Sr. Principal Scientist Applied BioMath, LLC Concord, Massachusetts
Drug discovery efforts are moving at a rapid pace and many novel treatments are being developed to treat complex diseases. This presents many challenges in drug modality selection, preclinical study designs and translation into the clinic. To ensure success, an in-depth understanding of both the mechanism of action of the drug and the pathology of the disease at a systems level is needed. Quantitative systems pharmacology (QSP) modeling can provide this mechanistic understanding by using basic biophysical and biochemical principles to describe the action of a drug in the context of the pathophysiology of disease. This presentation will highlight examples of how QSP modeling provides mechanistic understanding and quantitative translational leverage to bridge gaps between preclinical and clinical development.
Recognize opportunities within drug discovery and development where modeling can be used to predict how a drug will modulate complex biological systems involved in disease
Leverage QSP modeling to streamline drug development by designing the right in vitro/in vivo studies to support translation into the clinic
Utilize QSP modeling to support clinical trial design in different patient populations based on preclinical evidence