Refine
Has Fulltext
- yes (16) (remove)
Is part of the Bibliography
- no (16)
Keywords
- PBPK (3)
- Precipitation inhibition (2)
- Supersaturation (2)
- biorelevant dissolution (2)
- modeling and simulation (2)
- Atazanavir (1)
- Bioenabling formulations (1)
- Cinnarizine (1)
- Clinical relevant dissolution specification (1)
- Colitis Ulcerosa (1)
Institute
Introduction: When developing bio-enabling formulations, innovative tools are required to understand and predict in vivo performance and may facilitate approval by regulatory authorities. EMEND® is an example of such a formulation, in which the active pharmaceutical ingredient, aprepitant, is nano-sized. The aims of this study were 1) to characterize the 80 mg and 125 mg EMEND® capsules in vitro using biorelevant tools, 2) to develop and parameterize a physiologically based pharmacokinetic (PBPK) model to simulate and better understand the in vivo performance of EMEND® capsules and 3) to assess which parameters primarily influence the in vivo performance of this formulation across the therapeutic dose range.
Methods: Solubility, dissolution and transfer experiments were performed in various biorelevant media simulating the fasted and fed state environment in the gastrointestinal tract. An in silico PBPK model for healthy volunteers was developed in the Simcyp Simulator, informed by the in vitro results and data available from the literature.
Results: In vitro experiments indicated a large effect of native surfactants on the solubility of aprepitant. Coupling the in vitro results with the PBPK model led to an appropriate simulation of aprepitant plasma concentrations after administration of 80 mg and 125 mg EMEND® capsules in both the fasted and fed states. Parameter Sensitivity Analysis (PSA) was conducted to investigate the effect of several parameters on the in vivo performance of EMEND®. While nano-sizing aprepitant improves its in vivo performance, intestinal solubility remains a barrier to its bioavailability and thus aprepitant should be classified as DCS IIb.
Conclusions: The present study underlines the importance of combining in vitro and in silico biopharmaceutical tools to understand and predict the absorption of this poorly soluble compound from an enabling formulation. The approach can be applied to other poorly soluble compounds to support rational formulation design and to facilitate regulatory assessment of the bio-performance of enabling formulations.
Objectives Supersaturating formulations hold great promise for delivery of poorly soluble active pharmaceutical ingredients (APIs). To profit from supersaturating formulations, precipitation is hindered with precipitation inhibitors (PIs), maintaining drug concentrations for as long as possible. This review provides a brief overview of supersaturation and precipitation, focusing on precipitation inhibition. Trial-and-error PI selection will be examined alongside established PI screening techniques. Primarily, however, this review will focus on recent advances that utilise advanced analytical techniques to increase mechanistic understanding of PI action and systematic PI selection.
Key Findings. Advances in mechanistic understanding have been made possible by the use of analytical tools such as spectroscopy, microscopy and mathematical and molecular modelling, which have been reviewed herein. Using these techniques, PI selection can instead be guided by molecular rationale. However, more work is required to see wide-spread application of such an approach for PI selection.
Conclusions PIs are becoming increasingly important in enabling formulations. Trial-and-error approaches have seen success thus far. However, it is essential to learn more about the mode of action of PIs if the most optimal formulations are to be realised. Robust analytical tools, and the knowledge of where and how they can be applied, will be essential in this endeavour.
Supersaturating formulations are widely used to improve the oral bioavailability of poorly soluble drugs. However, supersaturated solutions are thermodynamically unstable and such formulations often must include a precipitation inhibitor (PI) to sustain the increased concentrations to ensure that sufficient absorption will take place from the gastrointestinal tract. Recent advances in understanding the importance of drug-polymer interaction for successful precipitation inhibition have been encouraging. However, there still exists a gap in how this newfound understanding can be applied to improve the efficiency of PI screening and selection, which is still largely carried out with trial and error-based approaches. The aim of this study was to demonstrate how drug-polymer mixing enthalpy, calculated with the Conductor like Screening Model for Real Solvents (COSMO-RS), can be used as a parameter to select the most efficient precipitation inhibitors, and thus realise the most successful supersaturating formulations. This approach was tested for three different Biopharmaceutical Classification System (BCS) II compounds: dipyridamole, fenofibrate and glibenclamide, formulated with the supersaturating formulation, mesoporous silica. For all three compounds, precipitation was evident in mesoporous silica formulations without a precipitation inhibitor. Of the nine precipitation inhibitors studied, there was a strong positive correlation between the drug-polymer mixing enthalpy and the overall formulation performance, as measured by the area under the concentration-time curve in in vitro dissolution experiments. The data suggest that a rank-order based approach using calculated drug-polymer mixing enthalpy can be reliably used to select precipitation inhibitors for a more focused screening. Such an approach improves efficiency of precipitation inhibitor selection, whilst also improving the likelihood that the most optimal formulation will be realised.
Objectives: The objective of this review is to provide an overview of PK/PD models, focusing on drug-specific PK/PD models and highlighting their value-added in drug development and regulatory decision-making.
Key findings: Many PK/PD models, with varying degrees of complexity and physiological understanding, have been developed to evaluate the safety and efficacy of drug products. In special populations (e.g. pediatrics), in cases where there is genetic polymorphism and in other instances where therapeutic outcomes are not well described solely by PK metrics, the implementation of PK/PD models is crucial to assure the desired clinical outcome. Since dissociation between the pharmacokinetic and pharmacodynamic profiles is often observed, it is proposed that physiologically-based pharmacokinetic (PBPK) and PK/PD models be given more weight by regulatory authorities when assessing the therapeutic equivalence of drug products.
Summary: Modeling and simulation approaches already play an important role in drug development. While slowly moving away from “one-size fits all” PK methodologies to assess therapeutic outcomes, further work is required to increase confidence in PK/PD models in translatability and prediction of various clinical scenarios to encourage more widespread implementation in regulatory decision-making.
Background: Drugs used to treat gastrointestinal diseases (GI drugs) are widely used either as prescription or over23 the-counter (OTC) medications and belong to both the ten most prescribed and ten most sold OTC medications worldwide. Current clinical practice shows that in many cases, these drugs are administered concomitantly with other drug products. Due to their metabolic properties and mechanisms of action, the drugs used to treat gastrointestinal diseases can change the pharmacokinetics of some co27 administered drugs. In certain cases, these interactions can lead to failure of treatment or to the occurrence of serious adverse events. The mechanism of interaction depends highly on drug properties and differs among therapeutic categories. Understanding these interactions is essential to providing recommendations for optimal drug therapy.
Objective: To discuss the most frequent interactions between GI and other drugs, including identification of the mechanisms behind these interactions, where possible.
Conclusion: Interactions with GI drugs are numerous and can be highly significant clinically. Whilst alterations in bioavailability due to changes in solubility, dissolution rate and metabolic interactions can be (for the most part) easily identified, interactions that are mediated through other mechanisms, such as permeability or microbiota, are less well understood. Future work should focus on characterizing these aspects.