Use of Quantitative Methods to Support Keytruda Dose Selection

Friday, March 23, 2018 - 1:25pm - 2:25pm
Lind 305
Anna Kondic (Merck & Co, Inc.)
Anna Georgieva Kondic
PhD MBADistinguished Scientist, Economic and Data Sciences
Merck Pharmaceuticals

Recently, immunotherapy has yielded promising results in several cancer types. Contrary to the established classical chemotherapy-dosing paradigm, a maximum tolerated dose approach does not always produce better clinical outcomes for novel targeted therapies, as their efficacy is frequently robust at pharmacologically active doses below the maximum tolerated dose. Integrated safety and efficacy assessments are needed to inform clinical dose and trial design, and to support an early identification of potentially safe and efficacious combination treatments. In this talk, I will walk you through the history of how the dose for Merck’s immunomodulatory drug pembrolizumab (Keytruda) was selected; how the transition from weight-based to fixed dose was made and how mathematical modeling and data science is helping shape the field of drug development.

Anna Georgieva Kondic is a mathematician by training, receiving her PhD in Mathematical Physics from Duke University in 1998. Anna holds a degree in Business Administration from NYU, with a specialization in negotiations.

Anna is currently a distinguished scientist in the Data and Economic Sciences department at Merck and Co, where she is responsible for the implementation of economic models in the early space of R&D. Prior to her current position, Anna was part of Merck’s quantitative pharmacology department, where she was responsible (among other things) for the filing strategy and clinical pharmacology dossier for Merck’s immunomodulatory drug Keytruda, currently approved for multiple tumor types.
Before Merck, Anna spent 11 years at Novartis, where she supported arthritis, osteoporosis, Oncology, diabetes and cardio-vascular disease using both empirical and mechanistic models to aid quantitative decision making.