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Extrapolation of experimental data from animals to man

G N Krasovskii

    Environmental Health Perspectives
    |February 1, 1976
    PubMed
    Summary

    This study establishes a computational method for extrapolating toxicologic data from animals to humans, utilizing body weight correlations. A safety coefficient is recommended for reliable public health application of these findings.

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    Area of Science:

    • Toxicology
    • Comparative Physiology
    • Biostatistics

    Background:

    • Extrapolating animal toxicologic data to humans is crucial for risk assessment.
    • Understanding interspecies differences in toxic responses is essential for accurate extrapolation.
    • Existing methods require refinement to account for biological variability.

    Purpose of the Study:

    • To investigate general regularities in comparative sensitivity to toxins across species.
    • To develop a computational method for extrapolating toxicologic data from animals to humans.
    • To enhance the reliability of animal-to-human data extrapolation for public health.

    Main Methods:

    • Analysis of toxicity parameters and biological constants in mammals.
    • Application of rectilinear regression equations to correlate biological constants with body weight.
    • Development of a computational extrapolation method based on identified regularities.

    Main Results:

    • A strong correlation was found between mammalian biological constants and body weight, described by a regression equation.
    • Toxicity parameters for 80% of tested substances followed this body weight-related regularity.
    • A computational method for extrapolating toxicologic data to the average human was developed.

    Conclusions:

    • Body weight serves as a reliable predictor for interspecies toxicologic data extrapolation.
    • Consideration of population sensitivity variability and experimental error is vital for accurate extrapolation.
    • A coefficient of reserve (minimum 10) is advised for safe application in public health practice.

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