Predictive performance of population pharmacokinetic parameters of tianeptine as applied to plasma concentrations from a post-marketing study

Abstract

The predictive ability of population pharmacokinetic parameters of tianeptine, obtained from a mixed effect analysis of pre-marketing pharmacokinetic studies, was evaluated using tianeptine plasma concentrations obtained during a large multi-center post-marketing surveillance study. The mean prediction error was 7.8 ng.ml-1 and the root mean square prediction error was 52.1 ng/ml when initial estimates of population pharmacokinetic parameters were used to predict drug concentrations in one half of the post-marketing data. When the population parameters were revised to reflect the data collected in the first half of the post-marketing study, the mean prediction error was reduced to -3.2 ng.ml-1 and the root mean square prediction error was reduced to 29.5 ng.ml-1. These results suggest that population pharmacokinetic parameters obtained from pre-marketing data may not accurately predict drug concentrations in patients receiving the drug in the post-marketing setting. Once the population parameters are updated to reflect data from the post-marketing period, the predictive ability of the data-base increases, but substantial variability in the prediction error remains.

Pharmacokinetic/Pharmacodynamic Studies in Drug Product Development

“…The significance of PK/PD evaluations during postmarketing surveillance studies was illustrated by Grasela et al103 These authors showed that population PK parameters for tianeptine obtained during premarketing studies did not accurately predict drug concentrations in patients receiving the drug in the postmarketing setting.…”

The impact of compliance in pharmacokinetic studies

“…18 Perhaps even more unfortunate it has lead in practice to deleting large numbers (up to 50%) of patients from analyses due to missing information on the dosage schedule. 16,23 A procedure that is currently in use to overcome this problem is to select patients with good compliance during a run-in period and to further stimulate compliance by pill counts, digital drug dispensers, patient diaries, ®nancial support, compliance counselling, and so on. Others protest that using observational data under a wide range of compliance patterns, is an underestimated opportunity to study the offset of drug action as dosing lapses occur on the patient's own initiative.…”