Lincoln, MA /PRNewswire/ - Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced that on September 13, 2017, Dr. Joshua Apgar, Co-Founder and CSO of Applied BioMath, will present a webinar titled "Exploring ADC Pharmacokinetics using QSP Modeling Strategies." This webinar will show how quantitative systems pharmacology (QSP) modeling approaches provided biological insights into the impact of drug-to-antibody (DAR) ratio and the resulting changes in molecular properties on overall pharmacokinetics (PK) and relative payload disposition as observed in preclinical studies.
"We used QSP modeling to explore the PK of antibody-drug conjugate (ADC) therapeutics which typically show a discrepancy between the PK of total antibody and that of conjugated antibody, carrying one or more payload molecules," said Joshua Apgar, PhD, Co-Founder and CSO at Applied BioMath. "This discrepancy is often attributed to deconjugation, however recent evidence suggests that the underlying mechanisms may be more complex. Modeling helps generate hypotheses that predict this complex behavior."
"This ADC case study is a great example of how Model-Aided Drug Invention (MADI) helps project teams quickly discern important characteristics of a platform or drug candidate," said John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "We often hear from our clients how valuable these biological and drug insights, sometimes counterintuitive, are as it helps accelerate drug candidates into the clinic and to then better ensure the likelihood of testing proof of clinical concept."
This webinar will air live at 2pm ET / 11am PT and is ideal for scientists interested in how computational models can be used to design novel ADCs and to optimize the discovery and development of existing ADCs. For more information on this webinar and to register, visit: www.appliedbiomath.com/20170913_webinar
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.
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