Clinical Trials for the 21 st Century: Expanding the reach of clinical trials benefits everyone.
However, given the high costs and risks in bringing new medical and pharmaceutical technologies to market, there will likely be increased pressure on companies to utilize digital technologies to alleviate some of the risk in clinical trials. A subsidiary of SPRIM, the core offering of ObvioHealth called ClaimIt (Figure 1), is making clinical trials faster and more cost-effective by digitizing the process, while complying with FDA requirements and Good Clinical Practice guidelines. This proprietary software supports observational and interventional studies, allowing integration with smart phones, connected devices, and real-time subject interaction.
Bryan Silverman, CEO, explains the clinical research industry is ripe for modernization. "Our mobile model affords a truly patient-centric approach. Claimlt allows study subjects to take part in important healthcare research from the comfort of their homes-anywhere in the world."
"Study protocols can be designed with smart devices, such as a Bluetooth blood pressure monitor or other devices to provide real-time, 24/7 data monitoring. This means that adverse events are detected immediately. Also, healthcare professionals can video chat or text with participants at any time."
This technology is not meant to replace traditional test sites, but is intended to extend the power and reach to eliminate some of the roadblocks, including participant dropout. ClaimIt offers both 100 percent site-less clinical trials, and the opportunity for hybrid studies where a brick & mortar environment is required.
"When the subject or patient leaves the CRO, hospital, clinic, or doctor's office, they are still digitally-connected to the trial, 24/7," says Silverman (Figure 2).
A Team Effort
What got this project in motion was hiring the right people, Silverman explains. "It's a true team effort. I hand-selected people that had already proven themselves working at other companies. Then I worked with them side-by-side. This is developing true software, not a patch-in app. The technical element of an app can be written in a day or two. This takes months and months of work."
"It requires a knowledge transfer from the people who do this for a living; clinical teams, biostatisticians, medical personnel. Then you have to take that knowledge dump and lay it out into the language of building the software. You have to understand how the technology works, taking the clinical knowledge, regulatory knowledge and requirements, and putting that into a digital format. I have to say that this is the hardest piece of software I've ever had to build, hands down."
Silverman adds that the hardest part was designing the back-end system architecture that is both device and application agnostic. "More often than not, you are working with large multi-nationals across all areas, medical device developers, hospital systems, pharmaceuticals, contract research and more."
"To do this, you need to design a solution that can create centralization. It then becomes the core, and you can enable any company you are working with to create this centralization where they now have an eco-system that allows all vendors and partners to plug in, operate, and play together in the same sandbox."
"There were many challenges regarding what can and can't be done with data. Who gets to see that data and how do you give them access to the data? For example, we are separating a lot of the elements into components and modularizing it. If I look at the bio-stat side, can I enable a bio-statistics module? Can it enable the system to do a high 80-plus percent of what an actual bio-statistician would be able to do? This way you can have data insights faster--not wait three months, but do it immediately--depending on what you're looking to do with what's right in front of you."
Silverman says that as long as it's written into the study protocol, and approved by the IRB (Institutional Review Board), any adaptive design can be leveraged using machine learning and live data. Any trial course can be corrected for elements, such as therapeutic dose and increasing or decreasing population test size to bring a study back on course instead of waiting for it to fail, which is the status quo for almost all clinical trials today.
"This was what struck me as a clinician; the ability to actually capture an adverse event in real-time and report it in real-time simply can't be done using only a traditional brick and mortar study site. This capability is extremely powerful when testing any new medical device or drug."
Silverman says that ObvioHealth started serving clients months ago, but they are never actually done with updating and creating the software. "We are always looking for our software platforms to grow from V1 to V1000 ++. What dictates that for the most part are sales meetings. The client tells us what they need or what they wish they could do in the future. Then we decide how to improve the product from our studies, the outcomes, what happened that could be better--there are always lessons to be learned."
"We are developing a method that we hope to roll out in the latter part of this year that will enable us to identify participants who are at high risk for drop-off or protocol deviation. It's like identifying a readiness or willingness to change. Identifying that will enable us to become more effective in recruitment. Another part we can do during a trial is run a parallel track that's focused on behavior to monitor and identify behaviors that show and build the early business case for medication adherence, which builds the early case for market access. We are building in these types of elements as we identify each new value add, because our goal is to continually improve the product."
"Our demographics cover the full spectrum. We had quite a large number of infant trials. Then it jumps to the other end of the pool, to the elderly and everything in-between. It covers a wide spectrum. Each level of a multilevel value prop exists to satisfy the needs of highly different stakeholders. It might be by adding a new technology capability, or a new way to communicate, and so on."
Keeping All Trials Safe
This service runs in the cloud. "Depending on what country we operate in, that might be a different cloud provider. If somebody can penetrate their walls, that's one level. The other level is using extremely advanced data encryption," says Silverman. "We can slice our data sixty ways from Sunday, and that's what we do as another layer of protection. So, even if a hacker captures any of our data, they will have absolutely nothing of any meaningful value. It's not just one, but multi-layered encryption."
Silverman says that his vision is to engage the subject from day one, go through all the phases with them, and then go into post marketing surveillance. "Imagine the ability to access and track the lifetime usage of drug X or implanted device Y, and to have machine learning tracking them forever. The data allows us to show the company, that makes a drug or device, what's happening at any point in time."
"Now, imagine data that starts showing the early signs of heart disease, which means you have to stop the use of that particular drug. On the other side, what if the data found that the drag or device was improving other aspects of the user's health that it was not designed to do? Suddenly the company has an expanded market they had no idea was out there."
By Joyce Laird, Contributing Writer
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|Title Annotation:||Emphasis On Digital Medicine|
|Publication:||Medical Design Technology|
|Date:||Nov 1, 2018|
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