{"title":"The impact of artificial intelligence on remote healthcare: Enhancing patient engagement, connectivity, and overcoming challenges","authors":"Udit Chaturvedi, Shikha Baghel Chauhan, Indu Singh","doi":"10.1016/j.ipha.2024.12.003","DOIUrl":"10.1016/j.ipha.2024.12.003","url":null,"abstract":"<div><div>The incorporation of advanced telemedicine technologies is helping artificial intelligence transform remote healthcare in the enhancement of patient care, diagnostics, monitoring, and overall medical treatment. This review examines how AI has transformed virtual healthcare with regard to patient engagement and connectivity, real-time monitoring of health status, and the accuracy of diagnosis. Key applications of AI, such as AI-enabled diagnostic systems, predictive analytics, and teleconsultation platforms, are reviewed for their strengths in overcoming the limitations of the traditional models of remote healthcare. This review consists of case studies on the applications of AI in different healthcare domains, such as cardiac monitoring, diabetes management, mental health teletherapy, and dermatology. It also looks into the ethical and regulatory challenges that arise, including bias in AI, data privacy, and accountability, in a way that emphasizes the necessity for robust regulatory frameworks in safeguarding patient safety. Future directions for AI innovation include such emerging technologies as 5G, blockchain, and IoMT, among others, that “will usher in a new era of remote healthcare delivery.”</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 5","pages":"Pages 323-329"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145195982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Opportunities and challenges of machine learning in anticaner drug therapies","authors":"Miao Chunlei , HuangFu Rui , Chen Yuan , Wu Shikui , Ping Yaodong","doi":"10.1016/j.ipha.2025.02.004","DOIUrl":"10.1016/j.ipha.2025.02.004","url":null,"abstract":"<div><div>Antitumor drug therapies encounter substantial costs and intricate challenges, imposing a financial strain on patients and potentially leading to serious adverse effects. These issues have prompted a shift towards personalized precision medicine, although the increased workload for clinicians limits its full implementation. Machine learning (ML) offers innovative solutions to these challenges. By effectively integrating and analysing large clinical datasets, ML can develop models to predict potential treatment-related risks for patients and optimize dosing regimens, thereby improving efficacy and reducing adverse effects. Additionally, ML can evaluate drug efficacy, providing empirical support for personalized treatments. This review highlights the research progress in ML for antitumor drug therapies and examines its crucial role in advancing personalized precision medicine. It is expected that ML will deliver more accurate, efficient, and cost-effective treatment options for patients while providing strong support for clinicians in refining treatment decisions, making it an essential tool in cancer therapy.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 5","pages":"Pages 336-341"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145196025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A review on intervention of AI in pharmaceutical sector: Revolutionizing drug discovery and manufacturing","authors":"Vijeth N. Bhat , Swati Bharati , Chellampillai Bothiraja , Jaiprakash Sangshetti , Vinod Gaikwad","doi":"10.1016/j.ipha.2025.04.001","DOIUrl":"10.1016/j.ipha.2025.04.001","url":null,"abstract":"<div><div>Artificial intelligence (AI) is designed to mimic human intelligence in machines. The growth of information technology and advancement in the computing power of computers provided a great platform for progress in many pharmaceutical industry and healthcare sectors. Leading to the consolidation of the pharmaceutical, and healthcare industries with AI companies. AI is used in various departments of the pharmaceutical sector such as drug discovery, development, target identification, manufacturing process, dosage design, clinical trial design, and many more. There are several challenges and limitations of AI that must be addressed by the pharmaceutical industry before its adoption and successful integration into various processes. The present article is focused on Artificial Neural Networks in the pharmaceutical sector, Drug design and discovery, drug repurposing, research and development, pharmaceutical product development, manufacturing process, quality assurance and quality controls, and some challenges and prospects of AI.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 5","pages":"Pages 342-349"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145196026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joyner David Anaya Miranda , Maricela Rojas Canchala , Carlos Alberto Gómez Mercado
