Translating Molecules into Medicines ― Cross-functional Integration at the Drug Discovery-development Interface
商品資訊
系列名:Aaps Advances in the Pharmaceutical Sciences
ISBN13:9783319500409
出版社:Springer Verlag
作者:Shobha N. Bhattachar (EDT); John S. Morrison (EDT); Daniel R. Mudra (EDT); David M. Bender (EDT)
出版日:2017/05/03
裝訂:精裝
規格:23.5cm*15.5cm (高/寬)
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作者簡介
David M. Bender is a Senior Research Scientist in Small Molecule Design and Development at Eli Lilly and Co. He received a B.S in chemistry from Miami University and an M.S. in organic chemistry from Colorado State University where he conducted research into the design and synthesis of novel antibacterial agents. He joined Eli Lilly and Co. in 1998 as a synthetic organic chemist in Discovery Chemistry Research. In 2009, he joined the Product Research and Development organization, where he has focused on formulation development, small molecule developability, absorption modeling and alternate drug delivery. Mr. Bender is currently a group leader in the Product Design and Developability group, and is responsible for overseeing the design and manufacture of clinical drug product for small molecules entering Lilly’s development pipeline.
Daniel R. Mudra is Director of ADME at Eli Lilly and Company. He earned his B.S. from The University of Dayton studying pharmacokinetic/pharmacodynamic effects of drug-impregnated implants and an M.S. from Loyola University Chicago investigating the biochemical regulation of the p38 kinase pathway. He earned his doctorate in Pharmaceutical Chemistry from The University of Kansas developing in situ and computational models of absorption studying the effects of excipients on permeability, metabolism and transport. Dr. Mudra began his industrial research career at XenoTech, LLC and has published on models of P450 induction and inhibition, drug absorption and PK. Since joining Lilly, he has contributed to projects from target identification to clinical development across a variety of therapeutic areas. He leads in the incorporation of mechanistic and physiologically based PK modeling including the use of molecular attributes to predict human clearance pathways.
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