Applied BioMath , the industry-leader in applying systems pharmacology and mechanistic modeling, simulation, and analysis to de-risk drug research and development, announced a collaboration with Gritstone Oncology, Inc. for semi-mechanistic systems pharmacology modeling.
Applied BioMath created a semi-mechanistic pharmacokinetic, receptor occupancy model for a Gritstone Oncology, Inc. bispecific antibody. Gritstone plans to leverage this model for clinical candidate selection for its work in treating solid tumors. “Our collaboration with Applied BioMath helped us explore the impact of various drug properties such as affinity and half life,” said Jonah Rainey, Vice President of Antibody Therapeutics at Gritstone Oncology, Inc. “Their modeling efforts provided a framework for identifying optimal bispecific design for lead selection.”
Applied BioMath employs a rigorous fit-for-purpose model development process which aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. Their approach employs proprietary algorithms and software that were designed specifically for mechanistic PK/PD modeling. “When you are designing a bispecific therapeutic, or any complex therapeutic, it’s extremely difficult to assess ideal drug properties without the aid of modeling,” said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. “Specifically, it’s the mechanistic component of our systems pharmacology modeling that enables us to closely replicate therapeutic and disease biology which in turn helps our clients quickly answer critical questions about their project.”
About Applied BioMath
Founded in 2013, Applied BioMath uses mathematical modeling and simulation to provide quantitative and predictive guidance to biotechnology and pharmaceutical companies to help accelerate and de-risk drug research and development. Their Model-Aided Drug Invention (MADI) approach employs proprietary algorithms and software to support groups worldwide in decision-making from early research through clinical trials. The Applied BioMath team leverages their decades of expertise in biology, mathematical modeling and analysis, high-performance computing, and industry experience to help groups better understand their candidate, its best-in-class parameters, competitive advantages, patients, and the best path forward into and in the clinic. For more information about Applied BioMath and its services, visit www.appliedbiomath.com.
