Mathematical Prediction of the Efficacy of Medicinal Products in Preclinical Studies

Generally, preclinical studies of medicines conducted in accordance with national and international regulatory recommendations allow minimising the risks of detecting serious adverse events in patients at the stage of clinical trials. Nevertheless, current analytical trends motivate the development of new prognostic approaches aimed at improving the reliability and accuracy of safety assessments. The aim of this study was to develop and test methodological approaches to comprehensive preclinical assessment of the key risk factors associated with the use of medicinal products in humans and to mathematical prediction of the corresponding benefits and risks. Materials and methods: the study combined information analysis and statistics; it used consolidated preclinical data on the protective properties of fabomotizole and national and international regulatory documents describing the principles and methods of evidence-based medicine, in particular, Bayesian statistics and prognostic research methods. Results: The article presents mathematical approaches developed to confirm the statistical reliability and prognostic significance of the results of preclinical assessment of the safety of medicines, based on Bayesian statistics, in particular, the concepts of weight of evidence (WoE), information value (IV), and normalised density (ND). Depending on the volume of the evaluated data, the WoE can be used to determine the weight of evidence of single variables, as well as entire groups of variables from individual tests or whole test panels, considered in the studies of general toxic effects, reproductive toxicity, genotoxicity and other studies characterising the condition of vital organs when evaluating the safety of medicines. Conclusions: The developed methodology allows evaluating the entire volume of information obtained in preclinical studies of medicinal products. The criteria in the form of WoE and IV in preclinical safety assessment of medicines can be used to estimate the benefits and risks of using medicines, including the products developed specifically for children and pregnant women.