Intelligent Pharmacy最新文献

{"title":"A comprehensive review on nanocarriers as a targeted delivery system for the treatment of breast cancer","authors":"Amreen Fatima,&nbsp;Nazish Naseem,&nbsp;Md Faheem Haider,&nbsp;Md Azizur Rahman,&nbsp;Jyotiraditya Mall,&nbsp;Muhammad Sahil Saifi,&nbsp;Juber Akhtar","doi":"10.1016/j.ipha.2024.04.001","DOIUrl":"10.1016/j.ipha.2024.04.001","url":null,"abstract":"<div><p>Breast cancer is the most common malignant tumour in women worldwide, as well as the leading cause of death from malignant tumours. All across the world, the incidence of breast cancer is steadily rising. Although numerous drugs acting through various mechanisms of action are available in the market as conventional formulations for the treatment of breast cancer, they face significant challenges in terms of bioavailability, dosing, and associated adverse effects, which severely limit their therapeutic efficacy. Several studies have shown that nanocarriers can significantly improve the drug's bioavailability, reducing the need for frequent dosing and reducing the toxicity linked to high drug doses. The current review provides insight into the challenges associated with conventional breast cancer formulations and the need for oral nanoparticulate systems to overcome problems associated with conventional formulations. This review focuses on various topics, such as an in-depth analysis of potential anticancer drugs that have used nanocarrier technology to treat breast cancer successfully.</p></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 3","pages":"Pages 415-426"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949866X24000509/pdfft?md5=a3eeadab16ca3e22f4367865768d9436&pid=1-s2.0-S2949866X24000509-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140779014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of novel Anti-SARS-CoV-2 compounds by targeting nucleoprotein and envelope protein through homology modeling, docking simulations, ADMET, and molecular dynamic simulations with the MM/GBSA calculation","authors":"Emmanuel Israel Edache ,&nbsp;Adamu Uzairu ,&nbsp;Paul Andrew Mamza ,&nbsp;Gideon Adamu Shallangwa ,&nbsp;Muhammad Tukur Ibrahim","doi":"10.1016/j.ipha.2024.02.008","DOIUrl":"10.1016/j.ipha.2024.02.008","url":null,"abstract":"<div><p>The current prominent virus that induces severe acute respiratory syndrome is SARS-CoV-2. The incidence of COVID-19 cases is increasing, necessitating the immediate development of effective treatments. Our objective was to employ an in-silico approach to evaluate the effectiveness of conventional compounds against COVID-19's nucleoprotein and envelope protein. A docking simulation was performed on 9 compounds as SARS-coronavirus inhibitors using AMDock software. Anti-covid-19 activities were further evaluated for the compounds. Based on docking results, the binding affinity of \"N-(4-carbamoylphenyl)-8-cyclopropyl-7-(naphthalen-1-ylmethyl)-5-oxo-2,3-dihydro-5H-thiazolo[3,2-a]pyridine-3-carboxamide,” also called compound 36 in this research, was found to be −8.8 ​kcal/mol for the modeled envelope protein and −7.3 ​kcal/mol for the template envelope protein, while −10.1 ​kcal/mol for the modeled nucleocapsid proteins (NP) and −8.7 ​kcal/mol for the template nucleocapsid proteins (NP) of SARS-coronavirus, respectively. The ligand and control drug (ritonavir) with high docking scores were subjected to pharmacological screening, molecular dynamic simulations, and Molecular Mechanics-generalized Born Surface Area (MM/GBSA) calculations. Furthermore, the jobs of pharmacokinetics were assessed, and the outcomes acquired show that the proposed compound 36 includes great oral bioavailability and a capacity to diffuse through various organic boundaries. The protein-ligand complexes were subjected to dynamic simulation analyses with a re-enactment time of 10 ns, likewise, their free binding energy was inspected operating the MM/GBSA approach. The docking (MD simulation) results acquired emphasize the pivotal residues answerable for the protein-ligand interaction, giving an understanding of the method of association. The MD simulation analysis verifies the structural stability of the selected complexes during the MD trajectory, with minor changes detected. The MM/GBSA data show that compound 36 has the lowest free energy of −12.498 ​kcal/mol for EP and −57.5185 ​kcal/mol for NP proteins of SARS-coronavirus, confirming the molecular docking result. As a result, the identified chemical can be used to develop a new family of antiviral medications against SARS-coronavirus-2.