{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T16:19:18Z","timestamp":1788365958973,"version":"build-2803163510"},"reference-count":80,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T00:00:00Z","timestamp":1788307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education (MOE) and Gyeongsangbuk-do, Republic of Korea","award":["2026-ANCHOR-15-115"],"award-info":[{"award-number":["2026-ANCHOR-15-115"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Mol. Sci.","IJMS"],"abstract":"<jats:p>Modern scientific and technological developments are driving major advances in drug research and development. This narrative review, based on a structured search of PubMed, Scopus, and Web of Science (2018\u20132026), examines how artificial intelligence (AI) and machine learning (ML) are accelerating a historically prolonged and expensive process, alongside pharmacogenomics, organ-on-a-chip systems, three-dimensional (3D) bioprinting, and nanotechnology. In benchmark studies, deep learning techniques have achieved an area under the receiver operating characteristic curve (AUROC) of over 0.85 for a subset of absorption, distribution, metabolism, excretion, and toxicity (ADMET) endpoints. AI-powered models show promising, albeit platform-dependent, accuracy in predicting candidate drug properties. Pharmacogenomics enables personalized medicine by tailoring therapies according to patients\u2019 genetic profiles, whereas organ-on-a-chip systems and 3D bioprinting provide physiologically relevant human tissue models for preclinical evaluation. In a blinded benchmark study, the Emulate Liver-Chip showed 87% sensitivity and 100% specificity for drug-induced liver injury, outperforming animal models in that specific comparison. Nanotechnology is advancing drug delivery through the use of nanoparticle systems, such as Doxil\u00ae and Onpattro\u00ae. Obstacles remain, including regulatory constraints, ethical considerations, data quality limitations, and the need for stronger validation, although ongoing funding, interdisciplinary collaboration, and evolving regulatory frameworks may support further development. Overall, these technologies show meaningful potential to shorten development time and improve treatment safety, although further prospective validation is required before realizing this potential at scale.<\/jats:p>","DOI":"10.3390\/ijms27177864","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T15:39:47Z","timestamp":1788363587000},"page":"7864","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating Artificial Intelligence with Emerging Pharmaceutical Technologies: Current Progress, Clinical Translation, and Future Challenges"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3942-6346","authenticated-orcid":false,"given":"Priya","family":"Sharma","sequence":"first","affiliation":[{"name":"School of Pharmacy and Emerging Sciences, Baddi University of Emerging Sciences & Technology, Solan 173205, Himachal Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5029-9774","authenticated-orcid":false,"given":"Saurabh","family":"Tiwari","sequence":"additional","affiliation":[{"name":"School of Materials Science and Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7863-1457","authenticated-orcid":false,"given":"Nokeun","family":"Park","sequence":"additional","affiliation":[{"name":"School of Materials Science and Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5302-3797","authenticated-orcid":false,"given":"\u0141ukasz","family":"Szeleszczuk","sequence":"additional","affiliation":[{"name":"Department of Organic and Physical Chemistry, Medical University of Warsaw, 1 Banacha Str., 02-097 Warsaw, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/nrd3078","article-title":"How to Improve R&D Productivity: The Pharmaceutical Industry\u2019s Grand Challenge","volume":"9","author":"Paul","year":"2010","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1007\/s40273-021-01065-y","article-title":"How Much Does It Cost to Research and Develop a New Drug? A Systematic Review and Assessment","volume":"39","author":"Schlander","year":"2021","journal-title":"Pharmacoeconomics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.jhealeco.2016.01.012","article-title":"Innovation in the Pharmaceutical Industry: New Estimates of R&D Costs","volume":"47","author":"DiMasi","year":"2016","journal-title":"J. Health Econ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3049","DOI":"10.1016\/j.apsb.2022.02.002","article-title":"Why 90% of Clinical Drug Development Fails and How to Improve It?","volume":"12","author":"Sun","year":"2022","journal-title":"Acta Pharm. Sin. B"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1038\/s41573-019-0024-5","article-title":"Applications of Machine Learning in Drug Discovery and Development","volume":"18","author":"Vamathevan","year":"2019","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Wu, J., He, J., Ni, Q., Li, Z., Lin, X., Zhao, Z., Qiu, L., Wang, H., Li, S., and Shi, C. (2026). AI-Driven Drug Discovery: Focus on Targets for Solid Tumors. Pharmaceutics, 18.","DOI":"10.3390\/pharmaceutics18030329"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1080\/17460441.2021.1909567","article-title":"Artificial Intelligence in Drug Discovery: Recent Advances and Future Perspectives","volume":"16","author":"Grisoni","year":"2021","journal-title":"Expert Opin. Drug Discov."