Learning Tracks

Regulatory teams often rely on fragmented data sources—labels, clinical trials, literature, and regulatory documents—requiring time-intensive manual synthesis that can delay critical decisions and increase compliance risk.  This session will explore how emerging approaches, including fit-for-purpose AI and automation, are being applied to streamline regulatory intelligence workflows, improve data consistency, and enable teams to focus on higher-value scientific and regulatory decision-making.

Moderator: Craig Kiester, RPh, MS, RAC
Global Head of Regulatory and Quality Policy,  Biocon Biologics

Cristina Ausin, PhD
Scientific Reviewer, OTBB, OND, CDER, FDA

Tao Bai, PhD
Associate Director for Innovation and Partnership, IO, OB, OGD, CDER, FDA

Nimi Chhina, PhD, JD
Vice President, Global Regulatory Affairs Operations, Policy & Intelligence, Teva Pharmaceuticals

David Pennington, RN, BSN, MBA
Chief Executive Officer, Dr. Evidence

Andre Raw, PhD
Associate Director, OPQA I, OPQ, CDER, FDA

Breakout Session Sponsor: