(M1430-10-64) Physiologically Based Biopharmaceutics Modeling of BCS Class I Extended-Release Drug Products: A Preliminary Exploration

Purpose: The development of physiologically based biopharmaceutics models (PBBMs) for extended-release (ER) drug products presents a unique challenge due to the complex interplay of dissolution, in vivo drug release, and absorption processes. To date, no PBBM for ER products has been approved for regulatory utility. This study aimed to develop and verify a PBBM for a BCS Class I drug in ER formulations, with the goal of improving our understanding of the factors affecting the in vivo performance of such products and shedding light on the potential applicability of PBBMs to ER drug products.

Methods: The study followed a three-step workflow: model development, verification, and application to additional ER formulations (Figure 1). A baseline PBBM was developed in GastroPlus™ using the default human-fasted setting for the Advanced Compartmental Absorption and Transit (ACAT) model of gut physiology. A one-compartment pharmacokinetic model was built based on data from intravenous (IV) infusions of 100/150 mg and immediate-release (IR) 100 mg tablet from the FDA internal database, Source 1. The solubilities at different pH values were obtained from Source 1, and the permeability was conservatively estimated based on uncalibrated Caco-2 test results from Source 1, literature, and optimization results from a syrup formulation. The baseline model was verified against the following formulations: IV 200 mg infusion from Source 1 for the IV model, and IR 100 mg x2 tablets, IR 200 mg BID, and ER commercial 100, 200, and 300 mg formulations from the FDA internal database, Source 2, for the oral model. Following verification, the model was applied to predict the pharmacokinetic performance of three additional ER formulations from Source 2 with dissolution profiles ranging from slow to fast release rates. In vitro dissolution profiles of ER formulations were directly implemented in tabulated format into the baseline model. The dosage form in GastroPlus was changed to 'CR: Dispersed' to represent their ER characteristics.

Results: The baseline PBBM demonstrated satisfactory performance in predicting the in vivo pharmacokinetics of the IV infusion, IR tablets, and the ER commercial formulations used for verification. As shown in Table 1, the ratio between predicted and observed Cmax, AUCi, and Tmax values for the IV 200mg infusion, IR tablets (100mg x2 and 200mg BID), and the ER commercial formulations with dose strengths of 100 mg, 200 mg, and 300 mg was within acceptable limits (±10%), and the coefficient of determination (R²) indicated a strong relationship between predicted and observed data. Upon successful verification, the model was applied to predict the pharmacokinetic performance of three additional ER formulations from Source 2 (Figure 2). The predicted PK curves demonstrated that the model could accurately capture the impact of varying dissolution rates on the in vivo pharmacokinetic performance of the ER formulations. The model's predictions for Cmax, AUCi, and Tmax were in good agreement with the observed data, further supporting the applicability of the PBBM to BCS Class I ER products.

Conclusion: The development and verification of the PBBM for a BCS Class I drug in ER formulations demonstrated the potential applicability of PBBMs in predicting the in vivo performance of ER drug products. The model showed satisfactory performance in predicting the pharmacokinetics of ER formulations, supporting the model's relevance to BCS Class I ER products. This study provides a preliminary exploration into the development of PBBMs for ER products and suggests further investigation to enhance their potential in drug development and regulatory decision-making processes.

Acknowledgements: The poster reflects the view of the authors and should not be construed to represent FDA’s views or policies.