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"10792","DOI":"10.1002\/anie.201814681","article-title":"Automated De Novo Drug Design: Are We Nearly There Yet?","volume":"58","author":"Schneider","year":"2019","journal-title":"Angew. Chem. Int. Ed."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1038\/s41573-020-0090-8","article-title":"Engineering Precision Nanoparticles for Drug Delivery","volume":"20","author":"Mitchell","year":"2021","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1038\/s41576-022-00466-9","article-title":"Human Organs-on-Chips for Disease Modelling, Drug Development and Personalized Medicine","volume":"23","author":"Ingber","year":"2022","journal-title":"Nat. Rev. Genet."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ilic, A., Zukic, S., Oljacic, S., Maran, U., Nikolic, K., and Popovic-Nikolic, M. (2026). Current Computational Approaches for the Discovery of Novel Anticancer Agents Targeting VEGFR and SIRT Signaling Pathways. Pharmaceutics, 18.","DOI":"10.3390\/pharmaceutics18020273"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kassa, F.M., Youssef, S.H., Song, Y., and Garg, S. (2025). Use of Computational Intelligence in Customizing Drug Release from 3D-Printed Products: A Comprehensive Review. Pharmaceutics, 17.","DOI":"10.3390\/pharmaceutics17050551"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kodumuru, R., Sarkar, S., Parepally, V., and Chandarana, J. (2025). Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy. Pharmaceutics, 17.","DOI":"10.3390\/pharmaceutics17030290"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.2174\/138161207780765954","article-title":"Artificial Intelligence Approaches for Rational Drug Design and Discovery","volume":"13","author":"Duch","year":"2007","journal-title":"Curr. Pharm. Des."},{"key":"ref_15","unstructured":"Wills, T. (2026, May 11). AI Drug Discovery: Assessing the First AI-Designed Drug Candidates to Go Into Human Clinical Trials. American Chemical Society, Available online: https:\/\/www.cas.org\/resources\/cas-insights\/ai-drug-discovery-assessing-the-first-ai-designed-drug-candidates-to-go-into-human-clinical-trials."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1016\/j.cell.2020.01.021","article-title":"A Deep Learning Approach to Antibiotic Discovery","volume":"180","author":"Stokes","year":"2020","journal-title":"Cell"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Niazi, S.K. (2025). Artificial Intelligence in Small-Molecule Drug Discovery: A Critical Review of Methods, Applications, and Real-World Outcomes. Pharmaceuticals, 18.","DOI":"10.3390\/ph18091271"},{"key":"ref_18","unstructured":"Insilico Medicine (2024). Insilico Medicine Announces Positive Topline Results of ISM001-055 for the Treatment of Idiopathic Pulmonary Fibrosis (IPF) Developed Using Generative AI, Insilico Medicine."},{"key":"ref_19","unstructured":"Business Wire, Inc. (2022). Exscientia Reports Topline Data from EXS-21546 Phase 1a Study Demonstrating Targeted A2A Receptor Signaling Inhibition in Healthy Volunteers, Business Wire, Inc."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"100102","DOI":"10.1016\/j.pharmr.2025.100102","article-title":"Leading Artificial Intelligence\u2013Driven Drug Discovery Platforms: 2025 Landscape and Global Outlook","volume":"78","author":"Dharmasivam","year":"2026","journal-title":"Pharmacol. Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3770","DOI":"10.1038\/s41467-019-11786-6","article-title":"A Critique of Pure Learning and What Artificial Neural Networks Can Learn from Animal Brains","volume":"10","author":"Zador","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"btae416","DOI":"10.1093\/bioinformatics\/btae416","article-title":"ADMET-AI: A Machine Learning ADMET Platform for Evaluation of Large-Scale Chemical Libraries","volume":"40","author":"Swanson","year":"2024","journal-title":"Bioinformatics"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1038\/nrd.2017.232","article-title":"Automating Drug Discovery","volume":"17","author":"Schneider","year":"2018","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e667","DOI":"10.1016\/S2589-7500(20)30192-8","article-title":"Artificial Intelligence in COVID-19 Drug Repurposing","volume":"2","author":"Zhou","year":"2020","journal-title":"Lancet Digit. Health"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e30","DOI":"10.1016\/S0140-6736(20)30304-4","article-title":"Baricitinib as Potential Treatment for 2019-NCoV Acute Respiratory Disease","volume":"395","author":"Richardson","year":"2020","journal-title":"Lancet"},{"key":"ref_26","unstructured":"U.S. Food and Drug Administration (2020). Emergency Use Authorization for Baricitinib (Olumiant) for Treatment of COVID-19, U.S. Food and Drug Administration."