Inhaled Medicines (Enhanced Edition‪)‬

Inhaled medicines are widely used to treat pulmonary and systemic diseases. The efficacy and safety of these medicines can be influenced by the deposited fraction, the regional deposition pattern within the lungs and by post-depositional events such as drug dissolution, absorption and clearance from the lungs. Optimizing performance of treatments thus requires that we understand and are able to quantify these product and drug attributes.

Inhaled Medicines: Optimizing Development through Integration of In Silico, In Vitro and In Vivo Approaches explores the current state of the art with respect to inhalation drug delivery, technologies available to assess product performance, and novel in silico methods now available to link in vitro product performance to clinical performance. Recent developments in the latter field, especially the prospect of integration of three-dimensional Computational Fluid Particle Methods (3D-CFPD) with physiologically based pharmacokinetic (PBPK models), unlocks the potential for in silico population studies that can help inform and optimize treatment and product development strategies. In this highly multidisciplinary field, where progress occurs at the intersection of several disciplines of engineering and science, this work aims to integrate current knowledge and understanding and to articulate a clear vision for future developments.
Considers the healthcare needs driving the field, and where inhaled drugs could have the maximum impact Gives a concise account of the state of the art in key areas and technologies such as device and formulation technologies, clinically relevant in vitro performance assessment, medical imaging, as well as in silico modelling and simulation Articulates how the combination of in vitro product performance data, medical imaging and simulations technologies in the framework of large scale in silico pre-clinical trials could revolutionize the field Provides systematic and thorough referencing to sources offering a more-in-depth analysis of technical issues