Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics
- 1st Edition - April 9, 2024
- Author: Ting-Chao Chou
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 8 8 7 4 - 6
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 8 8 7 5 - 3
“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… Read more
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Request a sales quote“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 insights 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 still a complementary alternative to the observation/statistics-based “Bottom-Up” traditional approach in R&D
Researchers and professionals in the fields of bioinformatics, computational biology, systems biology, and precision medicine
- Cover image
- Title page
- Table of Contents
- Front Matter
- Copyright
- Preface
- Abbreviations
- Acknowledgments
- Chapter I A new alternative concept for cost-effective R&D: The MAL-dynamics/algorithms/digital informatics
- Abstract
- A Challenges from complexity and diversity and the MAL-solutions
- B A complementary alternative new approach to the traditional approach for biomedical R&D, drug evaluations, and beyond
- C MAL applicability and implementations
- D The PK/PD issues
- References
- Chapter II General dynamics principle for experimental design of all dose-effect analysis and computer simulation
- Abstract
- A The principle and process for drug evaluation: Dose and effect analysis
- B Two different anti-HIV clinical trials: Protocol design and data analysis
- C Clinical trials of AZT + 3TC based on the traditional statistical approach
- D Comparisons of two clinical trials: AZT + 3TC vs AZT + IFN
- E Efficiency, cost-effectiveness, and integrative computerized automation
- F Preclinical and clinical trials: Definitions of “additive effect,” “synergism,” and “antagonism”
- References
- Chapter III MAL-PD/CI approach for biomedical R&D in vitro and in animals
- Abstract
- A Sample size, efficiency, and cost-effectiveness
- B Significance of the MAL-PD approach
- C Illustration of drug combination in vitro using MAL-PD/CI method
- D Illustration of drug combination in animals using MAL-PD/CI method
- E Application of MAL-PD/CI method in organ transplantation studies
- References
- Chapter IV Implementation of MAL-PD for Econo-Green R&D
- Abstract
- A Availability of computer software for automated MAL-PD/CI/BI
- B Comparisons and ranking of candidate drugs and biosimilars in vitro and in vivo using the same MAL-PD principle
- C Standardized drug evaluations for single drugs using the median-effect principle of MAL-PD
- References
- Chapter V Digital R&D approach to international FDA drug evaluation, clinical pharmacology, and clinical trial guidance
- Abstract
- A The observatory statistical PK principle plays an important role in FDA policy and priority
- B Modernization of drug evaluation guidance and guidelines
- C Why FDA drug evaluation is so relevant to a pharmacologist
- D New avenues for integrated and streamlined drug evaluation
- E The international FDA guidance and drug evaluation guidelines need an update and modernization
- F The current uncertainty, ambiguity, and confusion in drug R&D and regulations
- References
- Chapter VI The epothilone story: Experimental success and clinical failure
- Abstract
- A A pharmacologist and theoretical biologist for life
- B Epothilones: The interaction between chemists and pharmacologists
- C Anticancer epothilone preclinical studies as examples
- D Major MAL-PD findings of epothilones
- E A clinical trial study of isofludelone (KOS-1803)
- F A review of the failure of the isofludelone [KOS-1803] clinical trial
- References
- Chapter VII MAL-PD advocacy: Public hearing, public comments and scientific recommendations
- Abstract
- A Public meetings and public hearings at US FDA
- B Public comments to FDA
- C Presentation on MAL-PD theory and applications at CPIM, OTS, FDA
- D The problem of undefinable vague “models”
- E Consolidation and definition of precision medicine, translational medicine, and digital biology
- References
- Chapter VIII Consensus for international FDAs on definitions of “MAL-PD” and “Synergism”
- Abstract
- A The role of drug evaluation from international FDAs on drug evaluation
- B The International Council for Harmonization on “PD” and “synergism” for R&D
- C Different thinking for the clinical trial protocol design and data analysis/simulation
- References
- Chapter IX Historical, philosophical, and mathematical analysis: Why the MAL-PD approach and the traditional approach are opposite yet complementary
- Abstract
- A The MAL theory-based “top-down” versus the experimental observation-based “bottom-up” for bio-R&D and clinical trials
- B The inspiration and support from the visionary giants
- C Nature's equilibrium ecosystem and interdisciplinary common basic principle from ancient to modern
- D Artificial intelligence, cloud computing, computer learning, open AI, generative AI, and ChatGPT are the bottom-up platforms. Eventual convergence and integration with the nature's top-down algorithm?
- E Conversation with ChatGPT: Statements, informatics, errors, and this author's comments
- F System, pattern, combinatorial, number theory, and new frontiers for further mathematical developments: The contraction of two-dimensional Pascal Triangle from the biological model
- G The author rank-weighted triangle and algorithm for citation attribution in n-authored papers
- H The perspectives of the MAL-BP/PD/CI informatics
- References
- Chapter X Multidisciplinary examples of applications: Papers using the MAL-PD/BD/CI/BI theory/method⊛
- Abstract
- A Applications MAL-PD and CI in cancer-related research
- B Applications in antimicrobial research
- C Applications in basic biomedical sciences (2020–23)
- D MAL-PD theory/method of applications in different disciplines
- E Applications in immunology and organ transplantation
- F Philosophical propositions, AI, conceptual discussions and theoretical biology
- G Early theoretical, physical, biophysical, biochemical, and elementary particle studies
- H Other theories and concepts of non-MAL-PD approach, computer learning and artificial intelligence
- References
- Chapter XI Concluding remarks
- References
- Postscript
- Summary
- Appendix I
- Appendix II
- Appendix III
- Appendix IV
- Appendix V
- Appendix VI
- Glossary and definitions
- References
- Research supports
- Conflict of interest
- Disclaimer/Publisher’s note
- Declarations
- Index
- No. of pages: 438
- Language: English
- Edition: 1
- Published: April 9, 2024
- Imprint: Academic Press
- Paperback ISBN: 9780443288746
- eBook ISBN: 9780443288753
TC
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-index 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
Affiliations and expertise
PD Science LLCRead Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics on ScienceDirect