ReviewExploratory research in clinical and social pharmacy2023
Artificial intelligence in the field of pharmacy practice: A literature review.
Review in Exploratory research in clinical and social pharmacy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
62 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Medication experience of aged patients and their family caregivers during transitions of care: a qualitative meta-synthesis.International journal of qualitative studies on health and well-being · 2025Pooled it
- Medication Errors in Saudi Arabian Hospital Settings: A Systematic Review.Medicina (Kaunas, Lithuania) · 2024Pooled it
- Translation, cultural adaptation, and validation of the perceived Artificial Intelligence Literacy Questionnaire-6 (PAILQ-6) in Arabic-speaking pharmacists: A cross-sectional methodological study.Exploratory research in clinical and social pharmacy · 2026Article
- Governing AI for Pharmacovigilance in Low-Income Countries: Systems Perspective.Journal of medical Internet research · 2026Article
- Interaction of artificial intelligence, mental disorders, and diverse data modalities: Potential treatment management based on the "method-disease-data" axis.Neural regeneration research · 2026Article
- Integration of artificial intelligence applications in clinical pharmacy services: A scoping review.Future healthcare journal · 2026Review
- In defence of the drug, two hearts, one profession: Reintegrating medicines expertise and patient-centred care in pharmacy's professional identity.Exploratory research in clinical and social pharmacy · 2026Article
- The Risks to Patients Associated with Using Artificial Intelligence Tools in Pharmacy Practice: A Scoping Review.Pharmacy (Basel, Switzerland) · 2026Review
- Prescription Analysis in the Digital Era: Comparing Artificial Intelligence-Based Versus Manual Approaches.Cureus · 2026Article
- Accuracy and Effectiveness of AI-Powered Systems in Patient Counseling, Education, and Management in Optometry and Related Eye-Care Settings: A Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
- Pharmaceutical Compounding as a Pillar of Personalized Oncology: Current Applications, Emerging Technologies, and Future Perspectives.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance.Journal of medical Internet research · 2026Article
- Preliminary evaluation of an AI-enhanced simulated interprofessional learning intervention for pharmacy students: a mixed-methods pilot study.BMC medical education · 2026Article
- Future pharmacists in the age of Artificial Intelligence: a mixed-methods study of first-year students in Vietnam.BMC medical education · 2026Article
- Evaluating Large Language Models for Food Supplement Development: A Case Study in Glycemic Control.Nutrients · 2026Article
- Polypharmacy in HIV: Rethinking what counts and why it matters.HIV medicine · 2026Review
- Leveraging Artificial Intelligence-Based Applications to Remove Disruptive Factors from Pharmaceutical Care: A Quantitative Study in Eastern Romania.Pharmacy (Basel, Switzerland) · 2026Article
- Emerging advancements and expanding technological scope of education and practices in pharmacy and pharmaceutical sciences.BioImpacts : BI · 2026Review
- What leads to medication errors in polish hospitals from the perspectives of nurses? a multicenter cross-sectional survey.Frontiers in pharmacology · 2026Article
- Artificial intelligence in pharmacy practice: pharmacists' perceptions and concerns toward implementation.Frontiers in digital health · 2026Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is a transformative technology used in various industrial sectors including healthcare. In pharmacy practice, AI has the potential to significantly improve medication management and patient care. This review explores various AI applications in the field of pharmacy practice. The incorporation of AI technologies provides pharmacists with tools and systems that help them make accurate and evidence-based clinical decisions. By using AI algorithms and Machine Learning, pharmacists can analyze a large volume of patient data, including medical records, laboratory results, and medication profiles, aiding them in identifying potential drug-drug interactions, assessing the safety and efficacy of medicines, and making informed recommendations tailored to individual patient requirements. Various AI models have been developed to predict and detect adverse drug events, assist clinical decision support systems with medication-related decisions, automate dispensing processes in community pharmacies, optimize medication dosages, detect drug-drug interactions, improve adherence through smart technologies, detect and prevent medication errors, provide medication therapy management services, and support telemedicine initiatives. By incorporating AI into clinical practice, health care professionals can augment their decision-making processes and provide patients with personalized care. AI allows for greater collaboration between different healthcare services provided to a single patient. For patients, AI may be a useful tool for providing guidance on how and when to take a medication, aiding in patient education, and promoting medication adherence and AI may be used to know how and where to obtain the most cost-effective healthcare and how best to communicate with healthcare professionals, optimize the health monitoring using wearables devices, provide everyday lifestyle and health guidance, and integrate diet and exercise.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.