Applied BioMath, LLC Announces Collaboration with Revitope for Mechanistic PK/PD Modeling in Solid Tumors

On July 10, 2018 Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling, simulation, and analysis to de-risk and accelerate drug research and development, reported a collaboration with Revitope for an in-vitro and human mechanistic PK/PD modeling of Revitope’s bispecific T Cell Engaging Antibody Circuits (TEAC) targeting solid tumors (Press release, Applied BioMath, JUL 10, 2018, View Source [SID1234633659]). "TEAC are designed to increase tumor specificity and launch an immune activation only when bound to the cancer cell surface. This innovative engineering approach has the potential to unleash potent immune responses that are focused entirely on the tumor," said Werner Meier, CSO and acting CEO of Revitope Oncology. "Our goal in this collaboration is to leverage Applied BioMath’s modeling and analyses capabilities to identify TEAC drug properties that drive the potential for a better therapeutic index and ideally more efficacy in immuno-oncology."

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Applied BioMath employs a rigorous fit-for-purpose model development process, referred to as Model-Aided Drug Invention (MADI), which aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. Their MADI approach employs proprietary algorithms and software that were designed specifically for mechanistic PK/PD modeling. "Our mechanistic modeling approach allows our collaborators to assess the feasibility of their therapeutic much more quickly than if they were to rely on experiments alone," said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "They’ll be able to quickly answer strategic questions about the ideal properties for their therapeutic concept and help accelerate development in Lead Generation and by prioritizing experiments, thus helping them get into the clinical faster and for less money with potentially a BIC therapeutic, giving themselves a much higher chance of clinical success and maximizing R&D ROI."