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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.
Models predicting drug release from long-acting injectables (LAIs) after multiple doses can be developed using single-dose pharmacokinetic data. This suggests drug release may be similar between single and multiple dosing conditions for approved LAIs.
Area of Science:
- Pharmacokinetics
- Drug Development
- Regulatory Science
Background:
- Long-acting injectable products (LAIs) improve patient adherence and outcomes by prolonging drug release.
- Regulatory guidelines necessitate single- and multiple-dose trials to assess drug release consistency.
- Trial complexity can impede the development of novel LAIs.
Purpose of the Study:
- To investigate if drug release from LAIs differs between single- and multiple-dose administration.
- To evaluate the predictability of multiple-dose pharmacokinetics using single-dose data.
- To assess the potential to streamline LAI development by reducing trial complexity.
Main Methods:
- Utilized clinical pharmacokinetic (PK) data from five regulatory-approved LAIs.
- Developed population PK models with varying absorption structures using nonlinear mixed-effect modeling on single-dose data.
- Validated models by predicting PK profiles for multiple-dose administration and assessing accuracy against observed data.
Main Results:
- Single-dose LAI absorption was best characterized by first-order absorption models.
- Predicted multiple-dose PK profiles showed a mean accuracy of 93% (range: 70%-122%).
- Seven out of ten PK variables met predefined acceptance criteria for multiple-dose predictions.
Conclusions:
- Pharmacokinetic characteristics after multiple LAI doses can be predicted from single-dose PK models.
- Drug release from the studied LAIs appears consistent between single and multiple dosing conditions.
- Further research on diverse LAIs is needed to confirm generalizability and model limitations.
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