{"title":"Identifying potentiators of adverse reactions to antiretroviral drugs in a primary care model","authors":"Joyner David Anaya Miranda , Maricela Rojas Canchala , Carlos Alberto Gómez Mercado","doi":"10.1016/j.ipha.2025.02.003","DOIUrl":"10.1016/j.ipha.2025.02.003","url":null,"abstract":"<div><h3>Introduction</h3><div>Adverse drug reactions (ADRs) in Antiretroviral Treatment (ART) are influenced by multiple potentiators related to the patient, the disease, the drug, the environment and medical treatment, these ADRs are highly prevalent and are identified as an important risk factor that predisposes patients to ADRs. It was considered necessary to determine the demographic, social, and clinical factors associated with ADRs from antiretrovirals in HIV-positive patients, who were treated by the specialized comprehensive care program in a primary health care model.</div></div><div><h3>Methodology</h3><div>Observational, cross-sectional, analytical, and retrospective study with a population of patients on antiretroviral therapy in a primary care program. The outcome evaluated was adverse drug reactions vs. sociodemographic, pharmacological and clinical factors. For the statistical analysis, univariate, bivariate and multivariate analyses were performed, where a multiple binary logistic regression was used for explanatory purposes.</div></div><div><h3>Results</h3><div>A total of 5406 records of patients with antiretroviral therapy were analyzed, the prevalence of ADR was 16.68%, the multivariate analysis showed that the variables that increase the probability of ADR are age, education, area of residence, pharmacological group, HDL cholesterol levels, adherence, persistence, change of two or more times of ARV and treatment time.</div></div><div><h3>Conclusion</h3><div>Antiretrovirals, as well as the risk factors that are mainly associated with the occurrence of ADRs in this study, contribute to health professionals at all levels to anticipate, identify and minimize ADR, as well as to understand the need for close follow-up and monitoring to avoid the occurrence of serious ADRs.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 5","pages":"Pages 330-335"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145196024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Capitalization of digital healthcare: The cornerstone of emerging medical practices","authors":"Subhajit Hazra, Kundan Singh Bora","doi":"10.1016/j.ipha.2024.12.002","DOIUrl":"10.1016/j.ipha.2024.12.002","url":null,"abstract":"<div><h3>Background</h3><div>The digital healthcare sector in India is rapidly transforming, driven by strategic government initiatives and technological advancements. In 2020, the market was valued at approximately $1.5 billion and is projected to grow at a compound annual growth rate of ∼25% over the next five years.</div></div><div><h3>Methodology</h3><div>The study employed a descriptive and analytical approach, reviewing existing literature and data on the applications and implications of AI, mHealth, and GIS technologies in healthcare.</div></div><div><h3>Result</h3><div>The article highlighted the rapid growth of India's digital health market, driven by the adoption of telemedicine, mobile health, and electronic health records, alongside increased investments and internet penetration. Additionally, it also raised concerns about bias, transparency, and accountability in these technologies, urging the development of robust digital infrastructure, including Digital Health IDs, Health Facility Registries, and Healthcare Professionals Registries, as well as policy changes like the effective implementation of Personal Data Protection Bill and updates to the Information Technology Act.</div></div><div><h3>Conclusion</h3><div>India's healthcare market is at a critical juncture, where effective management of the ongoing digital transformation can vastly improve access and outcomes for millions. By tackling current challenges and embracing technological advancements, India could set a global standard in digital healthcare, ensuring equitable, high-quality care for all citizens, regardless of location or socio-economic status. The vision of a fully integrated digital healthcare system is not just possible but an impending reality that, with the right strategies and collaborations, could be realized within the next decade.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 5","pages":"Pages 309-322"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145195981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Extracellular vesicles as carriers for protein and peptide therapeutics delivery: A review","authors":"Yohannes Mengesha, Mesay Wondaya, Mulualem Workye, Lielet Belete","doi":"10.1016/j.ipha.2025.05.001","DOIUrl":"10.1016/j.ipha.2025.05.001","url":null,"abstract":"<div><div>Protein and peptide-based therapeutics hold immense potential for treating various diseases, including cancer, neurodegenerative disorders, and metabolic conditions. However, rapid degradation, poor bioavailability, short half-life, and early clearance limit their clinical application. Several protein and peptide modifications and drug delivery systems (DDS) tested including enzyme inhibitors, chemical modification and conventional nanoparticles have limitations like immune Reponses, extracellular vesicles (EVs), present a good solution to overcome this drawbacks. EVs have gained attention as novel delivery systems for protein and peptide therapeutics owing to their small size, biocompatibility, intrinsic targeting capabilities, lower immunogenicity, and ability to protect cargo from enzymatic degradation. EVs have demonstrated promising results in preclinical studies by enhancing the uptake, loading, penetration, and targeted release of protein/peptide cargos for conditions such as cancer, diabetes, and microbial infections. Additionally, they can serve as carriers for targeting peptides, enabling the delivery of synthetic drugs and genome-editing tools. This review explores the potential of EVs as drug delivery systems (DDS) for protein and peptide drugs, focusing on their advantages and characteristics, engineering and encapsulation, emerging EV and EV-cargo characterization techniques, release, and efficacy in overcoming the limitations of protein- and peptide-based delivery systems. The review also addresses challenges and future perspectives in translating EV-based protein and peptide delivery systems into clinical practice.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 5","pages":"Pages 350-367"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145196027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Banhishikha Kar , Beduin Mahanti , Ayan Kumar Kar , Subhabrota Majumdar