</p></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 3","pages":"Pages 346-366"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949866X24000315/pdfft?md5=e4fb430040702a6716cc9c5c1cccdeef&pid=1-s2.0-S2949866X24000315-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139966509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revolutionizing drug discovery: The impact of artificial intelligence on advancements in pharmacology and the pharmaceutical industry","authors":"Seema Yadav ,&nbsp;Abhishek Singh ,&nbsp;Rishika Singhal ,&nbsp;Jagat Pal Yadav","doi":"10.1016/j.ipha.2024.02.009","DOIUrl":"10.1016/j.ipha.2024.02.009","url":null,"abstract":"<div><p>To create novel treatments and treat complex diseases, the pharmaceutical sector is essential. Drug discovery, however, is a time-consuming, pricey, and dangerous endeavor. Artificial intelligence (AI) has become a potent instrument that has transformed several industries, including healthcare, in recent years. This summary gives a general overview of how AI is expediting the creation of novel medicines, revolutionizing the pharmaceutical sector, and enabling drug discovery. The pharmaceutical sector is experiencing a drug discovery revolution because of AI. The drug discovery process is changing at different phases because of AI approaches like machine learning and deep learning. This abstract demonstrates how AI facilitates drug development through target identification, lead compound optimization, drug design, drug repurposing, and clinical trial enhancement. AI integration has the potential to hasten the creation of novel treatments, save costs, and improve patient outcomes. To fully realize the potential of AI in pharmaceutical research and development, issues relating to data accessibility, algorithm interpretability, and laws must be resolved.</p></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 3","pages":"Pages 367-380"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949866X24000327/pdfft?md5=16a7341794a2e4603b3115e396701380&pid=1-s2.0-S2949866X24000327-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140467171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chitosan fortified repaglinide gastro-retentive mucoadhesive microsphere with improved anti-diabetic attribute","authors":"Anil Pawar ,&nbsp;Pranjal Lohakane ,&nbsp;Ramdas Pandhare ,&nbsp;Popat Mohite ,&nbsp;Shubham Munde ,&nbsp;Sudarshan Singh ,&nbsp;Vijay Chidrawar","doi":"10.1016/j.ipha.2024.01.012","DOIUrl":"10.1016/j.ipha.2024.01.012","url":null,"abstract":"<div><p>Repaglinide (RPG) has a high rate of absorption from the gastrointestinal system after oral administration due to low log <em>P</em> value. Hence, in this study the inotropic gelation process was used to fabricate mucoadhesive microspheres of RPG using biodegradable polymers such as guar gum, chitosan, and fenugreek seed mucilage. The mucoadhesive microspheres were characterized and tested <em>in vitro</em> followed with oral glucose tolerance test on animals. Scanning electron microscopy images demonstrated that the fabricated microspheres were smooth and spherical with lack of pores. The particle size and polydispersity index (PDI) of microsphere was observed as 300 ​μm and 0.349, respectively with high positive zeta potential of 38.4 ​mV. The results of percentage yield and swelling index analysis demonstrated 87.04 % and 90.65 %, respectively for optimized formulation with an <em>in vitro</em> release capability of 95.20 % in 10 ​h. In addition, the results suggested that the mucoadhesive microspheres successfully entrapped 94.86 ​± ​4.25 % of the RPG. These results clearly indicated that the optimized formulation of RPG fortified mucoadhesive microspheres reduced the blood glucose level (hyperglycemia due to glucose load 2 ​g/kg) significantly, compared to marketed RPG formulation (0.25 ​mg/kg) after 2 ​h of oral administration. Additionally, RPG incorporated microspheres enable the regulated blood glucose level over a 10 ​h. Hence, the formulation demonstrated overall improvement in anti-diabetic efficacy.