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.

1. Taube AA, Romanov BK Expert evaluation of prognostic criteria for non-clinical trials when registering medicinal products for medical use. Vestnik Smolenskoy gosudarstvennoy meditsinskoy akademii = Bulletin of the Smolensk State Medical Academy. 2021;20(1):18–25 (In Russ.) https://doi.org/10.37903/vsgma.2021.1.3

2. Good IJ. Weight of evidence: A brief survey. Bayesian Statistics. 1985;(2):249–70.

3. Lee PM. Bayesian statistical decision theory. New York: Wiley; 1997.

4. Zeng G. A necessary condition for a good binning algorithm in credit scoring. Appl Math Sci. 2014;8(65):3229–42. https://doi.org/10.12988/ams.2014.44300

5. Solomina AS, Shreder OV, Makarova ED, Zabrodina VV, Gorbatova DM, Kolik LG1, et al. Fabomotizole as means of pharmacological correction of pre- and postnatal disorders induced by peat smoke pollution, tobacco smoke, alcohol, hyperglycaemia, and cyclophosphamide in the offspring of rats. Molekulyarnaya meditsina = Molecular Medicine. 2020;18(3):34–48 (In Russ.) https://doi.org/10.29296/24999490-2020-03-05

6. Shreder OV, Shreder ED, Durnev AD, Seredenin SB. Association of genotoxic and teratogenic effects induced by cyclophosphamide and their modification with afobazole. Gigiena i sanitariya = Hygiene and Sanitation. 2011;(5):64–8 (In Russ.)

7. Durnev AD, Zhanataev AK, Shreder OV. Genotoxic events and diseases. Molekulyarnaya meditsina = Molecular Medicine. 2013;(3):3–19 (In Russ.)

8. Shreder ED, Shreder OV, Zabrodina VV, Durnev AD, Seredenin SB. Afobazole modifies the neurotoxic and genotoxic effects in rat prenatal alcoholization model. Bull Exp Biol Med. 2014;157(4):492–5 https://doi.org/10.1007/s10517-014-2599-5

9. Shreder OV, Shreder ED, Zabrodina VV, Durnev AD. Effects of afobazole on the searching activity and food-procuring skill of the offspring of rats exposed to hypoxia during fetal development. In: Alexandrov AK, Fedoseev LM, eds. Long-term memory: mechanisms, types and disorders. New York; 2012. Р. 117–31.