Monika Devi

Microemulsions are multifunctional complex colloidal dispersed systems with widely utilized applications in drug delivery systems and chemical engineering. The interwoven relationship within their compositional variables, like surfactants, oil-to-water ratios, and co-surfactant type, leads to highly nonlinear phase behaviors that are difficult to analyze using traditional empirical or mechanistic models. This narrative review mainly focuses on the emerging role of artificial neural networks (ANNs) in optimizing microemulsion systems. Initially, the current study contextualizes the physicochemical factors of microemulsions and identifies their computational bottlenecks in formulation and phase behavior predictions. The review then analyses the relevant neural network structures, including feed forward networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs), for assessing their applicability to high-dimensional regression and classification and, furthermore, to reduce experimental load in microemulsion research. One of the advancements of using ANN is that it can identify the ideal concentration of excipients for the desirable properties of emulsion. Case studies are addressed wherein neural networks have been tutored on experimental and simulated datasets to estimate the droplet size distribution, construct pseudo-ternary phase diagrams, and identify optimal formulation properties. In addition to that, emphasis is applied to model structural design, feature selection strategies, and model validation techniques. The study also considers the current obstacles, such as paucity of data availability, over-fitting, and the integration of expertise knowledge in the learning models. Looking forward to the next context, this review illustrates that artificial neural network-based approaches provide a scalable and adaptable computational framework for boosting innovation in microemulsion science.

Omeprazole, a widely prescribed proton pump inhibitor (PPI), is a cornerstone therapy for acid?related gastrointestinal disorders, including gastroesophageal reflux disease, peptic ulcer disease, and Zollinger–Ellison syndrome. While generally safe and effective, prolonged or inappropriate use has been linked to a spectrum of adverse drug reactions (ADRs). Common ADRs include headache, abdominal discomfort, nausea, diarrhea, and flatulence, which are usually mild and self?limiting. However, serious complications—such as Clostridioides difficile infection, interstitial nephritis, hypomagnesemia, vitamin B12 deficiency, bone fractures, hepatotoxicity, and severe cutaneous reactions—though rare, pose significant clinical challenges. Risk factors influencing ADR incidence include treatment duration, high dosage, advanced age, polypharmacy, comorbid conditions, and genetic polymorphisms in CYP2C19 metabolism, which alter drug bioavailability and efficacy. Clinical pharmacists play a crucial role in mitigating these risks through therapeutic optimization, monitoring of laboratory parameters, early identification of drug interactions, and patient education. Evidence?based deprescribing strategies and routine safety surveillance are essential to minimize preventable harm while preserving therapeutic benefit. This review highlights the clinical significance of omeprazole?associated ADRs from a pharmacist’s perspective, emphasizing the importance of rational prescribing, vigilant monitoring, and interdisciplinary collaboration in ensuring patient safety.