Applied BioMath (www.appliedbiomath.com), the industry-leader in applying mechanistic modeling, simulation, and analysis to accelerate and de-risk drug research and development, today announced their participation at PharmSci 360 occurring November 4-7, 2018 in Washington, D.C.
Joshua Apgar, PhD, CSO and Co-Founder, Applied BioMath, is a featured presenter during the short course "Quantitative Systems Pharmacology: Why, How and When in Drug Discovery and Development" occurring Sunday, November 4, 2018 from 9:00 AM – 1:00 PM. In this short course, Dr. Apgar will present a talk titled "QSP in Drug Discovery: Target Identification and Lead Candidate Selection/Optimization" from 9:45-10:15 AM, where he will discuss how modeling and simulation can impact critical decision points throughout drug discovery.
Applied BioMath will also partake in two poster sessions at the conference. Fei Hua, PhD, Senior Director, Modeling & Simulation and Clinical Pharmacology, will present "Inferring Target Occupancy from Fitting Nonlinear-PK Data with Mechanistic PKRO Model for Pembrolizumab" on Monday, November 5, 2018 from 1:30-2:30 PM at poster number M1330-05-033. This poster was selected by AAPS as the 2018 Best Abstract Award. Additionally, Dr. Hua will present "Drug-Induced TMDD: A Novel Class of PK Models for Immune-Stimulating Therapies" on Wednesday November 7, 2018 from 12:30-1:30 PM at poster number W1230-05-033.
"I look forward to discussing QSP approaches within drug discovery and development with the attendees at PharmSci 360," said Joshua Apgar, PhD, CSO and Co-Founder, Applied BioMath. "The presentation and our posters highlight multiple examples of how QSP models can inform critical decisions, and how performing these analyses early can de-risk programs, accelerate timelines, and enable best-in-class therapeutics."
In addition to the presentation and poster sessions, attendees can visit Applied BioMath throughout the duration of the conference at booth #832 within the Clinical Pharmacology neighborhood.
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.