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Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics
- Publication Year :
- 2024
-
Abstract
- '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
Details
- Language :
- English
- ISBNs :
- 9780443288746 and 9780443288753
- Database :
- eBook Index
- Journal :
- Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics
- Publication Type :
- eBook
- Accession number :
- 3698475