CONCORD, Mass., March 20, 2018 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling, simulation, and analysis to de-risk drug research and development, today announced their participation at the 4th annual ICI Boston Summit being held March 19-21, 2018 in Boston, MA.
John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath will present a talk titled "Predicting marketed PD-1 dosing and optimal PD-1 x TIM-3 dual targeting approaches in immuno-oncology" on Tuesday, March 20, 2018 at 9:30 a.m. In this presentation, Dr. Burke will present an example of how interrogating a systems pharmacology model of the co-modulation inhibitory receptors PD-1 and TIM-3 in immuno-oncology helped to assess risk by performing an in silico differentiation for a bispecific vs. FDC. He will also analyze why Bristol-Myers Squibb and Merck's anti-PD-1s therapeutic antibodies have similar dosing regimens when their affinities differ by two orders of magnitude, and provide predictions of the best-in-class profile for a PD-1 and TIM-3 dual antagonist biologic(s).
"We are very excited to present at the ICI Boston Summit for the first time this year," said John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. "This presentation establishes that developing and interrogating a systems pharmacology model provides early quantitative decision making guidance for project teams."
Applied BioMath utilizes its Model-Aided Drug Invention (MADI) approach to de-risk projects, accelerate the discovery and development of best-in-class therapeutics, and impact critical decisions in the continuum from preclinical exploration to clinical research. MADI leverages mechanistic pharmacokinetic and pharmacodynamic (PK/PD) and systems pharmacology which quantitatively integrates knowledge about therapeutics with an understanding of mechanism of action in the context of human disease mechanisms.
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 Model-Aided Drug Invention (MADI) 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