Applied BioMath® (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced their participation at PepTalk: The Protein Science Week being held January 8-12, 2018 in San Diego, California.
John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath, will present a talk titled “Computational Exploration of Mechanistic Determinants of Antibody-Drug Conjugates (ADC) Pharmacokinetics (PK) Using Quantitative Systems Pharmacology (QSP) Modeling Strategies” on Tuesday, January 9, 2018 at 3:15 p.m. This presentation will demonstrate a computational approach to understand the impact of drug antibody ratio (DAR) and resulting changes in molecular properties on overall PK and relative payload disposition as observed in preclinical and clinical studies.
“We’re very excited to participate at PepTalk for the first time next year,” said John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. “This presentation establishes that QSP models can be leveraged to help design novel ADCs, and to optimize the discovery and development of existing ADCs.”
Applied BioMath has vast experience using Model-Aided Drug Invention (MADI) to support ADC research and development. MADI leverages mechanistic PKPD and systems pharmacology which quantitatively integrates knowledge about therapeutics with an understanding of mechanism of action in the context of human disease mechanisms. When applied to ADCs, MADI allows the computational exploration of numerous scenarios, such as the analysis of DAR or overall design of the ADC, in a fraction of the time it would take to figure out experimentally. Applied BioMath has previously announced collaborations with Zymeworks Inc. for QSP support for ADC therapeutics intended for the treatment of cancer, as well as, with CytomX Therapeutics for the development of a QSP model of CytomX Therapeutics’ Probody platform.
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.
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