Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics (ePub)
(Sprache: Englisch)
"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...
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"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
. 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
Autoren-Porträt von Ting-Chao Chou
Born in Taiwan, Ting-Chao (David) Chou received his Ph.D. in Pharmacology from Yale University and completed his Post-Doctoral Fellowship at Johns Hopkins University School of Medicine. He joined Memorial Sloan-Kettering Cancer Center (MSKCC) in New York and became a Member and Professor of Pharmacology at Cornell University Graduate School of Medical Sciences in 1988. He retired from MSKCC in 2013 and founded PD Science LLC. Professor Chou was elected to the Membership of The Johns Hopkins Society of Scholars, induced by the President of JHU on April 8, 2019, among 16 national and international inductees. Dr. Chou's published 375 papers have garnered over forty thousand hundred citations with an h-ndex of 75 and i10-index of 290. He is the inventor/co-inventor of 40 U.S. patents. Currently, he advocates for MAL-based digital biomedical R&D for translational medicine bioinformatics (BI) to provide a complementary alternative basic framework to the traditional statistics-based R&D
Bibliographische Angaben
- Autor: Ting-Chao Chou
- 2024, 200 Seiten, Englisch
- Verlag: Elsevier Science & Techn.
- ISBN-10: 0443288755
- ISBN-13: 9780443288753
- Erscheinungsdatum: 09.04.2024
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- Größe: 61 MB
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