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Published on: March 11, 2021
Evaluating Model-Based Extrapolation of Plasma Exposure for Long-Acting Injectable Products: From Single- to
D Esther Lubberts1,2, Douglas J Eleveld1, Laurens F M Verscheijden2,3
1Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
None:
Long-acting injectable medicinal products (LAIs) prolong drug release and thereby aim to enhance adherence and patient outcomes. European regulatory guidelines require the conduct of single- and multiple-dose trials to exclude differences in drug release between non-steady and steady state conditions. The complexity of these trials may however hamper the development of LAIs. This study aimed to examine whether drug release is different after single- and multiple-dose administration using clinical pharmacokinetic (PK) data of a sample of five regulatory-approved LAIs. Single- and multiple-dose data were extracted from an internal regulatory database. Population pharmacokinetic models with different absorption structures were developed using nonlinear mixed-effect modeling based on the single-dose data of every LAI. The best-fitting models were used to predict the pharmacokinetic profiles after multiple-dose administration. The absorption of LAIs after single-dose administration was best described with (parallel) first-order absorption structures (with and without lag-time). After multiple-dose administration, the mean model accuracy was 93% (minimum to maximum: 70%-122%), and 7 out of 10 observed pharmacokinetic variables (i.e., area under the plasma concentration-time curve, minimum and maximum concentration) met the pre-specified acceptance criteria. In conclusion, multiple-dose PK characteristics can be predicted using models developed from single-dose PK data, which indicates that drug release may not be very different between dosing conditions in this sample of regulatory-approved LAIs. Nevertheless, additional studies on other LAIs are required to test the generalizability of our findings and to increase our understanding of the limitations of the proposed model-based approach vis-à-vis the current evidentiary standard.
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