Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics
Original price was: $252.88.$148.75Current price is: $148.75.
Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics | 9780443288746, Chou, Ting-Chao
Author: Chou, Ting-Chao
Edition: 1
ISBN: 9780443288746
Release Date: 26-04-2024
Package Dimensions: 9.2 x 7.5 x 1.0 inches
Languages: English
Binding: Paperback
Number Of Pages: 438
Details: “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
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