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1407","DOI":"10.1016\/S2213-2600(21)00331-3","article-title":"Efficacy and Safety of Baricitinib for the Treatment of Hospitalised Adults with COVID-19 (COV-BARRIER): A Randomised, Double-Blind, Parallel-Group, Placebo-Controlled Phase 3 Trial","volume":"9","author":"Marconi","year":"2021","journal-title":"Lancet Respir. Med."},{"key":"ref_28","unstructured":"Edelman, P.R., and Fekene, M. (2026, May 11). Sumitomo Dainippon Pharma and Exscientia Joint Development New Drug Candidate Created Using Artificial Intelligence (AI) Begins Clinical Study. Available online: https:\/\/www.sumitomo-pharma.com\/news\/20200130.html."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1038\/s41576-022-00572-8","article-title":"Pharmacogenomics: Current Status and Future Perspectives","volume":"24","author":"Pirmohamed","year":"2023","journal-title":"Nat. Rev. Genet."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1038\/nrg.2016.86","article-title":"Towards Precision Medicine","volume":"17","author":"Ashley","year":"2016","journal-title":"Nat. Rev. Genet."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e41317","DOI":"10.1016\/j.heliyon.2024.e41317","article-title":"Bridging the Gap: From Petri Dish to Patient\u2014Advancements in Translational Drug Discovery","volume":"11","author":"Rabbani","year":"2025","journal-title":"Heliyon"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1038\/s41591-018-0300-7","article-title":"High-Performance Medicine: The Convergence of Human and Artificial Intelligence","volume":"25","author":"Topol","year":"2019","journal-title":"Nat. Med."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1512","DOI":"10.1002\/cpt.70005","article-title":"Advancing Clinical Pharmacogenomics Worldwide Through the Clinical Pharmacogenetics Implementation Consortium (CPIC)","volume":"118","author":"Caudle","year":"2025","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1002\/cpt.1304","article-title":"Clinical Pharmacogenetics Implementation Consortium Guideline for Thiopurine Dosing Based on TPMT and NUDT15 Genotypes: 2018 Update","volume":"105","author":"Relling","year":"2019","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1821","DOI":"10.1001\/jama.2010.1543","article-title":"Reduced-Function CYP2C19 Genotype and Risk of Adverse Clinical Outcomes Among Patients Treated with Clopidogrel Predominantly for PCI: A Meta-Analysis","volume":"304","author":"Mega","year":"2010","journal-title":"JAMA"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1002\/cpt.668","article-title":"Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update","volume":"102","author":"Johnson","year":"2017","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1002\/cpt.147","article-title":"Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors","volume":"98","author":"Hicks","year":"2015","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1038\/tpj.2017.21","article-title":"Cost-Effectiveness of Pharmacogenetic-Guided Treatment: Are We There Yet?","volume":"17","author":"Verbelen","year":"2017","journal-title":"Pharmacogenomics J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2","DOI":"10.21037\/jlpm-24-36","article-title":"Challenges and Considerations in Implementing Clinical Pharmacogenomics","volume":"10","author":"Kanegusuku","year":"2025","journal-title":"J. Lab. Precis. Med."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2101394","DOI":"10.1002\/advs.202101394","article-title":"3D Printing of Physical Organ Models: Recent Developments and Challenges","volume":"8","author":"Jin","year":"2021","journal-title":"Adv. Sci."},{"key":"ref_41","first-page":"908","article-title":"Recent Advances in Three-Dimensional Bioprinting of Stem Cells","volume":"13","author":"Eswaramoorthy","year":"2019","journal-title":"J. Tissue Eng. Regen. Med."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"100165","DOI":"10.1016\/j.glmedi.2024.100165","article-title":"3D Printing of Cancer Models for Drug Discovery: Advancements, Challenges, and Future Perspectives","volume":"5","author":"Fanibuyan","year":"2025","journal-title":"J. Med. Surg. Public Health"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"14103","DOI":"10.1088\/1758-5090\/8\/1\/014103","article-title":"Towards Artificial Tissue Models: Past, Present, and Future of 3D Bioprinting","volume":"8","author":"Chen","year":"2016","journal-title":"Biofabrication"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1806899","DOI":"10.1002\/adma.201806899","article-title":"3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments","volume":"31","author":"Meng","year":"2019","journal-title":"Adv. Mater."