Applied BioMath (www.appliedbiomath.com), the industry-leader in applying systems pharmacology and mechanistic modeling, simulation, and analysis to de-risk drug research and development, today announced their upcoming webinar, "Translational Modeling Strategies to Predict Clinical Doses for CD3 Bispecific Molecules'' occurs Thursday, March 12, 2020 at 2p.m. ET / 11a.m. PT.
In this webinar, Alison Betts, Senior Director of Scientific Collaborations and Fellow of Modeling and Simulation, will present a case study where a translational quantitative systems pharmacology (QSP) model is proposed for CD3 bispecific molecules capable of predicting trimolecular complex (trimer) concentration between drug, T cell and tumor cell, and linking it to tumor cell killing. The model was used to predict the clinical starting dose of a P-cadherin/ CD3 bispecific construct (Pcad-LP-DART) using a Minimal Anticipated Biological Effect Level (MABEL) approach. The model also characterized the in vivo Pharmacokinetics (PK)/ Pharmacodynamics (PD) relationship of Pcad-LP-DART across mouse xenograft efficacy models and translated from mouse to human for Pcad-LP-DART for prediction of clinical efficacy, and to determine sensitive parameters impacting efficacy.
"We are excited that Alison Betts will be presenting this webinar that highlights the benefits of using mathematical, mechanistic modeling," said John Burke, PhD, Co-founder, President and CEO, Applied BioMath. "Quantitatively integrating the mechanism of action for this T cell engager with human disease mechanisms and preclinical data allowed teams to make more informed decisions in drug R&D, specifically here a MABEL FIH dose prediction."
This approach can also be applied at early stages to aid in the design of CD3 bispecific T cell engagers and other T cell engagers to select molecules with optimal properties and FIH dose predictions. This webinar is ideal for scientists and decision makers in drug R&D who want to learn more about how to leverage translational - mechanistic modeling and simulation approaches to provide quantitative guidance for their drug discovery and development.
For more information about and to register, visit https://pages.questexweb.com/AppliedBioMath-Registration-03122020.html?source=AppliedBioMath.
About Applied BioMath
Founded in 2013, Applied BioMath's mission is to revolutionize drug invention. 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 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.
Applied BioMath and the Applied BioMath logo are registered trademarks of Applied BioMath, LLC.
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Kristen Zannella