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Setting course for a translational pharmacology and a predictive toxicology based on the numerical probability of

Jose D Suarez-Torres¹, Carlos E Ciangherotti², Camilo A Orozco³

¹Department of Pharmacy, Faculty of Sciences, Universidad Nacional de Colombia, Bogotá D.C., Colombia; Department of Toxicology, Faculty of Medicine, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.

Environmental Toxicology and Pharmacology

|September 8, 2022

Abstract:

For a significant share of the chemicals, current bioassays mispredicted the outcomes in the reference methods they simulate. For any drug or chemical, and depending on the regulatory or corporate situation, three different approaches calculate the numerical probability by which agreement (or discrepancy) can be statistically expected between (1) the result of a predictive bioassay, and (2) the outcome on its reference method. If such concordance is expected with enough confidence based on a sufficient percentage probability, then specific results from that bioassay can be considered as correctly predictive. The statistical approaches analyzed in this article assist in valuable tasks, including (1) a better translation of the clinical relevance (or insignificance) of specific preclinical findings; (2) waiving unnecessary animal testing (or any other unpredictive testing; e.g., a given in vitro bioassay), and (3) in advancing only the most promising candidates in the pharmaceutical, pesticide, or chemical development process.

Keywords:

Bayesian forecasting Predictive toxicology Predictive values approach Probability of clinical relevance Probability of preclinical veracity Translational pharmacology

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