Michael Ibara, Pharm.D.

After my Pharm.D. degree, I was selected for a Fellowship in Drug Development where we worked hands‑on across pharmacology, toxicology, Phase I-IV. After my Fellowship I took a clinical scientist job at a then‑fledgling CRO, where I learned the statistical techniques - and pitfalls - of building integrated summaries of safety and efficacy that stand up to regulatory scrutiny. While there I founded a pharmacovigilance function in the United States and then in Ireland. I began my management career there too, learning what it takes to work with people next door and around the world. At the end of my tenure at the CRO I was consulting for companies bringing drugs to market.

That led me to accept a senior role at an oncology biotechnology company where I was responsible for pharmacovigilance and clinical operations - and worked through a safety and financial crisis for one of our lead drug candidates. Eventually our team's efforts led to us being acquired, and I moved on to a large global pharma, where I spent the bulk of my career in a series of roles, each the equivalent of working in a different company. I was always at the intersection of technology and the business, and it was there I first met EHR data and began trying to use it for clinical research, learning the hard way that most healthcare data has no direct translation into regulated research. Still, I designed and ran a system that took physician‑identified adverse events straight from the EHR and reported them electronically to FDA. Working to get industry, FDA and vendors to adopt it led me into the world of regulatory policy and economic incentives, and what I learned there shaped my later work at a clinical standards organization, organizing the stakeholders in eSource, the use of electronic source data across the trial process: pharma, regulators, vendors, academics and practitioners.

As the age of data arrived for clinical research, I stood up and grew a data science group at an integrated research and site organization. To bring more sites into research, we built a system that integrated with site EHR data nightly, and we used it to represent sites for studies and place patients into trials, and to support trial operations. Five years building and running it, with larger and larger partners, showed me the perennial gaps in how trials run and how we apply technology to them.

Near the end of that time ChatGPT was released, and I came to believe this would have the greatest impact on clinical research of anything in my career. I moved to an AI startup, wrote its go‑to‑market strategy, and worked hands‑on with the team to build the first products on the roadmap, which eventually led to us being acquired. Since then I've moved into my current role but stayed fully engaged with AI and clinical research. The technology has moved so fast that I recently rebuilt, alone and in a week with current models, a product the previous team had spent a year on. I have seen the potential and the pitfalls in this work and I am invested in bringing solutions to the industry at every level to find the productivity gains and steer clear of the regulatory and economic traps.