March Webinar: From data driven to theoretical: improving preclinical decision making with modeling

March Webinar: From data driven to theoretical: improving preclinical decision making with modeling Amy Moody, PhD Senior Principal Scientist, Pfizer, Cambridge, MA March 13, 2024 12:00-1:00 PM EST Register at https://rosaandco.com/webinars At Pfizer, modeling in the preclinical space is used in numerous ways to place programs in the appropriate quantitative context and supports key decision making on the path to clinical development. In this presentation, we will give two examples where modeling was at the center of decisions to progress or terminate early programs. Tafamidis is a small molecule TTR stabilizer and was the first treatment approved for amyloid cardiomyopathy (ATTR-CM). While tafamidis delays disease progression and provides substantial clinical benefit, it does not completely arrest disease progression and Pfizer was interested in whether a more potent molecule could provide additional clinical benefit. We will describe analysis of clinical and preclinical data that concluded tafamidis captures greater than 90% of the horsepower of this mechanism which led to the decision to terminate a follow-on program. Three mechanisms all aim to treat sickle cell disease by preventing polymerization of mutated hemoglobin (HbS). We will describe a model that was developed to predict the required level of target modulation by each mechanism alone and in combination. This model helped identify programs with the highest likelihood of success as well as faster paths to the clinic through combination strategies. These examples show how very different approaches (patient data driven vs. theoretical model) can be applied to preclinical programs to assess confidence in the target, set clear goals for program progression, and chart more efficient paths towards clinical success.