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In silico mechanistic modeling approaches have been designed by various stakeholders with the goal of supporting development and approval of generic orally inhaled drug products in the United States. This review summarizes the presentations and panel discussion that comprised a workshop session concentrated on the use of in silico models to predict various outcomes following orally inhaled drug product administration, including the status of such models and how model credibility may be effectively established., (© 2022 Teva Pharmaceuticals Ireland, Novartis Healthcare Private Limited, India and The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

On September 30 and October 1, 2021, the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics cosponsored a live virtual workshop titled "Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches." The overall aims of the workshop included (i) engaging the generic drug industry and other involved stakeholders regarding how mechanistic modeling and simulation can support their product development and regulatory submissions; (ii) sharing the current state of mechanistic modeling for bioequivalence (BE) assessment through case studies; (iii) establishing a consensus on best practices for using mechanistic modeling approaches, such as physiologically based pharmacokinetic modeling and computational fluid dynamics modeling, for BE assessment; and (iv) introducing the concept of a Model Master File to improve model sharing between model developers, industry, and the FDA. More than 1500 people registered for the workshop. Based on a postworkshop survey, the majority of participants reported that their fundamental scientific understanding of mechanistic models was enhanced, there was greater consensus on model validation and verification, and regulatory expectations for mechanistic modeling submitted in abbreviated new drug applications were clarified by the workshop., (© 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

The development of generic, single-entity, drug-device combination products for orally inhaled drug products is challenging in part because of the complex nature of device design characteristics and the difficulties associated with establishing bioequivalence for a locally acting drug product delivered to the site of action in the lung. This review examines in silico models that may be used to support the development of generic orally inhaled drug products and how model credibility may be assessed., (© 2019. This article is a U.S. Government work and is in the public domain in the USA. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Nasal delivery of lung targeted pharmaceutical aerosols is ideal for drugs that need to be administered during high flow nasal cannula (HFNC) gas delivery, but based on previous studies losses and variability through both the delivery system and nasal cavity are expected to be high. The objective of this study was to assess the variability in aerosol delivery through the nose to the lungs with a nasal cannula interface for conventional and excipient enhanced growth (EEG) delivery techniques. A database of nasal cavity computed tomography (CT) scans was collected and analyzed, from which four models were selected to represent a wide range of adult anatomies, quantified based on the nasal surface area-to-volume ratio (SA/V). Computational fluid dynamics (CFD) methods were validated with existing in vitro data and used to predict aerosol delivery through a streamlined nasal cannula and the four nasal models at a steady state flow rate of 30 L/min. Aerosols considered were solid particles for EEG delivery (initial 0.9 μm and 1.5 μm aerodynamic diameters) and conventional droplets (5 μm) for a control case. Use of the EEG approach was found to reduce depositional losses in the nasal cavity by an order of magnitude and substantially reduce variability. Specifically, for aerosol deposition efficiency in the four geometries, the 95% confidence intervals (CI) for 0.9 and 5 μm aerosols were 2.3-3.1 and 15.5-66.3%, respectively. Simulations showed that the use of EEG as opposed to conventional methods improved delivered dose of aerosols through the nasopharynx, expressed as penetration fraction (PF), by approximately a factor of four. Variability of PF, expressed by the coefficient of variation (CV), was reduced by a factor of four with EEG delivery compared with the control case. Penetration fraction correlated well with SA/V for larger aerosols, but smaller aerosols showed some dependence on nasopharyngeal exit hydraulic diameter. In conclusion, results indicated that the EEG technique not only improved lung aerosol delivery, but largely eliminated variability in both nasal depositional loss and lung PF in a newly developed set of nasal airway models.