges that everyone is going to have to address, or the study data is not going to relevant to the regulatory firms.