Dr. John Burke, CEO of Applied BioMath, will present "Quantitative Modeling and Simulation Approaches: Driving Critical Decisions from Research through Clinical Trials" at the Broad Institute at 415 Main Street in Cambridge on Thursday, January 19th. The talk will begin at 6pm in the auditorium and be followed by refreshments and networking at Meadhall at 4 Cambridge Center starting around 7pm. Please RSVP for the meeting.
Abstract: Quantitative Systems Pharmacology (QSP) is a mathematical modeling and engineering approach to translational medicine that aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. The goal of QSP modeling is “to understand, in a precise, predictive manner, how drugs modulate cellular networks in space and time and how they impact human pathophysiology [1].” In doing so, QSP approaches de-risk projects, accelerate the development of best in class therapeutics, and reduce late stage attrition rates. This results is helping industry save money, accelerate timelines, and make better therapeutics, ultimately improving patients’ lives. In the five years since the NIH QSP Working Group met last on this topic, progress has been made to advance this science and to integrate QSP approaches in the drug discovery and development process in industry. Here several case studies will be shown that highlights examples of QSP efforts that have accelerated the discovery and development of best-in-class therapeutics, and impacted critical decisions, in the continuum from preclinical exploration to clinical research. Examples include: providing biological understanding, impacts on new target proposals, lead generation, clinical candidate selection, IND support, and clinical trial go/no go decisions from industry.
1. Sorger, PK, et al. Quantitative and Systems Pharmacology in the Post-genomic Era: New Approaches to Discovering Drugs and Understanding Therapeutic Mechanisms. An NIH White Paper, QSP Workshop Group R. Ward, Editor. 2011.
Dr. Burke is CEO, President and Co-founder of Applied BioMath. He earned his PhD in Applied Mathematics from Arizona State University, completed a senior postdoctoral fellowship in Biological Engineering at Massachusetts Institute of Technology, and was Co-Scientific Director of the Cell Decision Process Center at Harvard Medical School, a NIH Center of Excellence. While at MIT and HMS he provided systems consulting support for large and small pharma and biotechs (e.g., AstraZeneca, Pfizer, Momenta), and software companies (e.g., Jacobian and MathWorks). Next he was at Merrimack Pharmaceuticals as a Senior Mathematical Biologist. He then was Global Head of Systems Biology and Pharmacology at Boehringer Ingelheim (BI). He was responsible for starting, implementing, scaling, and managing the worldwide strategy, portfolio, and efforts of BI’s systems initiatives. In a span of five years his group supported over 120 milestone transitions and major decisions from new target stage, lead generation, clinical candidate selection, through clinical trial support. Project indications and platforms included Oncology, Metabolic Disease, CNS, Cardiovascular, Respiratory, Infectious Disease, Inflammation and Immunology for large molecules, fixed dose combinations, ADC, and cell therapies. He is presently an Adjunct Professor at University of Massachusetts, Lowell, developing a QSP course at Harvard Medical School to be taught in the Spring of 2017, an industry advisor for the NIH/NCATS “Translational Center of Tissue Chip Technologies” and the DARPA - MIT Human on a Chip Grant, and an advisor to the Mathematics Department, University of Massachusetts, Lowell
Abstract: Quantitative Systems Pharmacology (QSP) is a mathematical modeling and engineering approach to translational medicine that aims to quantitatively integrate knowledge about therapeutics with an understanding of its mechanism of action in the context of human disease mechanisms. The goal of QSP modeling is “to understand, in a precise, predictive manner, how drugs modulate cellular networks in space and time and how they impact human pathophysiology [1].” In doing so, QSP approaches de-risk projects, accelerate the development of best in class therapeutics, and reduce late stage attrition rates. This results is helping industry save money, accelerate timelines, and make better therapeutics, ultimately improving patients’ lives. In the five years since the NIH QSP Working Group met last on this topic, progress has been made to advance this science and to integrate QSP approaches in the drug discovery and development process in industry. Here several case studies will be shown that highlights examples of QSP efforts that have accelerated the discovery and development of best-in-class therapeutics, and impacted critical decisions, in the continuum from preclinical exploration to clinical research. Examples include: providing biological understanding, impacts on new target proposals, lead generation, clinical candidate selection, IND support, and clinical trial go/no go decisions from industry.
1. Sorger, PK, et al. Quantitative and Systems Pharmacology in the Post-genomic Era: New Approaches to Discovering Drugs and Understanding Therapeutic Mechanisms. An NIH White Paper, QSP Workshop Group R. Ward, Editor. 2011.
Dr. Burke is CEO, President and Co-founder of Applied BioMath. He earned his PhD in Applied Mathematics from Arizona State University, completed a senior postdoctoral fellowship in Biological Engineering at Massachusetts Institute of Technology, and was Co-Scientific Director of the Cell Decision Process Center at Harvard Medical School, a NIH Center of Excellence. While at MIT and HMS he provided systems consulting support for large and small pharma and biotechs (e.g., AstraZeneca, Pfizer, Momenta), and software companies (e.g., Jacobian and MathWorks). Next he was at Merrimack Pharmaceuticals as a Senior Mathematical Biologist. He then was Global Head of Systems Biology and Pharmacology at Boehringer Ingelheim (BI). He was responsible for starting, implementing, scaling, and managing the worldwide strategy, portfolio, and efforts of BI’s systems initiatives. In a span of five years his group supported over 120 milestone transitions and major decisions from new target stage, lead generation, clinical candidate selection, through clinical trial support. Project indications and platforms included Oncology, Metabolic Disease, CNS, Cardiovascular, Respiratory, Infectious Disease, Inflammation and Immunology for large molecules, fixed dose combinations, ADC, and cell therapies. He is presently an Adjunct Professor at University of Massachusetts, Lowell, developing a QSP course at Harvard Medical School to be taught in the Spring of 2017, an industry advisor for the NIH/NCATS “Translational Center of Tissue Chip Technologies” and the DARPA - MIT Human on a Chip Grant, and an advisor to the Mathematics Department, University of Massachusetts, Lowell
BAGIM is sponsored by Dassault Systemes, DNASTAR, LabAnswer, Schrodinger, Silicon Therapeutics, Acellera, Acpharis, Cambridge Crystallographic Data Centre, Chemical Computing Group, Cresset, Cyrus Biotechnology, Dotmatics, Optibrium, and Scilligence,
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