},{"key":"ref_45","first-page":"101021","article-title":"Organoids and Organs-on-Chips for Accelerating R&D and Clinical Translation in Orthopaedics: Emerging Opportunities and Regulatory Pathways","volume":"56","author":"Lei","year":"2026","journal-title":"J. Orthop. Transl."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1038\/nbt.2989","article-title":"Microfluidic Organs-on-Chips","volume":"32","author":"Bhatia","year":"2014","journal-title":"Nat. Biotechnol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1038\/s43856-022-00209-1","article-title":"Performance Assessment and Economic Analysis of a Human Liver-Chip for Predictive Toxicology","volume":"2","author":"Ewart","year":"2022","journal-title":"Commun. Med."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1038\/s43586-022-00118-6","article-title":"A Guide to the Organ-on-a-Chip","volume":"2","author":"Leung","year":"2022","journal-title":"Nat. Rev. Methods Primers"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"106439","DOI":"10.1016\/j.ejps.2023.106439","article-title":"Cardiac Tissue Engineering for Myocardial Infarction Treatment","volume":"185","author":"Scacchetti","year":"2023","journal-title":"Eur. J. Pharm. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1056\/NEJMoa1716153","article-title":"Patisiran, an RNAi Therapeutic, for Hereditary Transthyretin Amyloidosis","volume":"379","author":"Adams","year":"2018","journal-title":"N. Engl. J. Med."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1056\/NEJMoa2035389","article-title":"Efficacy and Safety of the MRNA-1273 SARS-CoV-2 Vaccine","volume":"384","author":"Baden","year":"2021","journal-title":"N. Engl. J. Med."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1038\/s41587-024-02143-0","article-title":"A Small-Molecule TNIK Inhibitor Targets Fibrosis in Preclinical and Clinical Models","volume":"43","author":"Ren","year":"2025","journal-title":"Nat. Biotechnol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2602","DOI":"10.1038\/s41591-025-03743-2","article-title":"A Generative AI-Discovered TNIK Inhibitor for Idiopathic Pulmonary Fibrosis: A Randomized Phase 2a Trial","volume":"31","author":"Xu","year":"2025","journal-title":"Nat. Med."},{"key":"ref_54","unstructured":"(2026, July 11). Insilico Medicine Insilico Initiates Phase III Clinical Trial for Rentosertib, Its AI-Empowered TNIK Inhibitor for Idiopathic Pulmonary Fibrosis. Available online: https:\/\/insilico.com\/news\/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly Accurate Protein Structure Prediction with AlphaFold","volume":"596","author":"Jumper","year":"2021","journal-title":"Nature"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"D439","DOI":"10.1093\/nar\/gkab1061","article-title":"AlphaFold Protein Structure Database: Massively Expanding the Structural Coverage of Protein-Sequence Space with High-Accuracy Models","volume":"50","author":"Varadi","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate Structure Prediction of Biomolecular Interactions with AlphaFold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Saharan, V.A., Kulhari, H., and Jadhav, H. (2024). Principles of Research Methodology and Ethics in Pharmaceutical Sciences: An Application Guide for Students and Researchers, CRC Press. [1st ed.].","DOI":"10.1201\/9781003088226"},{"key":"ref_59","unstructured":"(2026, May 11). Center for Drug Evaluation and Research (CDER). FDA\u2019s ISTAND Pilot Program Accepts a Submission of First Organ-on-a-Chip Technology Designed to Predict Human Drug-Induced Liver Injury (DILI), Available online: https:\/\/www.fda.gov\/drugs\/drug-alerts-and-statements\/fdas-istand-pilot-program-accepts-submission-first-organ-chip-technology-designed-predict-human-drug."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.stem.2025.12.022","article-title":"Challenges and Opportunities for Human Organ Chips in FDA Assessments and Pharma Pipelines","volume":"33","author":"Ingber","year":"2026","journal-title":"Cell Stem Cell"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"061501","DOI":"10.1063\/5.0268362","article-title":"Revolutionizing Drug Evaluation System with Organ-on-a-Chip and Artificial Intelligence: A Critical Review","volume":"19","author":"Barua","year":"2025","journal-title":"Biomicrofluidics"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1186\/s12951-018-0392-8","article-title":"Nano Based Drug Delivery Systems: Recent Developments and Future Prospects","volume":"16","author":"Patra","year":"2018","journal-title":"J. Nanobiotechnol."