LINCOLN, Mass., Oct. 23, 2017 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced that CytomX has once again chosen Applied BioMath for the development of their semi-mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) models of human for immuno-oncology. "Our choice of Applied BioMath for continued QSP model development reflects a track record of past successes with high-quality, innovative, and timely deliverables. The models have been used for internal decision making as well as to enable productive interactions with regulatory agencies," said Mark Stroh, Senior Director, Clinical Pharmacology, at CytomX Therapeutics, Inc.
Applied BioMath previously built models of CytomX's Probody platform which were used to predict optimal drug properties and help understand how to optimize probody efficiencies to maximize anti-tumor targeting while minimizing the normal tissue binding. This extension of the collaboration will focus on further enhancing the models to incorporate human clinical data to aid in the identification of knowledge gaps, sensitive model parameters, and to be used to inform first-in-human (FIH) dosing. "Our models incorporate the biophysics of the therapeutic as well as the disease biology," said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "Because of this, our models translate well from in vitro to preclinical and into clinical studies. They can continuously be updated with new preclinical or clinical data to help with predictions as therapeutics enter the clinic."
About Applied BioMath
Applied BioMath (www.appliedbiomath.com), 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. Our involvement shortens project timelines, lowers cost, and increases the likelihood of a best-in-class drug. We provide clarity to complex situations, answer otherwise unanswerable questions, and our approach, when validated in the clinic, is 10x more accurate than traditional methodologies.
Applied BioMath and the Applied BioMath logo are trademarks of Applied BioMath, LLC.
SOURCE Applied BioMath, LLC