A tiered approach to pharmacokinetic studies.

Abstract

Studies of absorption, distribution, metabolism, and elimination (ADME) have long been recognized as important in the evaluation of the pharmacological efficacy of pharmaceutical agents. In recent years, the importance of ADME studies in toxicology also has become increasingly apparent. In realization of the importance of ADME studies, regulatory agencies have established guidelines governing the conduct of these studies. To be of maximum utility, it is desirable that ADME and pharmacokinetic studies be closely integrated with the toxicity testing protocol. However, in many instances this is not the case, which results in ADME and pharmacokinetic studies that are often chronologically and philosophically remote from the toxicity testing protocols. An inevitable consequence of this approach is that it frequently leads to the generation of ADME data that are of limited use in the process of toxicity evaluation and risk assessment. Recently, there has been increased focus on developing testing strategies that would result in the development of ADME data with greater application to toxicity testing and risk assessment. An example of such an approach is the concept of a tiered approach to the conduct of ADME studies. An important aspect of the tiered approach is generating ADME data at an earlier stage during the toxicity testing of a chemical. This could be effected by acceptance of the concept of a minimum experimental data set for a chemical. This minimum data set could be conducted in a timely and economic manner and would develop data addressing three fundamental questions: Is the chemical absorbed? Is the chemical metabolized? Does the chemical persist? The data generated under a minimum data set scenario would not be designed to provide sufficient information for utility in risk evaluation. However, it would provide important information at a much earlier stage of toxicity testing than currently generated under existing testing strategies. Such information would be of importance in the design of toxicity testing studies. Additional ADME and pharmacokinetic information could then be conducted when a specific concern (e.g., toxicity) becomes apparent. The advantage of this approach is that it allows the design of these additional follow-up studies to be tailored to the particular toxicity or risk-evaluation end point (e.g., target organ, species extrapolation, route evaluation, etc.). The specifics of the experimental aspects of the design of ADME and pharmacokinetics studies are discussed. In this development of alternate, and more efficient procedures, for the conduct of metabolism studies, it has become apparent that the potential use of ADME data obtained under studies designated by the regulatory guidelines is often of little use in addressing the major concerns of risk assessment (i.e., species, dose, and route extrapolation). In considering alternate approaches it has become apparent that increased use of dosimetry models such as physiologically based pharmacokinetic models could have significant utility ...

The Acquisition and Application of Absorption, Distribution, Metabolism, and Excretion (ADME) Data in Agricultural Chemical Safety Assessments

“…This minimal tier is a limited set of studies that are included in Tier 1 presented in this paper; it represents the basic starting point, particularly for a new chemical. Much of the remainder of the basic tier described in this paper appears in the second tier proposed by Wilson et al (1994). Useful perspectives are presented on both the ordering of information collection and experimental design issues.…”

“…Classical compartmental or noncompartmental analyses calculate pharmacokinetic parameters, such as T max (time of maximum concentration), C max (maximum concentration), AUC (area under the curve), F (bioavailable fraction of dose), and half-life. For a discussion of pharmacokinetic data interpretations, see Ross et al (2001), Frantz et al (1994), Gibaldi and Perrier (1982), O'Flaherty (1981), Renwick (2001), Wilson et al (1994), and Welling (1986). Computer programs are available for statistically fitting pharmacokinetic data and estimating parameters in compartmental and noncompartmental analyses.…”