Improved estimates of mean pharmacokinetic parameters for increased accuracy in dosing and reduced risk to patients. Issue 9 (1st March 2021)

• Record Type: Journal Article
• Authors: Scutt, Greg; Waxman, David
• Is Part Of: British journal of clinical pharmacology. Volume 87:Issue 9(2021)
• Page Start: 3518
• Page End: 3530
• Publication Date: 2021-03-01
• Subjects: pharmacokinetics -- statistics and study design -- therapeutic drug monitoring -- clinical pharmacology; Pharmacology -- Periodicals; Drugs -- Periodicals; 615.1
• DOI: 10.1111/bcp.14766
• Languages: English
• ISSNs: 0306-5251

Abstract

Abstract : Aims: Pharmacokinetic equations, which relate different parameters of a single individual, are often applied to reported mean parameter‐values, with the aim of estimating the mean value of an unreported parameter. Due to population heterogeneity this approach generally leads to errors in their estimation. We provide details of this source of error. Our aim is to take into account the effects of population heterogeneity in commonly used pharmacokinetic models. This provides improved estimates and knowledge of the concentration of a drug in the plasma over time. Methods: Inequalities and approximations for corrected mean estimates are derived. These results are then applied to published clinical‐trial data to illustrate their accuracy in practical situations. Results: By using mean values within the pharmacokinetic equations for a single individual, we show that estimates of mean parameter values, for a variety of dosing regimens, generally have errors. Using published clinical trial data, we show that such estimates can systematically deviate from the exact mean value by up to 19%. We provide analytical results, which amount to inequalities when there are systematic deviations from exact results, along with approximate results that improve the accuracy of estimates. Conclusions: Medical, pharmacy and nursing students should be educated about errors and inequalities that can arise when transforming reported mean values of pharmacokinetic parameters into the mean values of parameters that are required, but not reported. Using approximate results, that correct estimates of mean parameter values so that they more accurately reflect actual average values, may provide a practical solution.