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This study assesses the fluidized bed granulation process for the optimization of a model formulation using in-line near-infrared (NIR) spectroscopy for moisture determination. The granulation process was analyzed using an automated granulator and optimization of the verapamil hydrochloride formulation was performed using a mixture design. The NIR setup with a fixed wavelength detector was applied for moisture measurement. Information from other process measurements, temperature difference between process inlet air and granules (T(diff)), and water content of process air (AH), was also analyzed. The application of in-line NIR provided information related to the amount of water throughout the whole granulation process. This information combined with trend charts of T(diff) and AH enabled the analysis of the different process phases. By this means, we can obtain in-line documentation from all the steps of the processing. The choice of the excipient affected the nature of the solid-water interactions; this resulted in varying process times. NIR moisture measurement combined with temperature and humidity measurements provides a tool for the control of water during fluid bed granulation.

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Objectives Pharmacy automation is increasing in hospitals. The aim of this systematic review was to identify and evaluate the literature on automated unit dose dispensing systems (UDDS) producing individually packaged and labelled drugs for inpatients. Methods The search was conducted on eight electronic databases, including Scopus, Medline Ovid, and Cinahl, and limited to peer reviewed articles with English abstracts published 2000-2020. Studies were included in the review if drug dispensing was performed by an automated UDDS where individually packaged and labelled unit doses were subsequently assembled patient specifically for inpatients. All outcomes related to UDDS functionality were included with specific interest in medication safety, cost-efficiency and stock management. Outcomes were categorised and results synthesised qualitatively. Results 664 publications were screened, one article identified manually, resulting in eight included articles. Outcomes of the studies were categorised as medication administration errors (MAEs), dispensing errors, costs and cost-effectiveness. Studies showed that automated UDDS reduced significantly MAEs of inpatients compared with traditional ward stock system (WSS), especially when UDs were dispensed patient specifically by unit dose dispensing robot. Patient specific drug dispensing with automated UDDS was very accurate. Of three different automated medication systems (AMSs), patient specific AMS (psAMS) was the most cost-effective and complex AMS (cAMS) the most expensive system across all error types due to the higher additional investments and operation costs of automated dispensing cabinets (ADCs). None of the studies investigated the impact on the medication management process such as efficiency, costs and stock management as primary outcome. Conclusions UDDS improved patient safety. However, automation is a costly investment and the implementation process is complex and time consuming. Further controlled studies are needed on the clinical and economical outcomes of automated UDDS to produce reliable knowledge for hospital decision makers on the cost-benefit of the investment and to support decision making.