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Variability in susceptibility - how big, how often, for what responses to what agents?
Environmental Toxicology and Pharmacology
|July 26, 2011
Summary
Human studies reveal significant interindividual variability in drug exposure and response. Systematic analysis of this variability may refine safety factors for different agents and responses.
Area of Science:
- Pharmacology
- Toxicology
- Epidemiology
Background:
- Interindividual variability in drug exposure, pharmacokinetics, and pharmacodynamics is a critical factor in determining non-cancer responses.
- Existing drug and epidemiological literature contains valuable data on dose-response variability that remains underexplored.
Purpose of the Study:
- To survey recent human observations on interindividual variability in exposure-related parameters, pharmacokinetics, and pharmacodynamics.
- To highlight the potential for systematic analysis of existing data to inform understanding of dose-response relationships.
- To propose that enhanced measurement and analysis of variability can lead to adaptive safety factor modifications.
Main Methods:
- Systematic review and analysis of available human observational data.
- Literature survey focusing on exposure-related parameters, pharmacokinetics, and pharmacodynamics.
- Exploration of existing drug and epidemiological datasets.
Main Results:
- Drug and epidemiological literatures contain substantial, yet unanalyzed, information on variability in doses linked to non-cancer responses.
- It is probable that increased systematic measurement and analysis will reveal tendencies for certain responses to specific agents to occur at more variable exposures/doses.
- Current data suggest a need for a more nuanced approach to safety factor application.
Conclusions:
- Existing literature is a rich source for understanding interindividual variability in dose-response relationships.
- Systematic analysis of variability is likely to uncover agent- and response-specific patterns.
- Future research should focus on gathering and analyzing variability data to enable adaptive modifications to safety factors, potentially improving risk assessment accuracy.
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