Applied BioMath, the industry-leader in applying mechanistic modeling to drug research and development, announced their collaboration with Tusk Therapeutics for quantitative systems pharmacology (QSP) modeling and analysis to enable preclinical candidate selection in immuno-oncology. Applied BioMath leveraged its proprietary mechanistic modeling platform to develop a QSP model of one of Tusk Therapeutics' targets and antibody candidates, then analyzed this model to identify optimal drug properties to aid preclinical candidate selection.
Tusk Therapeutics is harnessing the power of the innate and adaptive immune systems to fight cancer through the development of novel immune modulating therapeutics based on an in-depth understanding of the immune system. Tusk Therapeutics is establishing a diversified pipeline of antibodies against a selection of both novel and validated targets that play an important role in the immune response to cancer.
"Our project with Tusk is a great example of the impact QSP modeling has on drug research and development," said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "By creating a QSP model, we were able to identify optimal drug properties to ultimately enable preclinical drug candidate selection. Performing these analyses in silico prior to planning experiments reduces project timelines and budget."