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Yusuf, A., Almotairy, A.R.Z., Henidi, H., Alshehri, O.Y., and Aldughaim, M.S. (2023). Nanoparticles as Drug Delivery Systems: A Review of the Implication of Nanoparticles\u2019 Physicochemical Properties on Responses in Biological Systems. Polymers, 15.","DOI":"10.3390\/polym15071596"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1038\/nbt.3330","article-title":"Principles of Nanoparticle Design for Overcoming Biological Barriers to Drug Delivery","volume":"33","author":"Blanco","year":"2015","journal-title":"Nat. Biotechnol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"42","DOI":"10.3892\/br.2021.1418","article-title":"Nanotechnology and Its Use in Imaging and Drug Delivery (Review)","volume":"14","author":"Sim","year":"2021","journal-title":"Biomed. Rep."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"7794","DOI":"10.1200\/JCO.2005.04.937","article-title":"Phase III Trial of Nanoparticle Albumin-Bound Paclitaxel Compared with Polyethylated Castor Oil\u2013Based Paclitaxel in Women with Breast Cancer","volume":"23","author":"Gradishar","year":"2005","journal-title":"J. Clin. Oncol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s10549-007-9591-y","article-title":"Multicenter Phase II Trial of Genexol-PM, a Cremophor-Free, Polymeric Micelle Formulation of Paclitaxel, in Patients with Metastatic Breast Cancer","volume":"108","author":"Lee","year":"2008","journal-title":"Breast Cancer Res. Treat."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"e17571","DOI":"10.1002\/advs.202417571","article-title":"Recent Advances in MRNA Delivery Systems for Cancer Therapy","volume":"12","author":"Zhang","year":"2025","journal-title":"Adv. Sci."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Ugwu, O.P.-C., Ogenyi, F.C., Basajja, M., Ugwu, C.N., Mustafa, M.M., and Okon, M. (2026). Ben Nanoparticle-Mediated MRNA Delivery for Cancer, Autoimmunity, and Genetic Diseases: A Rapid Review. Front. Drug Deliv., 6.","DOI":"10.3389\/fddev.2026.1793322"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.addr.2020.05.012","article-title":"Translational Considerations in Nanomedicine: The Oncology Perspective","volume":"158","author":"Gabizon","year":"2020","journal-title":"Adv. Drug Deliv. Rev."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"100686","DOI":"10.1016\/j.modpat.2024.100686","article-title":"Ethical and Bias Considerations in Artificial Intelligence\/Machine Learning","volume":"38","author":"Hanna","year":"2025","journal-title":"Mod. Pathol."},{"key":"ref_72","first-page":"447","article-title":"Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations","volume":"366","author":"Obermeyer","year":"2019","journal-title":"Science (1979)"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"FDD59","DOI":"10.4155\/fdd-2020-0028","article-title":"Artificial Intelligence in Drug Design: Algorithms, Applications, Challenges and Ethics","volume":"3","author":"Arabi","year":"2021","journal-title":"Future Drug Discov."},{"key":"ref_74","unstructured":"U.S. Food and Drug Administration (2021). Artificial Intelligence\/Machine Learning (AI\/ML)-Based Software as a Medical Device (SaMD) Action Plan, U.S. Food and Drug Administration."},{"key":"ref_75","unstructured":"Committee for Medicinal Products for Human Use (CHMP), and Committee for Medicinal Products for Veterinary Use (CVMP) (2022). Reflection Paper on the Use of Artificial Intelligence (AI) in the Medicinal Product Lifecycle, CVMP."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1016\/j.drudis.2020.11.037","article-title":"Artificial Intelligence in Drug Discovery: What Is Realistic, What Are Illusions? Part 2: A Discussion of Chemical and Biological Data","volume":"26","author":"Bender","year":"2021","journal-title":"Drug Discov. Today"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"3521","DOI":"10.1073\/pnas.1611835114","article-title":"Overcoming Catastrophic Forgetting in Neural Networks","volume":"114","author":"Kirkpatrick","year":"2017","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"5054","DOI":"10.1039\/D2BM00797E","article-title":"A Focused Review on Three-Dimensional Bioprinting Technology for Artificial Organ Fabrication","volume":"10","author":"Panda","year":"2022","journal-title":"Biomater. Sci."},{"key":"ref_79","unstructured":"Deloitte (2026, May 11). Measuring the Return from Pharmaceutical Innovation. Available online: https:\/\/www.deloitte.com\/uk\/en\/Industries\/life-sciences-health-care\/research\/measuring-return-from-pharmaceutical-innovation.html."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Sung, J.J.Y., and Stewart, C. (2024). Chapter 1\u2014Artificial Intelligence and the Future of Medicine. Artificial Intelligence in Medicine, Academic Press.","DOI":"10.1016\/B978-0-323-95068-8.00001-7"}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/17\/7864\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T15:40:02Z","timestamp":1788363602000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/17\/7864"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,2]]},"references-count":80,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["ijms27177864"],"URL":"https:\/\/doi.org\/10.3390\/ijms27177864","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,2]]}}}