</p></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 3","pages":"Pages 441-449"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949866X24000224/pdfft?md5=3b0ca9f262b5e390472892b8c57f954f&pid=1-s2.0-S2949866X24000224-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139825761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extracellular vesicles: The future of therapeutics and drug delivery systems","authors":"Md Jamir Uddin ,&nbsp;Popat Mohite ,&nbsp;Shubham Munde ,&nbsp;Nitin Ade ,&nbsp;Tosin Ayodeji Oladosu ,&nbsp;Vijay R. Chidrawar ,&nbsp;Ravish Patel ,&nbsp;Sankha Bhattacharya ,&nbsp;Himanshu Paliwal ,&nbsp;Sudarshan Singh","doi":"10.1016/j.ipha.2024.02.004","DOIUrl":"https://doi.org/10.1016/j.ipha.2024.02.004","url":null,"abstract":"<div><p>Extracellular vesicles (EVs) are nanometric size, a cell-derived drug delivery carrier composed of membrane-bound structures, release into the cellular medium and found in body fluids. EVs serve a dual purpose, acting as a means of disposing of redundant material and a method of communication between cells. Their natural origin, biocompatibility, protein, and nucleic acid composition boosts superior targeting capabilities. While strong safety profile, intrinsic pleiotropic therapeutic effects, ability to accommodate both lipophilic and hydrophilic agents, and pass through blood–brain barrier makes them exceptional nanocarrier. Several synthetic drug delivery methods have been fabricated and introduced to the market throughout the previous few decades. However, their inefficiency, cytotoxicity, and/or immunogenicity hinder their applications. Evidence demonstrates that EVs play a critical role in major physiological and pathological processes, such as cellular homeostasis, infection propagation, cancer progression, and cardiovascular diseases. Moreover, EVs offer a range of advantages over traditional synthetic carriers, thus paving the way for innovative drug delivery approaches. Although therapeutic applications as carrier is limited due to lack of scalable isolation techniques and efficient drug loading, EVs serve great potential as nanocarriers. The review summarizes and discuss recent progress and challenges associated with development of EVs as nanocarrier.</p></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 3","pages":"Pages 312-328"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949866X24000273/pdfft?md5=fc15256de188ba137c11be7de0fceab3&pid=1-s2.0-S2949866X24000273-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141243819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"QSAR, molecular docking, and molecular designs of some anti-epilepsy compounds","authors":"Usman Abdulfatai ,&nbsp;Stephen Ejeh ,&nbsp;Abduljelil Ajala ,&nbsp;Samuel Ndaghiya Adawara ,&nbsp;Olasupo Sabitu Babatunde ,&nbsp;Zakari Ya'u Ibrahim","doi":"10.1016/j.ipha.2023.11.011","DOIUrl":"10.1016/j.ipha.2023.11.011","url":null,"abstract":"<div><p>Epilepsy is a non-communicable central nervous system (CNS) disease that accounts for approximately 0.8–1.2 % of the global population at any time. The hyper-activities of gamma butyric acid aminotransferase (GABA_AT) enzyme have been confirmed to be largely responsible for seizure/epilepsy. Because of this special function, the GABA_AT enzyme has been the main target of many anti-epilepsy drugs (AEDs). To date, many discovered AEDs have not eradicated this neurological disease. Since experimental determinations of modern drugs are usually costly and sometimes non-eco-friendly, in-silco quantitative structure–activity relationship (QSAR)-machine learning, docking and pharmacokinetics (PMK) techniques were used to design and test the oral bio-availabilities of all the designed AEDs. QSAR models were generated, and the predictive properties of R²int = 0.9827, R²ext = 0.9407, and R²adj of 0.9667 indicate the evidence that the developed model was not by chance. Six (6) new AEDs were newly designed, and they were found to have better anti-epileptic activities values of 2.146799, 2.224866, 2.31479, 2.450313, 2.301474, and 2.618303 than the standard AED, Vigabatrin (0.40672). Also, the docked new compounds shows excellent binding energies of −127.001, −129.071, −130.515, −126.881, −130.771, and −126.974 kcal/mol compared to the referenced AED (−76.9173 kcal/mol). The PMK and absorption, distribution, metabolism, excretion, and toxicity (ADMET) investigations also revealed that all the designed compounds were found to be bio-available for human administration. 'Therefore, the newly designed analogues (AEDs) could be considered as potential drug candidates for the treatment of epilepsy.