Electroactive Polymers for On-Demand Drug Release.

Conductive materials have played a significant role in advancing society into the digital era. Such materials are able to harness the power of electricity and are used to control many aspects of daily life. Conductive polymers (CPs) are an emerging group of polymers that possess metal-like conductivity yet retain desirable polymeric features, such as processability, mechanical properties, and biodegradability. Upon receiving an electrical stimulus, CPs can be tailored to achieve a number of responses, such as harvesting energy and stimulating tissue growth. The recent FDA approval of a CP-based material for a medical device has invigorated their research in healthcare. In drug delivery, CPs can act as electrical switches, drug release is achieved at a flick of a switch, thereby providing unprecedented control over drug release. In this review, recent developments in CP as electroactive polymers for voltage-stimuli responsive drug delivery systems are evaluated. The review demonstrates the distinct drug release profiles achieved by electroactive formulations, and both the precision and ease of stimuli response. This level of dynamism promises to yield "smart medicines" and warrants further research. The review concludes by providing an outlook on electroactive formulations in drug delivery and highlighting their integral roles in healthcare IoT.

Virtually Possible: Enhancing Quality Control of 3D-Printed Medicines with Machine Vision Trained on Photorealistic Images.

Three-dimensional (3D) printing is an advanced pharmaceutical manufacturing technology, and concerted efforts are underway to establish its applicability to various industries. However, for any technology to achieve widespread adoption, robustness and reliability are critical factors. Machine vision (MV), a subset of artificial intelligence (AI), has emerged as a powerful tool to replace human inspection with unprecedented speed and accuracy. Previous studies have demonstrated the potential of MV in pharmaceutical processes. However, training models using real images proves to be both costly and time consuming. In this study, we present an alternative approach, where synthetic images were used to train models to classify the quality of dosage forms. We generated 200 photorealistic virtual images that replicated 3D-printed dosage forms, where seven machine learning techniques (MLTs) were used to perform image classification. By exploring various MV pipelines, including image resizing and transformation, we achieved remarkable classification accuracies of 80.8%, 74.3%, and 75.5% for capsules, tablets, and films, respectively, for classifying stereolithography (SLA)-printed dosage forms. Additionally, we subjected the MLTs to rigorous stress tests, evaluating their scalability to classify over 3000 images and their ability to handle irrelevant images, where accuracies of 66.5% (capsules), 72.0% (tablets), and 70.9% (films) were obtained. Moreover, model confidence was also measured, and Brier scores ranged from 0.20 to 0.40. Our results demonstrate promising proof of concept that virtual images exhibit great potential for image classification of SLA-printed dosage forms. By using photorealistic virtual images, which are faster and cheaper to generate, we pave the way for accelerated, reliable, and sustainable AI model development to enhance the quality control of 3D-printed medicines.

Fabrication and Characterization of Fast-Dissolving Films Containing Escitalopram/Quetiapine for the Treatment of Major Depressive Disorder.

Major depressive disorder (MMD) is a leading cause of disability worldwide. Approximately one-third of patients with MDD fail to achieve response or remission leading to treatment-resistant depression (TRD). One of the psychopharmacological strategies to overcome TRD is using a combination of an antipsychotic as an augmenting agent with selective serotonin reuptake inhibitors (SSRIs). Among which, an atypical antipsychotic, quetiapine (QUE), and an SSRI, escitalopram (ESC), were formulated as a fixed-dose combination as a fast-dissolving film by coaxial electrospinning. The resultant fiber's morphology was studied. SEM images showed that the drug-loaded fibers were smooth, un-beaded, and non-porous with a fiber diameter of 0.9 ± 0.1 µm, while the TEM images illustrated the distinctive layers of the core and shell, confirming the successful preparation of these fibers. Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) studies confirmed that both drugs were amorphously distributed within the drug-loaded fibers. The drug-loaded fibers exhibited a disintegration time of 2 s, which accelerated the release of both drugs (50% after 5 min) making it an attractive formulation for oral mucosal delivery. The ex vivo permeability study demonstrated that QUE was permeated through the buccal membrane, but not ESC that might be hindered by the buccal epithelium and the intercellular lipids. Overall, the developed coaxial fibers could be a potential buccal dosage form that could be attributed to higher acceptability and adherence among vulnerable patients, particularly mentally ill patients.

A Non-Nutritive Feeding Intervention Alters the Expression of Efflux Transporters in the Gastrointestinal Tract.

Intestinal interactions with nutrients, xenobiotics and endogenous hormones can influence the expression of clinically relevant membrane transporters. These changes in the gastrointestinal (GI) physiology can in turn affect the absorption of numerous drug substrates. Several studies have examined the effect of food on intestinal transporters in male and female humans and animal models. However, to our knowledge no studies have investigated the influence of a non-nutritive fibre meal on intestinal efflux transporters and key sex and GI hormones. Here, we show that a fibre meal increased the acute expression of P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), and multidrug-resistance-associated protein-2 (MRP2) in small intestinal segments in both male and female Wistar rats. Enzyme-linked immunosorbent assays were used for the protein quantification of efflux transporters and hormonal plasma concentration. In male rats, the fibre meal caused the plasma concentration of the GI hormone cholecystokinin (CCK) to increase by 75% and the sex hormone testosterone to decrease by 50%, whereas, in contrast, the housing food meal caused a decrease in CCK by 32% and testosterone saw an increase of 31%. No significant changes in the hormonal concentrations, however, were seen in female rats. A deeper understanding of the modulation of efflux transporters by sex, food intake and time can improve our understanding of inter- and intra-variability in the pharmacokinetics of drug substrates.