“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
1. Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics - p. i 2. Cover - p. i 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Preface - p. ix 7. Abbreviations - p. xi 8. Acknowledgments - p. xiii 9. Chapter I A new alternative concept for cost-effective R&D: The MAL-dynamics/algorithms/digital informatics⊛ - p. 1 10. Chapter II General dynamics principle for experimental design of all dose-effect analysis and computer simulation⊛ - p. 39 11. Chapter III MAL-PD/CI approach for biomedical R&D in vitro and in animals⊛ - p. 65 12. Chapter IV Implementation of MAL-PD for Econo-Green R&D⊛ - p. 77 13. Chapter V Digital R&D approach to international FDA drug evaluation, clinical pharmacology, and clinical trial guidance⊛ - p. 83 14. Chapter VI The epothilone story: Experimental success and clinical failure⊛ - p. 95 15. Chapter VII MAL-PD advocacy: Public hearing, public comments and scientific recommendations⊛ - p. 113 16. Chapter VIII Consensus for international FDAs on definitions of “MAL-PD” and “Synergism”⊛ - p. 127 17. Chapter IX Historical, philosophical, and mathematical analysis: Why the MAL-PD approach and the traditional approach are opposite yet complementary⊛ - p. 133 18. A: The MAL theory-based “top-down” versus the experimental observation-based “bottom-up” for bio-R&D and clinical trials - p. 133 19. B: The inspiration and support from the visionary giants - p. 135 20. C: Nature's equilibrium ecosystem and interdisciplinary common basic principle from ancient to modern - p. 136 21. 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? - p. 141 22. E: Conversation with ChatGPT: Statements, informatics, errors, and this author's comments - p. 143 23. F: System, pattern, combinatorial, number theory, and new frontiers for further mathematical developments: The contraction of two-dimensional Pascal Triangle from the biological model - p. 152 24. G: The author rank-weighted triangle and algorithm for citation attribution in n-authored papers - p. 166 25. H: The perspectives of the MAL-BP/PD/CI informatics - p. 173 26. Chapter X Multidisciplinary examples of applications: Papers using the MAL-PD/BD/CI/BI theory/method⊛ - p. 181 27. Chapter XI Concluding remarks⊛ - p. 219 28. Postscript - p. 225 29. Summary - p. 229 30. Appendix I - p. 233 31. Appendix II - p. 247 32. Appendix III - p. 269 33. Appendix IV - p. 283 34. Appendix V - p. 315 35. Appendix VI - p. 317 36. Glossary and definitions - p. 409 37. Research supports - p. 417 38. Index - p. 419
“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
1. Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics - p. i 2. Cover - p. i 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Preface - p. ix 7. Abbreviations - p. xi 8. Acknowledgments - p. xiii 9. Chapter I A new alternative concept for cost-effective R&D: The MAL-dynamics/algorithms/digital informatics⊛ - p. 1 10. Chapter II General dynamics principle for experimental design of all dose-effect analysis and computer simulation⊛ - p. 39 11. Chapter III MAL-PD/CI approach for biomedical R&D in vitro and in animals⊛ - p. 65 12. Chapter IV Implementation of MAL-PD for Econo-Green R&D⊛ - p. 77 13. Chapter V Digital R&D approach to international FDA drug evaluation, clinical pharmacology, and clinical trial guidance⊛ - p. 83 14. Chapter VI The epothilone story: Experimental success and clinical failure⊛ - p. 95 15. Chapter VII MAL-PD advocacy: Public hearing, public comments and scientific recommendations⊛ - p. 113 16. Chapter VIII Consensus for international FDAs on definitions of “MAL-PD” and “Synergism”⊛ - p. 127 17. Chapter IX Historical, philosophical, and mathematical analysis: Why the MAL-PD approach and the traditional approach are opposite yet complementary⊛ - p. 133 18. A: The MAL theory-based “top-down” versus the experimental observation-based “bottom-up” for bio-R&D and clinical trials - p. 133 19. B: The inspiration and support from the visionary giants - p. 135 20. C: Nature's equilibrium ecosystem and interdisciplinary common basic principle from ancient to modern - p. 136 21. 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? - p. 141 22. E: Conversation with ChatGPT: Statements, informatics, errors, and this author's comments - p. 143 23. F: System, pattern, combinatorial, number theory, and new frontiers for further mathematical developments: The contraction of two-dimensional Pascal Triangle from the biological model - p. 152 24. G: The author rank-weighted triangle and algorithm for citation attribution in n-authored papers - p. 166 25. H: The perspectives of the MAL-BP/PD/CI informatics - p. 173 26. Chapter X Multidisciplinary examples of applications: Papers using the MAL-PD/BD/CI/BI theory/method⊛ - p. 181 27. Chapter XI Concluding remarks⊛ - p. 219 28. Postscript - p. 225 29. Summary - p. 229 30. Appendix I - p. 233 31. Appendix II - p. 247 32. Appendix III - p. 269 33. Appendix IV - p. 283 34. Appendix V - p. 315 35. Appendix VI - p. 317 36. Glossary and definitions - p. 409 37. Research supports - p. 417 38. Index - p. 419