</p></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 3","pages":"Pages 427-434"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949866X23001259/pdfft?md5=b5d5a294d721cc4faafe33be21511ebc&pid=1-s2.0-S2949866X23001259-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138627236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the competence of ChatGPT for customer and patient service management","authors":"Abid Haleem ,&nbsp;Mohd Javaid ,&nbsp;Ravi Pratap Singh","doi":"10.1016/j.ipha.2024.03.002","DOIUrl":"10.1016/j.ipha.2024.03.002","url":null,"abstract":"<div><p>The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables it to process massive volumes of data and produce text that is both cohesive and illuminating. Service is a crucial component everywhere as it provides the basis for establishing client rapport and offering aid and support. In healthcare, the application of ChatGPT for patient service support has been one of the most significant advances in recent years. ChatGPT can help overcome language obstacles and improve patient satisfaction by facilitating communication with healthcare personnel and understanding of care. It can assist in enhancing the entire patient experience by offering personalised information and support to patients and making it more straightforward for them to communicate with healthcare professionals. Its goal can be to expedite and streamline service by promptly and accurately responding to customers. Businesses of all sizes increasingly use ChatGPT since it allows them to provide 24/7 customer support without requiring human contact. This paper briefly discusses ChatGPT and the need for better services. Various perspectives on improving customer and patient services through ChatGPT are discussed. The article also discussed the major key enablers of ChatGPT for refining customer and patient assistance. Further, the paper identifies and discusses the critical application areas of ChatGPT for customer and patient service. With its ability to handle several requests simultaneously, respond quickly and accurately to client questions, and gain knowledge from every interaction, ChatGPT is revolutionising customer and patient service. Its accessibility and compatibility with various communication channels make it a desirable solution for businesses looking to improve support. As technology advances, ChatGPT is positioned to become an essential tool for businesses wishing to provide speedy and customised service. Although ChatGPT may give convincing solutions, the chance of providing accurate and updated information poses a problem for its usage in service jobs that need accurate and up-to-date information. In future, various services will become better and more efficient due to ChatGPT and AI.</p></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 3","pages":"Pages 392-414"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949866X24000480/pdfft?md5=486c0b1deb623f0ab297c68f59356065&pid=1-s2.0-S2949866X24000480-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140272095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of pharmaceuticals using 3D and 4D printing","authors":"Afiya Baig,&nbsp;Rohan Barse,&nbsp;Asawari Paryekar,&nbsp;Vijay Jagtap","doi":"10.1016/j.ipha.2024.05.008","DOIUrl":"10.1016/j.ipha.2024.05.008","url":null,"abstract":"<div><div>This overview examines the latest developments and applications of 3D and 4D printing in the health care and pharmaceutical field. The technique of creating a 3D object from a 3D model in the required size and shape is known as 3D printing. Whereas, 4D printing is the establishment of intricate three-dimensional formations that can change form in response to various external inputs. Applying 3D printing technology 3D printing, the healthcare industry has produced significant strides toward a patient-centred approach. The future of biomedical science and patient-centered care could be completely transformed by 3D printing with further advancements in research and development. 3D, 4D Technology used in printing is one of the most advanced industrial technologies available worldwide. The 3D and 4D printing pharmaceutical enterprises have completed the shift from centralised to distributed systems for the purpose of creating dosage forms. The goal of the study is to support the research goal of determining the degree to which patient-specific treatment is enhanced and healthcare outcomes are improved through the use of printing technologies in pharmaceuticals. Beyond this thorough analysis, the study highlights potential and problems from several angles and comparative aspects between 3D and 4D printing.