Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre-including this research content-immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
Substituting spacer by another in noninvasive ventilation (NIV) involves many variables, e.g. total emitted dose (TED), mass median aerodynamic diameter (MMAD), type of spacer, total lung deposition and total systemic absorption, which must be adjusted to ensure patient optimum therapy. Data mining based on artificial neural networks and genetic algorithms were used to model in vitro inhalation process, predict and optimize bioavailability from inhaled doses delivered by metered dose inhaler (MDI) using different spacers in NIV. Modeling of data indicated that in vitro performance of MDI-spacer systems was dependent mainly on fine particle dose (FPD), fine particle fraction (FPF), MMAD and to lesser extent on spacer type. Ex vivo model indicated that amount of salbutamol collected on facemask filter was directly affected by FPF. In vivo model (24hQ) depended directly on spacer type, FPF and TED. Female patients showed higher 0.5hQ and 24hQ values than males. AeroChamber VC spacer demonstrated higher TED and 24hQ in vivo values. Results indicated suitability of MDI-spacer systems in achieving appropriate in vitro inhalation performance. The possibility of modeling and predicting both ex vivo and in vivo capabilities of MDI-spacer systems from knowledge of in vitro attributes enabled detailed focus on important variables required to deliver safe and accurate doses of salbutamol to ventilated patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.