MAL-PD Theory/Algorithm Guided Clinical Protocol Design for Computerized Data Analysis and Digital Conclusions in Drug Evaluations for Single Drugs and Combinations

• Published in: The Journal of pharmacology and experimental therapeutics Vol. 389; p. 96
• Main Authors: Chou, Ting-chao, Fu, Jianing, Chou, Joseph H., Lin, Shu-Fu, Alassane-Kpembi, Imourana, Chang, Taitsung, Wan, Xiao, Wong, Richard J., Fong, Yuman, Ulrich-Merzenich, Gudrun S., Shapiro, Theresa A.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.06.2024
• ISSN: 0022-3565
• DOI: 10.1124/jpet.096.131292

Abstract ID 131292 Poster Board 096 Mathematical system analysis on mass-action law (MAL) and enzyme model resulted in the derivation of over 300 reaction-rate equations, which can be deduced into unified general MAL-dynamics theories/algorithms for computer simulation of diagnostic plots: i. The Median-Effect Eq. (MEE) & (MEP) for “action” determines Dm (Median-effective-dose) for the potency of drugs or mass-entities and its dynamics (m value) for the shape of dose-effect-curve (DEC). ii. The Combination Index Eq (CIE) & (CIP) for “interactions” allows digitalization of synergism (CI<1), additive-effect (CI=1), and antagonism (CI>1), and iii. The Dose-Reduction Index Eq. (DRIE) & (DRIEP) for the “consequences of interactions”. The unified MAL-dynamics theory/algorithm of pharmacodynamics/bioinformatics (MAL-PD/BI) and the Minimum Two-dose Data Point Theory (MTDPT) of MAL-PD automatically add two default dose-data points (Dose zero and Dm) to all MAL-dynamics analysis, thus the basis for efficiency and cost-effectiveness for R&D. MEE/MEP allows the projection of optimal dose range, dose density, and protocol design in vitro, in vivo, and in clinical trials. The universal/unlimited applicability is due to all terms of Equations i-iii being dimensionless relativity ratios. (i.e., canceled out with ratio), thus independent of unit physical state, structure, and mechanism. All Equations i-iii are based on One, thus leading to the Unity of One Theory (UOT). To date, this MAL-PD/CI/BI dynamics/informatics has garnered over 25,000 citations in 23,000 papers, in 1,541 journals and 1,341 patents internationally, which attests to the significance and importance in all spectrum of R&D. This MAL-theory/algorithm allows a simple, efficient, Econo-green, and unified drug evaluations R&D. For single drugs, each requires about 6, 4, and 3 doses in vitro, in animal, and in clinical protocol design, respectively (at MAL-PD/MEE/MEP guided/designed dose range and density) for effects (at selected end-points and target/surrogate measurements). The drug combination evaluation follows the same guidelines, with the MAL-PD/CI being the most efficient diagonal constant-ratio combination scheme for all dose-dependent dynamic analyses, with automated quantitative computer simulation. This paper will illustrate specific MAL-PD/CI/BI examples for experimental planning, protocol design, data analysis, data entries, computer simulations, and computer printout reports. It is demonstrated that using two anticancer agents against xenograft tumors in nude mice (e.g., Taxotere, T-607, and their Combination) and anti-HIV agents in clinical trials (e.g., AZT, IFN, AZT+IFN), using only 10 dose-data-points (<70 mice and 36 patients, respectively), the MAL-PD/CI/BI method quantitatively determined potency of each drug and Combinations, and quantitatively determines synergism (CI<1) with PD-automated computer simulation. It is concluded that the MAL theory/algorithm-based Top-Down R&D approach is complimentary alternative to the traditional/conventional observation/statistics-based Bottom-Up R&D approach. However, using the same MAL fundamental principles, the MAL theory/algorithm provides unified and streamlined guidance to scientific R&D in biomedical sciences and beyond, including environmental, agricultural, marine, and food sciences. This work was partially supported by a Research Grant (T112) from the ACS, NIH Grant CA18856, CA05826, and CA27569.