Interpretation of toxicological research data in establishing the no observed adverse effect level (NOAEL) for medicinal products

INTRODUCTION. Toxicological studies of new pharmaceuticals in laboratory animals represent an obligatory stage in drug risk assessment, designed to identify toxic effects, their potential reversibility, and dependence on dose and/or systemic exposure. The primary quantitative outcome of these studies is the no-observed-adverse-effect level (NOAEL), whose key practical application involves determining the starting dose for early-phase human clinical trials. The very definition of NOAEL raises the fundamental question: which experimental changes should be classified as adverse? Toxicology study designs are complex, incorporating a comprehensive range of evaluation parameters including physiological, instrumental, clinical laboratory, and pathological morphological assessments. Upon study completion, researchers accumulate extensive datasets requiring rigorous scientific analysis and evidence-based interpretation of all detected changes.

AIM. The aim of this study is to develop a comprehensive methodology for interpreting toxicological data to enhance objectivity in NOAEL determination.

DISCUSSION. Due to the lack of terminological rigor in describing the NOAEL dose, the present work attempts to unify this term. Particular attention is given to the issue of biological significance of observed changes, as well as the description of criteria for determining their adversity. The developed scheme for interpreting experimental data encompasses three consecutive stages: analysis of the relationship between the observed effect and the administration of the test object; assessment of the effect size and/or degree of changes; determination of the nature of the identified changes in terms of their adversity, including evaluation of their reversibility, pharmacodynamic acceptability, potential for developing an adaptive response, and others. The cornerstone of the proposed methodology is the Weight-of-Evidence principle, which enables ranking of identified adverse effects according to their significance and their integration into a unified assessment system.

CONCLUSIONS. The developed integrated approach, based on multifactorial data analysis (including quantitative and qualitative indicators) and the Weight-of-Evidence assessment principle, can enhance the objectivity of evaluating observed effects and determining the No Observed Adverse Effect Level (NOAEL).

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