Applications of population pharmacokinetics in current drug labelling

Summary

Background and Objective: The application of population pharmacokinetics (PopPK) appears increasingly in drug labelling. The current study was to examine the use of PopPK in dose recommendation in drug-product labels.

Method: PopPK information was identified in the data sheets included in the physician desk reference (PDR). Electronic key word searches were conducted in the electronic library of PDR. The use of PopPK in the prescribing information, including the determination of dosing regimen, dosing in special populations and dose-adjustments was summarized and evaluated. The reliability and criteria for integrating the information derived from PopPK studies into the product labelling were discussed.

Results and Discussion: Among more than 2500 items listed in the PDR, 88 listings were found to have PopPK information in the labelling. The information included general data (Gen) on pharmacokinetics (PK) and the effects of gender (sex), age, race, drug–drug interactions (DDI), smoking (Smk), alcohol consumption (Alc), disease state (Dis), renal impairment (Ren) and metabolic status (Met) on the PK parameters (Table). Whether there was an effect (+) or not (−) is also shown. Appendix 1 lists the products included in each category.

 

Gen Sex Age Race DDI Smk Alc Dis Ren Met Total 23 27 34 20 19 9 1 4 7 1 + − 8 12 0 9 4 0 0 3 1 − − 19 22 20 10 5 1 4 4 0

Searches conducted at different times suggest an increase in both quantity and quality of PopPK data in drug development. PopPK is widely used in paediatric studies and the sample sizes in these studies are sometimes too small. The application of PopPK to protein drugs is increasing rapidly (Appendix 2). Several precautions should be exercised when PopPK is applied to protein drugs. When considering gender effects, different normalization methods for body weight have been used. The number of subjects included in the PopPK analysis should be given and the influence of the imbalance in any covariate should be investigated. PopPK-DDI results are particularly difficult to evaluate unless details about potentially influential factors such as dosing and sampling information for both drug and interacting drugs are given.

Conclusions: The use of PopPK to aid optimal dosing is increasing. Several noticeable problems raised usually avoid the acceptability of PopPK studies. More investigations are needed to inform the development of consensuses on these issues. There is an accelerating shift from PopPK to PopPK/PD. The limitations of such modelling should be recognized.