Model for the Analysis of Membrane-Type Dissolution Tests for Inhaled Drugs

Impactor-type dose deposition is a common prerequisite for dissolution testing of inhaled medicines, and drug release typically takes place through a membrane. The purpose of this work is to develop a mechanistic model for such combined dissolution and release processes, focusing on a drug that initially is present in solid form. Our starting points are the Noyes-Whitney (or Nernst-Brunner) equation and Fick's law. A detailed mechanistic analysis of the drug release process is provided, and approximate closed-form expressions for the amount of the drug that remains in solid form and the amount of the drug that has been released are derived. Comparisons with numerical data demonstrated the accuracy of the approximate expressions. Comparisons with experimental release data from literature demonstrated that the model can be used to establish rate-controlling release mechanisms. In conclusion, the model constitutes a valuable tool for the analysis of in vitro dissolution data for inhaled drugs

Characterization of Membrane-Type Dissolution Profiles of Clinically Available Orally Inhaled Products Using a Weibull Fit and a Mechanistic Model

Dissolution rate impacts the absorption rate of poorly soluble inhaled drugs. In vitro dissolution tests that can capture the impact of changes in critical quality attributes of the drug product on in vivo dissolution are important for the development of products containing poorly soluble drugs, as well as modified release formulations. In this study, an extended mathematical model allowing for dissolution of polydisperse powders and subsequent diffusion of dissolved drug across a membrane is described. In vitro dissolution profiles of budesonide, fluticasone propionate, and beclomethasone dipropionate delivered from three commercial drug products were determined using a membrane-type Transwell dissolution test, which consists of a donor and an acceptor compartment separated by a membrane. Subsequently, the profiles were analyzed using the developed mechanistic model and a semi-empirical model based on the Weibull distribution. The two mathematical models provided the same rank order of the performance of the three drug products in terms of dissolution rates, but the rates were significantly different. The faster rate extracted from the mechanistic model is expected to reflect the true dissolution rate of the drug; the Weibull model provides an effective and slower rate that represents not only drug dissolution but also diffusion across the Transwell membrane. In conclusion, the developed extended model provides superior understanding of the dissolution mechanisms in membrane-type (Transwell) dissolution tests

Controlled Pulmonary Delivery of Carrier-Free Budesonide Dry Powder by Atomic Layer Deposition

Ideal controlled pulmonary drug delivery systems provide sustained release by retarding lung clearance mechanisms and efficient lung deposition to maintain therapeutic concentrations over prolonged time. Here, we use atomic layer deposition (ALD) to simultaneously tailor the release and aerosolization properties of inhaled drug particles without the need for lactose carrier. In particular, we deposit uniform nanoscale oxide ceramic films, such as Al2O3, TiO2, and SiO2, on micronized budesonide particles, a common active pharmaceutical ingredient for the treatment of respiratory diseases. In vitro dissolution and ex vivo isolated perfused rat lung tests demonstrate dramatically slowed release with increasing nanofilm thickness, regardless of the nature of the material. Ex situ transmission electron microscopy at various stages during dissolution unravels mostly intact nanofilms, suggesting that the release mechanism mainly involves the transport of dissolution media through the ALD films. Furthermore, in vitro aerosolization testing by fast screening impactor shows a μ2-fold increase in fine particle fraction (FPF) for each ALD-coated budesonide formulation after 10 ALD process cycles, also applying very low patient inspiratory pressures. The higher FPFs after the ALD process are attributed to the reduction in the interparticle force arising from the ceramic surfaces, as evidenced by atomic force microscopy measurements. Finally, cell viability, cytokine release, and tissue morphology analyses verify a safe and efficacious use of ALD-coated budesonide particles at the cellular level. Therefore, surface nanoengineering by ALD is highly promising in providing the next generation of inhaled formulations with tailored characteristics of drug release and lung deposition, thereby enhancing controlled pulmonary delivery opportunities.ChemE/Product and Process Engineerin

IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 4: Prediction accuracy and software comparisons with improved data and modelling strategies

Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption is much needed. Current status of predictive performance, within the confinement of commonly available in vitro data on drugs and formulations alongside systems information, were tested using 3 PBPK software packages (GI-Sim (ver.4.1), Simcyp® Simulator (ver.15.0.86.0), and GastroPlusTM (ver.9.0.00xx)). This was part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project. Fifty eight active pharmaceutical ingredients (APIs) were qualified from the OrBiTo database to be part of the investigation based on a priori set criteria on availability of minimum necessary information to allow modelling exercise. The set entailed over 200 human clinical studies with over 700 study arms. These were simulated using input parameters which had been harmonised by a panel of experts across different software packages prior to conduct of any simulation. Overall prediction performance and software packages comparison were evaluated based on performance indicators (Fold error (FE), Average fold error (AFE) and absolute average fold error (AAFE)) of pharmacokinetic (PK) parameters. On average, PK parameters (Area Under the Concentration-time curve (AUC0-tlast), Maximal concentration (Cmax), half-life (t1/2)) were predicted with AFE values between 1.11 and 1.97. Variability in FEs of these PK parameters was relatively high with AAFE values ranging from 2.08 to 2.74. Around half of the simulations were within the 2-fold error for AUC0-tlast and around 90% of the simulations were within 10-fold error for AUC0-tlast. Oral bioavailability (Foral) predictions, which were limited to 19 APIs having intravenous (i.v.) human data, showed AFE and AAFE of values 1.37 and 1.75 respectively. Across different APIs, AFE of AUC0-tlast predictions were between 0.22 and 22.76 with 70% of the APIs showing an AFE &gt; 1. When compared across different formulations and routes of administration, AUC0-tlast for oral controlled release and i.v. administration were better predicted than that for oral immediate release formulations. Average predictive performance did not clearly differ between software packages but some APIs showed a high level of variability in predictive performance across different software packages. This variability could be related to several factors such as compound specific properties, the quality and availability of information, and errors in scaling from in vitro and preclinical in vivo data to human in vivo behaviour which will be explored further. Results were compared with previous similar exercise when the input data selection was carried by the modeller rather than a panel of experts on each in vitro test. Overall, average predictive performance was increased as reflected in smaller AAFE value of 2.8 as compared to AAFE value of 3.8 in case of previous exercise.QC 20200930</p