Applied BioMath, LLC Announces Webinar on using Systems Pharmacology for First-in-Human Dose Predictions
CONCORD, Mass., Sept. 7, 2018 /PRNewswire/ -- 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 upcoming webinar titled "A Lipid Nanoparticle Quantitative Systems Pharmacology (QSP) Case Study". The webinar airs live Wednesday, September 12, 2018 at 2p.m. ET / 11a.m. PT.
In this webinar, Pratap Singh, PhD, Director of Pharmacometrics and Quantitative Clinical Pharmacology, Alexion Pharmaceuticals, will present a QSP case study which assesses a lipid nanoparticle to treat Crigler-Najjar Syndrome Type 1. This case study is based on work performed by Applied BioMath and Alexion Pharmaceuticals (CPT Pharmacometrics Syst. Pharmacol. (2018) 7, 404-412). In this project, a QSP model was developed to support translation from preclinical to clinical studies, and first-in-human studies. The model also helped gain a deeper understanding of the mechanisms of hUGT1A1-modRNA and provided first-in-human dose predictions.
"Through using a QSP model, we were able to integrate preclinical data from studies in rats with known physiological differences between human and rat to provide a more comprehensive understanding of the mechanisms of hUGT1A1-modRNA," said Joshua Apgar, PhD, Co-Founder and CSO, Applied BioMath. "The model also helped inform recommended safe starting dose and impacted clinical strategy in terms of patient populations for Ph1."
A QSP model-based approach is more likely to provide greater predictive power than the empirical PK/PD approaches because QSP aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. QSP models provide quantitative guidance throughout R&D and are often leveraged to help optimize and accelerate lead generation, prioritize experiments, de-risk clinical candidate selection, and help with Ph1 & Ph2 predictions.
This webinar is ideal for scientists and decision makers in R&D who want to learn more about how to leverage QSP to provide quantitative guidance for their drug discovery and development.
To register for this webinar, visit https://pages.questexweb.com/AppliedBiomath-Registration-091218.html?source=appliedbiomath. 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.
Press contact:
Kristen Zannella
kristen.zannella@appliedbiomath.com
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SOURCE Applied BioMath, LLC