{"title":"Nanoliposome as a carrier for topical delivery of oxymetazoline hydrochloride: In-vitro assessment and in-vivo anti-inflammatory potential","authors":"Banhishikha Kar , Beduin Mahanti , Ayan Kumar Kar , Subhabrota Majumdar","doi":"10.1016/j.ipha.2024.09.006","DOIUrl":"10.1016/j.ipha.2024.09.006","url":null,"abstract":"<div><div>The present investigation on nanoliposome infused with oxymetazoline hydrochloride was fabricated with phosphatidylcholine and cholesterol to effectively deliver the drug to the skin. Oxymetazoline hydrochloride evidence to show anti-inflammatory characteristics. The drug produces pro-resolving lipoxins in accordance with the formation of anti-inflammatory 15(S)-hydroxy-eicosatetraenoic acid and the consequent reduction of pro-inflammatory lipid mediators such as leukotriene B4 which leads to the reduction in inflammation at the topical region. The oxymetazoline hydrochloride infused nanoliposomes were prepared by thin film lipid hydration method. The present research assessed the average particle size of different formulations ranges from 147.4 ± 0.77 nm to 371.7 ± 0.99 nm with polydispersity value ranging from 0.181 ± 0.02 to 0.392 ± 0.03. Furthermore, the zeta potentials ranging from −15.2 ± 0.25 mV to −30.5 ± 0.24 mV. The percentage of drug release at 12 h (Y1) has a <em>p</em>-value of 0.0073, entrapment efficiency (%) (Y2) has <em>p</em>-value of 0.0001 and particle size (nm) (Y3) has a <em>p</em>-value of 0.0480. Hence all the dependent responses found to be significant. This study exhibited small particle size distribution with consistent polydispersity index which ensure the monodispersed nature of the nanoliposomes. The satisfactory zeta potential value indicates the stability of formulation. The outcome of the study projected that oxymetazoline hydrochloride loaded nanoliposome have the potential to deliver drugs to specific regions with their high stability and predictable release at the target region.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 4","pages":"Pages 256-267"},"PeriodicalIF":0.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sarvananda Letchuman , H.D.T. Madhuranga , B.L.N.K. Madhurangi , Amal D. Premarathna , Muthupandian Saravanan
{"title":"Alkaloids unveiled: A comprehensive analysis of novel therapeutic properties, mechanisms, and plant-based innovations","authors":"Sarvananda Letchuman , H.D.T. Madhuranga , B.L.N.K. Madhurangi , Amal D. Premarathna , Muthupandian Saravanan","doi":"10.1016/j.ipha.2024.09.007","DOIUrl":"10.1016/j.ipha.2024.09.007","url":null,"abstract":"<div><div>Alkaloids, naturally occurring compounds in a diverse range of plant species (<em>Coffea</em> spp., <em>Erythroxylum coca</em>, <em>Cinchona</em> spp. etc.), hold vast potential for biological, medicinal, and pharmacological applications. As the global focus shifts towards natural therapeutic agents due to their lower toxicity compared to synthetic compounds, this review takes a novel approach by examining the ecological and molecular factors influencing the medicinal properties of alkaloids. Using a comparative analysis of alkaloid potency across various plant species, we explore how environmental factors, such as soil composition and climate, impact alkaloid concentration and efficacy. Additionally, this review highlights the synergistic potential of alkaloids when combined with other phytochemicals, offering new insights into more potent, multi-compound therapeutic formulations. We documented ten key medicinal properties, including antioxidant, anti-inflammatory, and anticancer effects, and delve into the molecular pathways through which alkaloids exert these benefits. By exploring alkaloids from under-researched plant species, we aim to broaden the scope of medicinal applications, particularly within the realm of personalized medicine, where alkaloid efficacy may vary based on genetic and pathological factors. This novel perspective emphasized the need for further research to optimize alkaloid extraction methods and assess their potential in personalized and combination therapies, ultimately paving the way for more effective natural treatments.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 4","pages":"Pages 268-276"},"PeriodicalIF":0.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yirui Wang , Xiaoling Wu , Li Tang , Yingjie Fei , Hengyu Guo , Yujun Wang , Wei Zhao , Siqian Zheng , Bowen Sun , Xia Wang
{"title":"Design representation of pain visualization coding","authors":"Yirui Wang , Xiaoling Wu , Li Tang , Yingjie Fei , Hengyu Guo , Yujun Wang , Wei Zhao , Siqian Zheng , Bowen Sun , Xia Wang","doi":"10.1016/j.ipha.2024.11.001","DOIUrl":"10.1016/j.ipha.2024.11.001","url":null,"abstract":"<div><div>This paper proposes an innovative method for visualizing pain by transforming complex pain metrics into intuitive visual codes, making pain expression more precise and easier to understand and empathize with. The system categorizes pain by type, source, intensity, and range, employing creative visual elements to vividly represent these categories. This design not only enhances the clarity and accuracy of pain communication but also bridges the gap between patient experience and medical interpretation, providing a more human-centered solution in the healthcare field.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"3 4","pages":"Pages 304-307"},"PeriodicalIF":0.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}