The use of advanced analytical technologies like artificial intelligence (AI) and machine learning (ML) is not exactly new to the field of clinical trials. However, the use of such tools has exploded in recent years, due to several factors; according to a recent industry report by KPMG​, the pandemic has accelerated AI’s adoption so much it has been termed “COVID-19 whiplash.”

Bioclinica chief innovation officer Dan Gebow, who has years of experience harnessing AI, spoke with Outsourcing-Pharma about the evolution of AI in clinical research, and his own experience in helping shape the tech.

OSP: Could you please share the ‘elevator presentation’ version of Bioclinica—who you are, what you do, key specialties, and what makes you stand out from the crowd?

DG: I’m a research scientist by training and over the course of my career I’ve worked on several clinical trials where I was really frustrated with the lack of effective technology. About 15 years ago, I was fed up enough to set out on my own to modernize the tools that are used in clinical trial research and bring them up to the level of sophistication that I was seeing in Silicon Valley at the time.

That mission has parlayed that into what I do today at Bioclinica, which is doing just that on a very large scale with a team of more than 300 engineers whose sole job is to invent the future of disease discovery research.

Bioclinica’s primary business is our imaging core lab. In a clinical trial, medical imaging is an important endpoint. It’s estimated that around 60% of trials have medical images collected as part of the patient’s review, and in oncology, it’s nearly 100%.