Date: Thursday, April 3, 2025
Time: 11am ET
Solutions: Discovery, Preclinical, Early clinical, Late clinical, Regulatory
Model-Informed Drug Development (MIDD) has revolutionized the pharmaceutical industry by turning complex data into actionable insights. From in silico simulations of pharmacokinetics (PK) and pharmacodynamics (PD) to AI-driven risk assessments for liver injury, MIDD is guiding critical decisions such as dosing recommendations, “go/no-go” calls, and pipeline planning. This approach brings enormous value by enhancing cost efficiency, speeding up time to market, and delivering better treatments to patients.
The integration of Artificial Intelligence (AI) into MIDD doesn’t replace traditional methods but enhances them. AI accelerates model development by enriching data and providing more accurate validation. During this webinar, Certara experts will demonstrate how AI, including machine learning, is transforming MIDD into a faster and more powerful tool for decision-making in drug development.
Key topics include the application of deep learning in drug discovery, GPTs for validating QSP models that establish therapeutic potential, the use of machine learning in efficacy and safety analysis across diverse populations, and the evolving regulatory perspectives on AI’s role in evidence generation. Join us to explore how AI is streamlining the development of clinically relevant medicines, breaking down barriers, and enhancing our ability to bring new treatments to patients.
Senior Vice President, Certara Drug Development Solutions
Fran has over 25 years of experience with strategic and operational global drug development from early discovery to filing and post-marketing. She possesses a broad knowledge of strategic drug discovery and development, with a special focus on development strategy and the application of model-informed drug development (MIDD).
Senior Vice President and Head of Quantitative Systems Pharmacology
Piet van der Graaf is Senior Vice President and Head of Quantitative Systems Pharmacology at Certara and Professor of Systems Pharmacology at Leiden University. From 2013-2016 he was the Director of Research of the Leiden Academic Centre for Drug Research. From 1999-2013 he held various leadership positions at Pfizer in Discovery Biology, Pharmacokinetics and Drug Metabolism and Clinical Pharmacology. He was the founding Editor-in-Chief of CPT: Pharmacometrics & Systems Pharmacology from 2012-2018 before becoming Editor-in-Chief of Clinical Pharmacology & Therapeutics. Piet received his doctorate training in clinical medicine with Nobel prize laureate Sir James Black at King’s College London. He has been awarded the 2024 Gary Neil Prize for Innovation in Drug Development from the American Society of Clinical Pharmacology and Therapeutics (ASCPT) and was the recipient of the 2021 Leadership Award from the International Society of Pharmacometrics (ISoP). Piet is an elected Fellow of the British Pharmacological Society and has published >200 articles in the area of quantitative pharmacology and drug development.
Data Science and AI Solutions Architect
Ian Kerman (M.S. in Biology, M.S. in Computer Science) is a data science and AI solutions architect at Certara. With over 15 years of life science experience, Ian specializes in applying advanced AI and machine learning techniques to enhance research and discovery. His previous work included data and feature engineering, predictive model creation, and helping companies leverage AI to drive innovation in the pharmaceutical and healthcare sectors. Ian’s passion for solving complex scientific challenges fuels his current role of helping life science companies integrate AI, including LLMs and GPTs, into their life sciences workflows and processes.
Modeling and Simulation Expert
Ayman Akil, PhD is a modeling and simulation expert specializing in Model-Informed Drug Development (MIDD) and AI-driven pharmacometrics. As Director of Quantitative Science Services at Certara, he leads U.S.-based pharmacometrics consulting, applying population PK, exposure-response, and PK/PD modeling to optimize drug development. With a PhD in Pharmaceutical Sciences (University of Pittsburgh) and a fellowship in Disease & Therapeutic Response Modeling (Indiana University), Dr. Akil has held roles at Synteract, Mercer University, and Indiana University School of Medicine. His research spans Pharmacometrics and AI-driven drug modeling, leveraging tools like Phoenix WinNonlin, NONMEM, and R.
