Applied BioMath, the industry-leader in applying mechanistic modeling to drug development, has announced that it will collaborate with CytomX Therapeutics to develop a quantitative systems pharmacology (QSP) model of CytomX Therapeutics' probody platform.

"We chose Applied BioMath for this project because their past work with us has proven that they are the leader in applying QSP approaches in drug development. We look forward to this collaboration to help us maximize the efficiency of our probody platform for immuno-oncology. "Michael Kavanaugh, MD, chief scientific officer of CytomX Therapeutics

CytomX Therapeutics' novel probody platform allows the design of drugs that take advantage of unique conditions in the tumor microenvironment to enhance the tumor-targeting features of an antibody while reducing drug activity in healthy tissue.  Applied BioMath's QSP platform model will be systematically studied to better understand how avidity and target expression affect tissue targeting. This model will also be used to predict optimal drug properties and to help understand how to optimize probody efficiencies to maximize anti-tumor targeting while minimizing the normal tissue binding.

"The Probody platform from CytomX Therapeutics is exemplary of the novel approaches needed to transform drug development. We are thrilled to help maximize the efficiency of their innovations leveraging our own proprietary technologies. "Dr. John Burke, PhD, Co-Founder, president, and chief executive officer of Applied BioMath

Applied BioMath, the industry-leader in applying mechanistic modeling to drug research and development, helps biotechnology and pharmaceutical companies answer complex, critical Go/No-go decisions in R&D. Applied BioMath leverages biology, proprietary mathematical modeling and analysis technology, high-performance computing, and decades of industry experience to help groups better understand their candidate, its best-in-class parameters, competitive advantages, and the best path forward. The company’s involvement shortens project timelines, lowers cost, and increases the likelihood of a best-in-class drug. It provide clarity to complex situations, answer otherwise unanswerable questions, and approach, when validated in the clinic, is 10x more accurate than traditional methodologies.