In a recent discussion focused on drug development and portfolio management, hosted by Emerj, Panos Karelis from Intelligencia AI and Scott Bradley of Novartis independently explored how AI is reshaping critical decision-making in these areas.
Throughout their conversation, both leaders emphasized the importance of embedding AI thoughtfully into existing decision-making frameworks. Their insights underscore the importance of success not only in technical accuracy but also in transparency, change management, and the ability to translate predictions into actionable guidance for teams operating across clinical and business domains.
- Building trust through transparency: How making AI models interpretable at both input and output levels helps overcome skepticism, supports validation steps in early-stage drug development, and builds confidence across R&D teams.
- Improving portfolio decision-making: How AI enables sponsors to evaluate trade-offs across pipeline assets earlier and with greater accuracy—helping R&D leaders identify high-potential assets, reduce risk, and allocate resources more strategically.
Read and listen to the expertise shared on AI adoption, risk management, data transparency, and change leadership in pharmaceutical R&D.