Author : Ting-Chao Chou
Publisher : Elsevier
ISBN 13 : 0443288755
Total Pages : 440 pages
Book Rating : 4.53/5 ( download)
Book Synopsis Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics by : Ting-Chao Chou
Download or read book Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics written by Ting-Chao Chou and published by Elsevier. This book was released on 2024-04-09 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics provides a comprehensive overview and update of the mass-action law-based unified dose-effect biodynamics, pharmacodynamics, bioinformatics, and the combination index theorem for synergy definition (MAL-BD/PD/BI/CI). Contents advocate the fundamental MAL-PD/BI/CI/BI principle for biomedical R&D, clinical trials protocol design computerized data analysis, illustrates the MAL-dynamics theory with sample analysis, and includes data entry and automated computer report print-outs. In 11 sections “Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics leads the reader from an introduction and overview, to trial protocols and MAL-PD/CI approach for biomedical R&D in vitro and in animals. It describes the current Landscape of International FDA Drug Evaluation, Clinical Pharmacology, and Clinical Trials Guidance. This is a valuable resource for biomedical researchers, healthcare professionals, and students seeking to harness the power of data informatics in precision medicine. • gives insight into that index equation (DRIE) that digitally determines how many folds of dose-reduction is needed for each drug in synergistic combinations • provides a comprehensive overview and update of mass-action law-based unified bioinformatics, dose effect biodynamics, pharmacodynamics, and the combination index theorem for synergy definition (MAL-BD/PD/BI/CI) • describes how the MAL theory/algorithm-based “Top-Down digital approach is the opposite and yet is a complementary alternative to the observation/statistics-based “Bottom-Up traditional approach in R&D