Applied BioMath, LLC Announces Webinar on Model-Based Approaches to Design Bispecific Modalities in Early Discovery
CONCORD, Mass., Jan. 21, 2020 /PRNewswire/ -- 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, "Model-Based Approach to Design Bispecific Modalities in Early Discovery" occurs Tuesday, February 4, 2020 at 2p.m. ET / 11a.m. PT.
Understanding drug targets is critical to building an appropriate therapeutic that specifically binds to and elicits the magnitude and duration of response needed for an indication. In this webinar, Jennifer Fretland, PhD, Head of DMPK US, Sanofi, will present a tiered model-based approach used to determine the risk, feasibility, and developability of a bispecific antibody at the early stage to appropriately cover multiple antigen pairs. Once feasibility was assessed, further modeling was performed to determine ideal affinity ranges for each target in bispecific format at the site of action in order to help inform lead generation strategy. Sensitivity analysis was performed to understand each systems pharmacology parameter and its impact on predicted target coverage, which can help prioritize experiments and understand uncertainty earlier in the program. Ultimately, this approach guided teams for informed antibody design, prioritization of experiments, and triaging of challenging antigen pairs.
"A bispecific biologic binding two targets can lead to a variety of effects due to the possibility each antigen may exhibit similar or different kinetic-values. For example, impacting target mediated drug disposition, therapeutic index, and posology ultimately impacts not only developability, but also patients and clinical trials," said John Burke, PhD, Co-Founder, President and CEO, Applied BioMath. "Quantitatively integrating knowledge about the therapeutic with an understanding of its mechanism of action in the context of human disease mechanisms allows us to predict optimal drug properties and prioritize experiments. Doing this analysis before lead generation can help identify the risky projects, but just as importantly, identify and enhance the potential winners."
This webinar is ideal for scientists, protein engineers, and decision makers in R&D who want to learn more about how to leverage Quantitative Systems Pharmacology (QSP) approaches to provide quantitative guidance for their drug discovery and development.
For more information and to register, visit https://pages.questexweb.com/AppliedBioMath-registration-020420.html.
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 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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SOURCE Applied BioMath, LLC