A physiologically based biopharmaceutical analysis of zolpidem

2021 ◽  
Author(s):  
◽  
Rafael Leal Monteiro Paraiso

Computational oral absorption models, in particular PBBM models, provide a powerful tool for researchers and pharmaceutical scientists in drug discovery and formulation development, as they mimic and can describe the physiologically processes relevant to the oral absorption. PBBM models provide in vivo context to in vitro data experiments and allow for a dynamic understanding of in vivo drug disposition that is not typically provided by data from standard in vitro assays. Investigations using these models permit informed decision-making, especially regarding to formulation strategies in drug development. PBBM models, but can also be used to investigate and provide insight into mechanisms responsible for complex phenomena such as food effect in drug absorption. Although there are obviously still some gaps regarding the in silico construction of the gastrointestinal environment, ongoing research in the area of oral drug absorption (e.g. the UNGAP, AGE-POP and InPharma projects) will increase knowledge and enable improvement of these models. PBBM can nowadays provide an alternative approach to the development of in vitro–in vivo correlations. The case studies presented in this thesis demonstrate how PBBM can address a mechanistic understanding of the negative food effect and be used to set clinically relevant dissolution specification for zolpidem immediate release tablets. In both cases, we demonstrated the importance of integrating drug properties with physiological variables to mechanistically understand and observe the impact of these parameters on oral drug absorption. Various complex physiological processes are initiated upon food consumption, which can enhance or reduce a drug’s dissolution, solubility, and permeability and thus lead to changes in drug absorption. With improvements in modeling and simulation software and design of in vitro studies, PBBM modeling of food effects may eventually serve as a surrogate for clinical food effect studies for new doses and formulations or drugs. Furthermore, the application of these models may be even more critical in case of compounds where execution of clinical studies in healthy volunteers would be difficult (e.g., oncology drugs). In the fourth chapter we have demonstrated the establishment of the link between biopredictive in vitro dissolution testing (QC or biorelevant method) PBBM coupled with PD modeling opens the opportunity to set truly clinically relevant specifications for drug release. This approach can be extended to other drugs regardless of its classification according to the BCS. With the increased adoption of PBBM, we expect that best practices in development and verification of these models will be established that can eventually inform a regulatory guidance. Therefore, the application of Physiologically Based Biopharmaceutical Modelling is an area with great potential to streamline late-stage drug development and impact on regulatory approval procedures. Freie Schlagwörter / Tags

Pharmaceutics ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 74 ◽  
Author(s):  
Marival Bermejo ◽  
Bart Hens ◽  
Joseph Dickens ◽  
Deanna Mudie ◽  
Paulo Paixão ◽  
...  

The application of in silico modeling to predict the in vivo outcome of an oral drug product is gaining a lot of interest. Fully relying on these models as a surrogate tool requires continuous optimization and validation. To do so, intraluminal and systemic data are desirable to judge the predicted outcomes. The aim of this study was to predict the systemic concentrations of ibuprofen after oral administration of an 800 mg immediate-release (IR) tablet to healthy subjects in fasted-state conditions. A mechanistic oral absorption model coupled with a two-compartmental pharmacokinetic (PK) model was built in Phoenix WinNonlinWinNonlin® software and in the GastroPlus™ simulator. It should be noted that all simulations were performed in an ideal framework as we were in possession of a plethora of in vivo data (e.g., motility, pH, luminal and systemic concentrations) in order to evaluate and optimize these models. All this work refers to the fact that important, yet crucial, gastrointestinal (GI) variables should be integrated into biopredictive dissolution testing (low buffer capacity media, considering phosphate versus bicarbonate buffer, hydrodynamics) to account for a valuable input for physiologically-based pharmacokinetic (PBPK) platform programs. While simulations can be performed and mechanistic insights can be gained from such simulations from current software, we need to move from correlations to predictions (IVIVC → IVIVP) and, moreover, we need to further determine the dynamics of the GI variables controlling the dosage form transit, disintegration, dissolution, absorption and metabolism along the human GI tract. Establishing the link between biopredictive in vitro dissolution testing and mechanistic oral absorption modeling (i.e., physiologically-based biopharmaceutics modeling (PBBM)) creates an opportunity to potentially request biowaivers in the near future for orally administered drug products, regardless of its classification according to the Biopharmaceutics Classification System (BCS).


2017 ◽  
Vol 14 (12) ◽  
pp. 4661-4674 ◽  
Author(s):  
Patrick D. Sinko ◽  
David Gidley ◽  
Richard Vallery ◽  
Aaron Lamoureux ◽  
Gordon L. Amidon ◽  
...  

2010 ◽  
Vol 40 (2) ◽  
pp. 118-124 ◽  
Author(s):  
Kiyohiko Sugano ◽  
Makoto Kataoka ◽  
Claudia da Costa Mathews ◽  
Shinji Yamashita

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