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Objectives: The main objective of the present work was to combine in vitro and in silico tools to better understand the in vivo behavior of the immediate release (IR) formulation of zolpidem in the fasted and fed states.
Methods: The dissolution of zolpidem was evaluated using biorelevant media simulating the gastric and intestinal environment in the fasted and fed states. Additionally, the influence of high viscosity and high fat content on the release of zolpidem under fed state conditions was investigated. The in vitro results were combined with a physiologically based pharmacokinetic (PBPK) model constructed with Simcyp to simulate the zolpidem pharmacokinetic profile in both prandial states.
Key findings: In vitro biorelevant dissolution experiments representing the fasted and fed states, combined with PBPK modelling, were able to simulate the plasma profiles from the clinical food effect studies well. Experiments reflecting the pH and fat content of the meal led to a good prediction of the zolpidem plasma profile in the fed state, whereas increasing the viscosity of the gastric media led to an under-prediction.
Conclusions: This work demonstrates that the combination of biorelevant dissolution testing and PBPK modelling is very useful for understanding the in-vivo behavior of zolpidem in the fasted and fed states. This approach could be implemented in the development of other drugs exhibiting negative food effects, saving resources and bringing new drug products to the market faster.
Background: Zolpidem is a non-benzodiazepine hypnotic agent which has been shown to be effective in inducing and maintaining sleep in adults and is one of the most frequently prescribed hypnotics in the world. For drugs that are used to treat sleeping disorders, the time to reach the maximum concentration (Tmax) of the drug in plasma is important to achieving a fast onset of action and this must be maintained when switching from one product to another.
Objectives: The main objective of the present work was to create a PBPK/PD model for zolpidem and establish a clinically relevant “safe space” for dissolution of zolpidem from the commercial immediate release (IR) formulation. A second objective was to analyze literature pharmacokinetic data to verify the negative food effect ascribed to zolpidem and consider its ramifications in terms of the “safe space” for dissolution.
Methods: Using dissolution, pharmacokinetic and pharmacodynamic data, an integrated PBPK/PD model for immediate release zolpidem tablets was constructed in Simcyp®. This model was used to identify the clinically relevant dissolution specifications necessary to ensure efficacy.
Results: According to the simulations, as long as 85% of the drug is released in 45 minutes or less, the impact on the PK and PD profiles of zolpidem would be minimal. According to the FDA, the drug has to dissolve from the test and reference products at a similar rate and to an extent of 85% in not more than 30 minutes to pass bioequivalence via the BCS-biowaiver test. Thus, the BCS-biowaiver specifications are somewhat more stringent than the “safe space” based on the PBPK/PD model. Published data from fasted and fed state pharmacokinetic studies suggest but do not prove a negative food effect of zolpidem.
Conclusions: A PBPK/PD model indicates that current BCS biowaiver criteria are more restrictive for immediate release zolpidem tablets than they need to be. In view of the close relationship between PK and PD, it remains advisable to avoid taking zolpidem tablets with or immediately after a meal, as indicated by the Stilnox® labeling.
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.