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Artificial intelligence (AI) has developed into a powerful tool that employs human knowledge to swiftly resolve complex issues. Significant advancements in computer learning and artificial intelligence present a revolutionary opportunity for pharmaceutical formulation, drug dis-covery, and dosage form testing. AI algorithms would analyze a tremendous amount of biological reference data, such as proteomics and genomes, to assist researchers in identifying target diseases and predicting their possible interactions with proposed approaches to treatment. Just such focused and efficient drug development significantly augments the likelihood of acquiring drug approvals. AI may add, at the same time, develop costs and streamline research and development processes. Clas-sical machine learning techniques help not only in designing the experiment but also significantly in predicting the pharmacokinetics and toxicity of new drugs. This ability reduces the need for expen-sive, time-consuming animal testing by selection with optimization of lead compounds. Personalized medical strategies based on actual patient data assessments by algorithms such as those of AI may benefit patients through increased treatment adherence and outcomes. The review covers many ap-plications of AI for process optimization, testing, drug delivery dosage form design, and drug discov-ery. This study underlines the benefits brought by numerous types of techniques based on AI in phar-maceutical technology. However, there are exciting prospects to enhance patient care and medication development processes because of the pharmaceutical industry's continuous investment in and re-search into AI.
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http://dx.doi.org/10.2174/0115701638388052250724070324 | DOI Listing |
J Orthop Res
September 2025
Department of Kinesiology, College of Health Sciences, University of Rhode Island, Kingston, Rhode Island, USA.
Arthroplasty surgery is a common and successful end-stage intervention for advanced osteoarthritis. Yet, postoperative outcomes vary significantly among patients, leading to a plethora of measures and associated measurement approaches to monitor patient outcomes. Traditional approaches rely heavily on patient-reported outcome measures (PROMs), which are widely used, but often lack sensitivity to detect function changes (e.
View Article and Find Full Text PDFBMC Nurs
September 2025
Institute of Business Administration and Business Informatics, IT for the Caring Society, University of Hildesheim, Hildesheim, Germany.
Background: As populations age, informal caregivers play an increasingly vital role in long-term care, with 80% of care provided by family members in Europe. However, many individuals do not immediately recognize themselves as caregivers, especially in the early stages. This lack of awareness can increase physical and emotional stress and delay access to support services.
View Article and Find Full Text PDFGenome Biol
September 2025
Institute of Translational Medicine, Zhejiang University School of Medicine, Zhejiang, Hangzhou, 310029, China.
Metagenomic analyses of microbial communities have unveiled a substantial level of interspecies and intraspecies genetic diversity by reconstructing metagenome-assembled genomes (MAGs). The MAG database (MAGdb) boasts an impressive collection of 74 representative research papers, spanning clinical, environmental, and animal categories and comprising 13,702 paired-end run accessions of metagenomic sequencing and 99,672 high quality MAGs with manually curated metadata. MAGdb provides a user-friendly interface that users can browse, search, and download MAGs and their corresponding metadata information.
View Article and Find Full Text PDFBariatric surgery is an effective treatment for morbid obesity, but patient outcomes differ greatly because of a variety of phenotypes, comorbidities, and postoperative adherence. In bariatric care, artificial intelligence (AI) and machine learning (ML) are becoming revolutionary tools because traditional predictive models based on BMI and demographic variables are unable to account for these complexities. To put it simply, AI is a branch of computer science that enables machines to perform tasks that typically require human intelligence.
View Article and Find Full Text PDFNeurol Sci
September 2025
Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
The rapid evolution of digital tools in recent years after COVID-19 pandemic has transformed diagnostic and therapeutic practice in neurology. This shift has highlighted the urgent need to integrate digital competencies into the training of future specialists. Key innovations such as telemedicine, artificial intelligence, and wearable health technologies have become central to improving healthcare delivery and accessibility.
View Article and Find Full Text PDF