LINCOLN, Mass., March 22, 2017 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling to drug research and development, today announced the latest line-up of speakers for QSP Day 2017. QSP Day 2017 is a day full of presentations, posters, and networking opportunities with the quantitative systems pharmacology (QSP) community. The focus is to learn about how mechanistic and mathematical modeling is de-risking and accelerating drug research and development.
The event will occur on Thursday April 6, 2017 from 9am to 5pm at MIT's Samberg Conference Center. Featured speakers include:
- Bruce Gomes, PhD, Executive Director, Pharmacometrics, Novartis
- Raj Kamath, PhD, Senior Principal Research Scientist, AbbVie
- Peter Sorger, PhD, Head of Therapeutic Sciences, Professor of Systems Biology at Harvard University
- Collin D. Edington, PhD, Postdoctoral Research Associate, Linda Griffith Lab, MIT
Seating is limited. Register today at www.appliedbiomath.com to reserve your spot! If you have a poster to share, abstract submission is also currently open. Three abstracts will be invited to give a 15-min presentation during the conference. Cash prizes are available to top student and post-doc posters.
"With the steep rise of mathematical modeling in drug R&D, it's as important as ever for us to stay networked as a community to share successes and challenges. Our QSP seminar series has led this effort for the past three years and we look forward to QSP Day 2017 as an extension of that effort!"
Dr. John Burke, PhD, Co-Founder, President, and CEO of Applied BioMath
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.
SOURCE Applied BioMath