Applied BioMath (www.appliedbiomath.com), the industry-leader in providing model-informed drug discovery and development (MID3) support to help accelerate and de-risk drug research and development, today announced their participation at SITC occurring virtually and in Washington, D.C. on November 10-14, 2021.

At the conference, David Flowers, PhD, Principal Scientist at Applied BioMath is presenting the poster (#227) titled, "A computational semi-mechanistic pharmacology model of ATG-101, a PD-L1/4-1BB bispecific antibody for treatment of solid tumors." This work describes Applied BioMath's collaboration with Antengene for the development of a systems pharmacology model that was used to understand the tumor killing mechanism and provide first-in-human dose predictions and analysis of Antengene's therapeutic and inform clinical starting and efficacious doses for phase 1.

Additionally, Applied BioMath's collaboration with Genmab will be featured at poster #786, "Dose selection for DuoBody®-PD-L1×4-1BB (GEN1046) using a semimechanistic pharmacokinetics/pharmacodynamics model that leverages preclinical and clinical data."

"We are proud to present our science and mathematics and discuss how modeling and simulation approaches can impact programs in our partner's pipeline, in this case for a bispecific in oncology," said John Burke, PhD, Co-founder, President and CEO of Applied BioMath. "As therapies grow in complexity, systems pharmacology approaches are uniquely suited to help accelerate and de-risk programs, which ultimately help our partners develop better therapies for patients and reduce late stage attrition."

To learn more about Applied BioMath, visit www.appliedbiomath.com.

About Applied BioMath
Founded in 2013, Applied BioMath's mission is to revolutionize drug invention. Applied BioMath applies biosimulation, bioinformatics, clinical pharmacology, and software solutions 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 and software, visit www.appliedbiomath.com.

Applied BioMath and the Applied BioMath logo are registered trademarks of Applied BioMath, LLC.