Applied BioMath (www.appliedbiomath.com), the industry-leader in applying systems pharmacology and mechanistic modeling, simulation, and analysis to de-risk drug research and development, today announced their fourth annual Quantitative Systems Pharmacology (QSP) Summit will occur May 20-21, 2020 at the MIT Samberg Conference Center in Cambridge, MA. In its fourth year, the QSP Summit is a free, two-day conference featuring talks from key industry and academic researchers, a poster session with awards, and networking time with peers. This year’s speakers include:
- Panagiota Foteinou, PhD, Principal QSP Scientist, Sanofi
- Sergio Iadevaia, PhD, Scientific Director, QSP Pharmacometrics and Data Analysis, Takeda
- Kathryn Miller-Jensen, PhD, Associate Professor of Biomedical Engineering, Yale University
- Michael Rosenblatt, MD, Chief Medical Officer, Flagship Pioneering
- Samuel Isaacson, PhD, Associate Professor of Mathematics and Statistics, Boston University
- Theresa Yuraszeck, PhD, Associate Director, CSL Behring
- Bo Zheng, PhD, Associate Director, Clinical Pharmacology, CSL Behring
- Simon Zhou, PhD, Executive Director, Clinical Pharmacology and Translational Development, Celgene
“We are excited to host the QSP Summit for the fourth time this year,” said John Burke, PhD, Co-founder, President and CEO, Applied BioMath. “Year over year we see growth at this event from the number of attendees, speakers, and poster presentations. We look forward to another great event this year; bringing industry and academic participants together to discuss applying QSP in drug research and development.” For more information about the QSP Summit, visit www.appliedbiomath.com/quantitative-systems-pharmacology-summit-2020. For more information about all of Applied BioMath’s events, visit https://www.appliedbiomath.com/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.