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| Michael B. Bolger, Simulations Plus and USC School of Pharmacy |
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Dr. Michael Bolger is the Founding Scientist and Director of Life Sciences at Simulations Plus, Inc., Lancaster, California. He obtained a B.A. in Biology and Chemistry from UC San Diego in 1973 and his Ph.D. in Pharmaceutical Chemistry from UC San Francisco in 1978. From 1978-1980 he was an NIH Postdoctoral Fellow in pharmacology at the UC San Diego School of Medicine.
For the next 23 years, he was a professor of Pharmaceutical Sciences at USC School of Pharmacy, Los Angeles, California and he retired from USC in the spring of 2004. During this period he developed an interest in the computational aspects of drug design and drug development. As a faculty member at USC School of Pharmacy, his research was supported by several NIH basic science research grants and he published over 50 peer-reviewed publications. From 1989-1991 he served as a US Food and Drug Administration National Science Advisor. He is Chair of the AAPS Data Mining Focus Group, a member of the editorial board of Pharmaceutical Research and AAPS PharmSci, and has served as a reviewer for numerous scientific publications. He is currently Adjunct Associate Professor of Pharmaceutical Sciences at USC.
From 1987-1993, simultaneous with his academic duties, he was a founder and Director of Medicinal Chemistry at CoCensys Inc. There, he studied the chemistry and use of novel neuroactive steroids for treatment of anxiety, epilepsy, and sleep disorders. Drug candidates emanating from seven of Dr. Bolger’s patents have been tested in Phase I and II clinical trials for petite mal epilepsy, sleep disorders, and migraine.
Currently, he directs a team of scientist / programmers at Simulations Plus, Inc. (Lancaster, CA) in the development of software programs (ADMET Predictor, GastroPlus, ADMET Modeler, DDDPlus, and MembranePlus) for estimation of biopharmaceutical properties, simulations of absorption and bioavailability, automated generation QSP/AR model building, in vitro dissolution, and cell culture permeability simulation. He was elected to the rank of Fellow of the American Association for the Advancement of Science in 1996.
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Integration of Early ADME using Property Estimation and PBPK Simulation
Michael B. Bolger, Simulations Plus and USC School of Pharmacy
Purpose: To introduce methods and describe validation results for the integration of in silico and in vitro data in early discovery.
Introduction: A wide variety of software tools are available for biopharmaceutical property estimation related to absorption, distribution, metabolism, elimination, and toxicity (ADMET). These in silico methods are supplemented by in vitro measurement of log P, solubility, Caco-2 Papp, fraction unbound in plasma, and metabolic stability. We will present methods and validation results for integration of all of this data in a database that is linked to whole body physiologically-based (PBPK) simulation of ADME.
Methods: By using estimated and experimental values for biopharmaceutical properties, fraction absorbed (Fa) and fecal excretion were simulated in silico using GastroPlus™. Bioavailability (Fb) and Cp vs. time profiles were simulated with knowledge of: intrinsic clearance, volume of distribution (Vd) and plasma protein binding (fup). Vd was estimated by using physiologically-based pharmacokinetics linked to a tissue composition model parameterized in silico using just log P and fup. In vitro experiments were required for estimation of clearance and bioavailability.
Results: We also found that the simulation model was able to correctly predict the dissolution and plasma concentration vs. time profile for poorly soluble drugs. We were able to predict the bioavailability for drugs with high first pass extraction using PBPK. Finally, we were able to correctly predict the non-linear dose dependence for substrates of influx transporters and for talinolol which is an effluxed substrate for Pgp.
Conclusions: Integration of biopharmaceutical properties from in silico estimation and in vitro experiments with a mechanistic, physiologically-based gastrointestinal simulation is a valuable predictive tool in pharmaceutical discovery and development.
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in silico technology in drug discovery and development
Michael B. Bolger, Simulations Plus and USC School of Pharmacy
Introduction:
in silico models of biopharmaceutical, pharmacokinetic, and physiological properties related to absorption, distribution, metabolism, excretion, and toxicity (ADMET) have become a valuable tool for reducing the number of experiments that need to be conducted in order to find drug candidates with less chance of failure during development. Application of the estimated properties and/or measured in vitro properties in a physiologically-based gastrointestinal simulation to predict fraction absorbed, bioavailability, and Cp vs. time profiles in discovery, development, pre-clinical, and clinical phases of pharmaceutical development can be considered to be a means of integrating the various calculated and measured properties to enhance decision making.
This workshop is intended to provide the attendees with a lecture and demonstration of in silico tools for drug discovery and development. The workshop will present general information about publicly available sources of data for model building, concepts and schematic outlines of model building methods, and knowledgeable interpretation and analysis of results.
Workshop Outline:
* Introduction to properties and models of interest in early ADMET (log P, log D, pKa, native solubility, solubility in buffer, solubility in bio-relevant media, pH dependence of solubility, effective permeability, apparent permeability, diffusivity, dissolution rate, fraction absorbed, bioavailability, volume of distribution, clearance, plasma protein binding, carcinogenicity, mutagenicity, maximal recommended therapeutic dose, and hERG K+ channel inhibition.
* Overview of QSPR model building methods.
* Calculation of properties for a single molecule and databases of drugs with known fraction absorbed or human effective permeability.
* Integration of biopharmaceutical properties and formulation factors by using gastrointestinal simulation and physiologically-based pharmacokinetics. (parameter sensitivity analysis and virtual clinical trials).
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