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Applied BioMath, LLC Announces Participation at Immuno-Oncology Summit
CONCORD, Mass., July 29, 2019 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying systems pharmacology and mechanistic modeling, simulation, and analysis to accelerate and de-risk drug research and development, today announced their participation at the Immuno-Oncology Summit occurring August 5-9, 2019 in Boston, MA. John Burke, PhD, Co-Founder, President and CEO, Applied BioMath will present "Model Aided Drug Invention: In Silico Differentiation for bispecific targeting and developing systems platform models in I/O" at the conference Wednesday, August 7th at 10 a.m.
Model-aided drug invention (MADI) is a mathematical modeling and engineering approach to translational medicine that quantitatively integrates knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. In his presentation Dr. Burke will discuss case studies that explore integrating mathematical modeling to predict optimal drug properties targeting PD-1 and TIM3 in immuno-oncology for bispecific biologics and platform systems pharmacology models in I/O. The case studies highlight MADI efforts that have de-risked projects, accelerated the discovery and development of best-in-class therapeutics, and impacted critical decisions or provided deep biological insights in the continuum from preclinical to clinical research.
"We are very excited to present at the Immuno-Oncology Summit for the first time this year," said John Burke, PhD, Co-Founder, President and CEO, Applied BioMath. "This presentation establishes that developing and interrogating a systems pharmacology model provides early quantitative decision-making guidance for project teams, and we hope this resonates with attendees at the conference."
In addition to the presentation, Applied BioMath has two posters and a booth at the conference. The posters entitled "Development of a multiscale QSP model to characterize the tumor suppressive effects of a cytokine mRNA immunotherapy in a preclinical melanoma mouse model" and "A semi-mechanistic platform model to capture individual animal responses to checkpoint inhibitors in a syngeneic mouse model" highlight their recent collaborations.
For more information about Applied BioMath's upcoming events, visit www.appliedbiomath.com/news-resources/events.
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