Artificial intelligence in the field of pharmacy practice: A literature review

Exploratory Research in Clinical and Social Pharmacy, Journal Year: 2023, Volume and Issue: 12, P. 100346 - 100346

Published: Oct. 21, 2023

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 applications field of practice. The incorporation technologies provides pharmacists with tools systems that help them make accurate evidence-based clinical decisions. By using algorithms Machine Learning, can analyze large volume data, medical records, laboratory results, profiles, aiding identifying drug-drug interactions, assessing safety efficacy medicines, making informed recommendations tailored individual requirements. Various models have been developed predict detect adverse drug events, assist decision support medication-related decisions, automate dispensing processes community pharmacies, optimize dosages, adherence through smart technologies, prevent errors, provide therapy services, telemedicine initiatives. incorporating into health care professionals augment their decision-making patients personalized allows for greater collaboration between different healthcare services provided single patient. For patients, may be useful tool providing guidance on how when take medication, education, promoting know where obtain most cost-effective best communicate professionals, monitoring wearables devices, everyday lifestyle guidance, integrate diet exercise.

Language: Английский

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Forecasting the impact of artificial intelligence on clinical pharmacy practice

JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 13, 2025

Abstract There is a need to understand contemporary scientific advances as clinical pharmacy evolves. One rapidly expanding area artificial intelligence (AI), which has grown significantly over the past year because of public availability large language models. This commentary reviews published literature describing and evaluating applications AI each aspect medication use process forecasts potential future roles for in practice. Potential challenges implementation are also described.

Language: Английский

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Management of drug supply chain information based on “artificial intelligence + vendor managed inventory” in China: perspective based on a case study

Frontiers in Pharmacology, Journal Year: 2024, Volume and Issue: 15

Published: July 16, 2024

Objectives To employ a drug supply chain information system to optimize management practices, reducing costs and improving efficiency in financial asset management. Methods A digital artificial intelligence + vendor managed inventory (AI+VMI)-based for hospitals has been established. The enables digitalization intelligentization of purchasing plans, reconciliations, consumption settlements while generating purchase, sales, reports as well various query reports. indicators evaluating the effectiveness before after project implementation encompass loss reporting, discrepancies, inter-hospital medication retrieval frequency, expenditure, cloud pharmacy service utilization. Results successful this reduced hospital rate approximately 20% decreased average annual error from 0.425‰ 0.025‰, significantly boosting by 42.4%. It also minimized errors application, allocation, distribution increasing adverse reaction Drug across multiple districts standardized, leading improved access medicines enhanced patient satisfaction. Conclusion AI+VMI improves ensuring security, costs, enhancing safety management, elevating professional competence level pharmaceutical personnel.

Language: Английский

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Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation

Frontiers in Digital Health, Journal Year: 2025, Volume and Issue: 7

Published: March 4, 2025

Early diagnosis and accurate prognosis play a pivotal role in the clinical management of cancer preventing cancer-related mortalities. The burgeoning population Asia general South Asian countries like India particular pose significant challenges to healthcare system. Regrettably, demand for services far exceeds available resources, resulting overcrowded hospitals, prolonged wait times, inadequate facilities. scarcity trained manpower rural settings, lack awareness low penetrance screening programs further compounded problem. Artificial Intelligence (AI), driven by advancements machine learning, deep natural language processing, can profoundly transform underlying shortcomings industry, more populous nations India. With about 1.4 million cases reported annually 0.9 deaths, has burden that surpassed several nations. Further, India's diverse large ethnic is data goldmine research. Under these circumstances, AI-assisted technology, coupled with digital health solutions, could support effective oncology care reduce economic GDP loss terms years potential productive life lost (YPPLL) due stupendous burden. This review explores different aspects management, such as prevention, diagnosis, precision treatment, prognosis, drug discovery, where AI demonstrated promising results. By harnessing capabilities research, professionals enhance their ability diagnose cancers at earlier stages, leading treatments improved patient outcomes. continued research development, transformative mitigating posed growing advancing fight against Moreover, AI-driven technologies assist tailoring personalized treatment plans, optimizing therapeutic strategies, supporting oncologists making well-informed decisions. However, it essential ensure responsible implementation address ethical privacy concerns associated using healthcare.

Language: Английский

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Application of Internet Hospitals in the Disease Management of Patients With Ulcerative Colitis: Retrospective Study

Journal of Medical Internet Research, Journal Year: 2025, Volume and Issue: 27, P. e60019 - e60019

Published: March 18, 2025

Background Ulcerative colitis (UC) is a chronic disease characterized by frequent relapses, requiring long-term management and consuming substantial medical social resources. Effective of UC remains challenging due to the need for sustainable remission strategies, continuity care, access services. Intelligent diagnosis refers use artificial intelligence–driven algorithms analyze patient-reported symptoms, generate diagnostic probabilities, provide treatment recommendations through interactive tools. This approach could potentially function as method management. Objective study aimed data from both physical hospitals internet hospitals, highlighting potential benefits intelligent service model offered hospitals. Methods We collected on visits patients with Department Gastroenterology at Tianjin Medical University General Hospital. A total 852 were included between July 1, 2020, June 31, 2023. Statistical methods, including chi-square tests categorical variables, t continuous rank-sum visit numbers, used evaluate preferences expenses UC. Results found that presented different models distribution needs patient groups. Patients who chose focused consultation prescription medication (3295/3528, 93.40%). Patients’ gradually shifted web-based services provided Over time, 58.57% (270/461) either or combination offline treatment. The number in modes was highest (mean 13.83, SD 11.07), younger inclined (49.66%>34.71%). In addition, compared there no difference testing fees examination but medicine lower. Conclusions demonstrates managing UC, feasibility, accessibility, convenience, economics.

