Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced their participation in an upcoming quantitative systems pharmacology (QSP) event hosted by the Pharmaceutical and BioScience Society on September 29, 2017 in Boston, MA. Applied BioMath is the sole major sponsor of the day-long event as well as a presenter of two case studies in immuno-oncology and osteoarthritis.
Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath, will present two case studies, one highlighting an example of integrating systems modeling to predict optimal drug properties targeting PD-1 and TIM3 in immuno-oncology for bispecific biologics and fixed dose combinations, and a second showing QSP approaches to determine best in class properties for targeted anabolic growth factor to arthritic joints.
“Our proprietary QSP modeling approach has a proven track record of helping biotechnology and pharmaceutical companies better understand their drug candidate’s mechanism of action in the context of human disease mechanisms,” said Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath. “These case studies are just two of many examples we have where our participation in the project has de-risked projects, accelerated the discovery and development of best-in-class therapeutics, and impacted critical decisions, in the continuum from preclinical exploration to clinical research.”
Immediately prior to this event, Dr. Burke will present at the 8th Annual World Bispecific Summit in Boston, MA. Additionally, Dr. Burke will present a variety of case studies at the American Conference of Pharmacometrics (AcoP) October 15-18, 2017 in Ft. Lauderdale, Florida. For more information on any of these events, please visit www.appliedbiomath.com/events.
About Applied BioMath
Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, helps biotechnology and pharmaceutical companies answer complex, critical Go/No-go decisions in R&D. Applied BioMath leverages biology, proprietary mathematical modeling and analysis technology, high-performance computing, and decades of industry experience to help groups better understand their candidate, its best-in-class parameters, competitive advantages, and the best path forward. Our involvement shortens project timelines, lowers cost, and increases the likelihood of a best-in-class drug. We provide clarity to complex situations, answer otherwise unanswerable questions, and our approach, when validated in the clinic, is 10x more accurate than traditional methodologies.
Applied BioMath and the Applied BioMath logo are trademarks of Applied BioMath, LLC.