Opportunities for improving techniques for interspecies extrapolation in the risk assessment process

Area of Science:

• Toxicology
• Risk Assessment
• Biostatistics

Background:

• Current quantitative cancer risk assessment relies on linearized multistage models from animal bioassays.
• This approach has numerous assumptions that limit its accuracy for low-dose and interspecies extrapolation.
• There is a critical need for mechanistic data to refine these risk assessment models.

Purpose of the Study:

• To highlight the need for mechanistic data in chemical carcinogenic risk assessment.
• To propose methods for incorporating biological data into risk estimation.
• To improve the accuracy of low-dose and interspecies extrapolation in risk assessment.

Main Methods:

• Utilizing target site dosimetry as an organizing concept.
• Employing physiological response modeling for interspecies extrapolation.
• Measuring chemical interactions with target macromolecules and toxic effects (e.g., altered cell regulation, DNA damage, oncogene activation).

Main Results:

• Target site dosimetry and physiological modeling can account for interspecies variations in chemical distribution and disposition.
• Biologically meaningful exposure indices can be derived from direct interaction measurements or toxic effect quantitation.
• Biological markers like DNA damage and cell proliferation offer insights into carcinogenic mechanisms.

Conclusions:

• Mechanistic data are essential for critically evaluating assumptions in current carcinogenic risk assessment.
• Incorporating mechanistic data and biological markers can lead to more accurate risk estimation.
• Future risk assessment models should integrate species-specific biological and toxicological characteristics.