4.7 Article

Integrating In Vitro Biopharmaceutics into Physiologically Based Biopharmaceutic Model (PBBM) to Predict Food Effect of BCS IV Zwitterionic Drug (GSK3640254)

期刊

PHARMACEUTICS
卷 15, 期 2, 页码 -

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MDPI
DOI: 10.3390/pharmaceutics15020521

关键词

PBPK modelling; PBBM modelling; biopharmaceutics; food effect; BCS IV; biorelevant media; in vitro; dissolution; permeability; MDCK cell line; FaSSIF; FeSSIF; Simcyp((R))

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This study describes a strategy that integrates in vitro solubility and permeability data into a PBBM model to predict the food effect of a BCS IV zwitterionic drug (GSK3640254) observed in clinical studies. The PBBM model was developed and validated using clinical data obtained from healthy volunteers. The results showed that the positive food effect observed in the clinical studies was attributed to micelle-mediated enhanced solubility and permeability. The developed PBBM model accurately predicted the results of the food effect, indicating its effectiveness in predicting the food effect of BCS class IV drugs.
A strategy followed to integrate in vitro solubility and permeability data into a PBBM model to predict the food effect of a BCS IV zwitterionic drug (GSK3640254) observed in clinical studies is described. The PBBM model was developed, qualified and verified using clinical data of an immediate release (IR)-tablet (10-320 mg) obtained in healthy volunteers under fasted and fed conditions. The solubility of GSK3640254 was a function of its ionization state, the media composition and pH, whereas its permeability determined using MDCK cell lines was enhanced by the presence of mixed micelles. In vitro data alongside PBBM modelling suggested that the positive food effect observed in the clinical studies was attributed to micelle-mediated enhanced solubility and permeability. The biorelevant media containing oleic acid and cholesterol in fasted and fed levels enabled the model to appropriately capture the magnitude of the food effect. Thus, by using Simcyp((R)) v20 software, the PBBM model accurately predicted the results of the food effect and predicted data were within a two-fold error with 70% being within 1.25-fold. The developed model strategy can be effectively adopted to increase the confidence of using PBBM models to predict the food effect of BCS class IV drugs.

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