Language: Английский

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AI-Driven Advancements in Pharmacy: Enhancing Drug Discovery, Optimization and Clinical Decision-Making

Published: March 24, 2025

Artificial Intelligence (AI) has emerged as a transformative force in pharmacy, reshaping drug discovery, medication management, and patient care. The integration of AI-driven methodologies, including machine learning, natural language processing (NLP), computer vision, predictive analytics, revolutionized pharmaceutical operations, enhancing efficiency, accuracy, safety. systems facilitate personalized medicine, clinical decision support, automated dispensing, pharmacovigilance, thereby minimizing errors optimizing treatment regimens. This paper explores the historical evolution, applications, benefits, challenges associated with AI pharmacy. adoption analytics aids adverse reaction detection, risk stratification, optimization, while support enhance accuracy regulatory compliance. Deep learning supervised models are extensively employed discovery development, significantly accelerating identification therapeutic candidates repurposing existing medications. Moreover, AI-based inventory management supply chain forecasting improve logistics, reducing waste ensuring optimal availability. Despite its vast potential, implementation pharmacy is accompanied by ethical, regulatory, financial challenges, data privacy concerns, algorithmic bias, workforce displacement, need for continuous systems. complexity decision-making, particularly "black box" problem, raises concerns regarding transparency interpretability practice. Regulatory frameworks, such GDPR FDA guidelines, continue to evolve address AI’s ethical safety implications applications. As technology advances, role will expand further, leading improved safety, cost reduction, enhanced engagement. By integrating unsupervised models, alongside IoT-driven monitoring systems, industry poised transition towards more data-driven, predictive, patient- centered approach healthcare. provides comprehensive examination current potential applications emphasizing necessity interdisciplinary collaboration, governance, ongoing research fully harness capabilities.

Language: Английский

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Optimization and impact of an evidence-based pre-audit prescription decision system in primary healthcare settings

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 14, 2025

Objective Analyze the operation mode of prescription pre-audit intelligent decision system in a county-level hospital, evaluate its intervention effects on outpatient and emergency operations, thus providing references for similar hospitals to carry out promote rational drug use. Methods Utilizing evidence-based approaches, rule modifications have been refined synergized with AI-driven decision-making analytics examine operational framework system. Additionally, retrospectively analyze types levels problems triggered by prescriptions from October 2022 August 2023, as well rationality Results According clinical unreasonable finely classified into different according severity problems. From number triggering issues such indications, dosage, special populations, compatibility, administration, contraindications showed decreasing trend compared before intervention. For example, routes administration decreased 1,745 20, contraindicated 1,399 16. The Level 5 alerts 5.609% 1.793% compliance rate increased 92.20% 95.98%. Conclusion enhances patient safety promotes However, requires fine-tuning continuous improvement library effectively validate improve accuracy. In future, integrating big data, artificial intelligence other technologies secondary development will be model worthy consideration. addition, promoting this medical federation establish regional review further high-quality pharmaceutical services.

Language: Английский

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Enhancing clinical decision-making: a scenario-based patient simulation study using QR code-based algorithms for the management of acute intoxication-type inborn errors of metabolism

The Turkish Journal of Pediatrics, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 13

Published: May 3, 2025

Background. Acute intoxication-type inborn errors of metabolism (IEMs) present significant challenges in pediatric care. Prompt recognition and appropriate management are essential to prevent serious complications reduce mortality. Recent studies increasingly highlight the use quick response (QR) code-based tools facilitate rapid intervention, particularly emergency departments primary healthcare settings. In this study, effectiveness a newly developed QR algorithm, designed support accurate effective acute IEMs and, indirectly, sequelae mortality, was evaluated for first time. Methods. This study included 113 residents from two centers, one with (Group 1, n=77) without 2, n=36) mandatory rotation. All participants completed scenario-based simulation 10 clinical questions on standardized patient case metabolism, both before after using algorithm. The accordance international guidelines, accessed via mobile devices. Pre- post-intervention responses were compared statistical tests. code guiding simulated analyzed. Results. Of participants, 73 (64.6%) female 40 (35.4%) male; median age 28.0 years. Forty-two (37.2%) had previous experience unit. Correct identification urgent treatment increased 77.9% 97.3% (p

Language: Английский

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Application of “Internet +” pharmaceutical consultation services in psychiatric hospital during the epidemic

Asian Journal of Psychiatry, Journal Year: 2023, Volume and Issue: 82, P. 103532 - 103532

Published: Feb. 24, 2023

Language: Английский

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AI-driven smart pharmacology

Intelligent Pharmacy, Journal Year: 2023, Volume and Issue: 1(4), P. 179 - 182

Published: Aug. 29, 2023

With the progress of digital technology and innovative drug R&D, machine learning data-driven algorithms have been increasingly used to support core work pharmaceutical areas such as new discovery, reuse supervision, etc.1 A concept "Smart Pharmacology" has gradually grown into a system with rich connotations comprehensive coverage, related applications industrial chain high prospects for development. The so-called Pharmacology " mainly uses big data, cloud computing, AI, IoT, 5G, Blockchain other forefront technologies provide whole-process, information-based, intelligence-driven solutions various scenarios in pharmacy sectors, including development, molecular design, hospital management, clinical decision support, modernization traditional medicine, informatization, regulation broad areas, wide range covering production, supply, circulation, procurement, allocation monitoring. In fact, emergency smart pharmacology provides optimized path modernizing whole life cycle management drugs instills vitality development modern pharmacy.

Language: Английский

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