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 6","pages":"Pages 804-813"},"PeriodicalIF":0.0,"publicationDate":"2024-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer vision to enhance healthcare domain: An overview of features, implementation, and opportunities","authors":"Mohd Javaid ,&nbsp;Abid Haleem ,&nbsp;Ravi Pratap Singh ,&nbsp;Mumtaz Ahmed","doi":"10.1016/j.ipha.2024.05.007","DOIUrl":"10.1016/j.ipha.2024.05.007","url":null,"abstract":"<div><div>The emergence of Artificial Intelligence (AI) has already brought several advantages to the healthcare sector. Computer Vision (CV) is one of the growing modern AI technologies. The distribution and administration of medications are about to change by using CV for medication management. This system scans pharmaceutical labels and keeps track of the process from delivery to administration using cameras, sensors, and computer algorithms. In order to assure accuracy in medicine delivery and dose, the system also makes it easier for doctors, nurses, and chemists to communicate. The computer vision-driven medication management system can significantly lower the number of medical mistakes that result from inaccurate or missing prescriptions, improper doses, or simply forgetting to take a particular drug. An exhaustive literature review has been done to identify work related to the research objectives. This paper is about CV and their need in healthcare. Various tasks associated with CV in the healthcare domain are discussed. Targeted healthcare goals through CV traits are briefed. Finally, the significant applications of CVs in healthcare were identified and discussed. Nowadays, CV has practical uses in healthcare. Its methods are widely used since they have shown excellent utility in several medical contexts, including medical imaging and surgical planning. The CV is used to study how to program computers to comprehend digital pictures. Numerous medical applications utilise this technology, such as automated abnormality identification, illness diagnosis, and surgical procedure guiding. CV is expanding quickly and has enormous promise to enhance healthcare. Some of the many CV applications in the healthcare sector include patient identification systems, medical picture analysis, surgical simulation and illness diagnosis.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 6","pages":"Pages 792-803"},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141131854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence: A promising tool in diagnosis of respiratory diseases","authors":"Pragya Yadav ,&nbsp;Vaibhav Rastogi ,&nbsp;Abhishek Yadav ,&nbsp;Poonam Parashar","doi":"10.1016/j.ipha.2024.05.002","DOIUrl":"10.1016/j.ipha.2024.05.002","url":null,"abstract":"<div><div>Respiratory diseases (RD) are a major healthcare issue and is predicted to be leading cause of mortality by 2030. Artificial intelligence (AI) has been recently gained interest -in scientific fields. Among a variety of application, it has made a marked embrace in medical domain where it is applied for diagnosis and disease progression by clinicians. Further, in particular, AI based Machine learning (ML) and Deep Learning (DL) algorithms have come up as an effective emerging trend in diagnosis of respiratory diseases. These algorithms are trained to classify the respiratory diseases such as pneumonia, fibrosis, cancer, tuberculosis emphysema, asthma based on radiographs, CT scans <em>etc.</em> images. The AI enabled diagnosis can facilitate precise diagnosis and differentiation among overlapping characteristics bearing lung diseases. This review focuses on the AI-based algorithms assisted, improved diagnosis of three respiratory diseases specifically COPD (Chronic obstructive pulmonary disease), asthma and lung fibrosis. Further, AI is expected to play a crucial role in facilitating diagnosis aiding clinicians in predicting and management of lung diseases taking it towards a promising tool for everyday clinical practice soon. It is written with a hope that this brief review of emphasizing utilization of AI in medical field will be helpful to clinicians.</div></div>","PeriodicalId":100682,"journal":{"name":"Intelligent Pharmacy","volume":"2 6","pages":"Pages 784-791"},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}