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The Omics‐Driven Machine Learning Path to Cost‐Effective Precision Medicine in Chronic Kidney Disease

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IMPACT Framework: Establishing Global Standards for Artificial Intelligence Implementation, Methodology, and Translation in Drug Discovery

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Strategic partnerships for AI-driven drug discovery: The role of relational dynamics

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ChemPrint: An AI-Driven Framework for Enhanced Drug DiscoveryPreprint

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Technological and industrial trends in China’s pharmaceutical sector

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Enhancing Large-Scale Pharmacogenetic Studies in African Populations for Clinical Care and Drug Development

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Artificial Intelligence in Drug Discovery and Development: Raising Quality per Decision

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Every Compound a Candidate: experience-led risk-taking approaches to accelerate small-molecule drug discovery

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SPP-MIM hybridization meta-films for high-sensitivity and high-stability biosensing at optical fiber end-facets

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Single-cell multiomics: a new frontier in drug research and development

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Incumbent strategic renewal drivers to AI disruption

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Exploring possible AI trajectories through 2030

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Artificial Intelligence in Dermatology Research and Drug Discovery

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Toward clinical translation of AI-Led drug discovery in endometrial cancer

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In silico Drug Discovery: Bridging the Gaps in Preclinical Translation

Markossian, S., Baskir, H. M., Grossman, A., Chandran, S., Rele, S. S., Hall, M. D., Amaro, R. E., Tropsha, A., & Zakharov, A. V. (2025) · Drug Discovery Today · doi:10.1016/j.drudis.2025.104567 · Cited by 4 · see citing works

Mathematical and Artificial Intelligence Techniques in Modern Drug Discovery: A Review

Agrwal, A., Kumar, R., Maheshwari, S., Sharma, M., Batra, C. M., Sharma, S., & Gaur, V. (2025) · Drug Development Research · doi:10.1002/ddr.70212 · Cited by 4 · see citing works

Big data in healthcare and medicine revisited: design and managerial challenges in the age of artificial intelligence

Raghupathi, W., & Raghupathi, V. (2026) · Health Information Science and Systems · doi:10.1007/s13755-026-00433-2 · Cited by 4 · see citing works

Advancing sustainability through digitalization: from drug development to patient care

Eugster, R., & Luciani, P. (2026) · RSC Pharmaceutics · doi:10.1039/d5pm00342c · Cited by 4 · see citing works

Digital twins to accelerate target identification and drug development for immune‐mediated disorders

Niarakis, A., & Moingeon, P. E. (2026) · FEBS Open Bio · doi:10.1002/2211-5463.70228 · Cited by 4 · see citing works

The role of AI in oncology: present applications and future horizons

Weitzner, A. S., Singla, N., & Rai, A. (2026) · npj Precision Oncology · doi:10.1038/s41698-026-01408-y · Cited by 4 · see citing works

Target discovery and drug design in the era of artificial intelligence

Fleming, P., & Ivanov, A. A. (2026) · Medicinal Chemistry Research · doi:10.1007/s00044-026-03562-1 · Cited by 4 · see citing works

GenAI and the Future of Creativity in Science and ArtPreprint

Barbosu, S., & Khashabi, P. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4586863 · Cited by 4 · see citing works

Clinical trials gain intelligence

(2025) · Nature Biotechnology · doi:10.1038/s41587-025-02754-1 · Cited by 4 · see citing works

What patents on AI-derived drugs reveal

Freilich, J., & Rai, A. K. (2025) · Science · doi:10.1126/science.adw1972 · Cited by 3 · see citing works

Transforming drug discovery through the fusion of AI-driven analysis and protein micropatterning

Roach, P. (2025) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2025.2567300 · Cited by 3 · see citing works

Deep learning for small-molecule drug discovery: From molecular design to clinical translation

Oliveira, R. I., Pereira, T., Abbasi, M., Salvador, J. A. R., & Arrais, J. P. (2025) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2025.101533 · Cited by 3 · see citing works

Generative AI in pharmaceutical R&D: From large language models to AI agents to regulation

Weatherall, J., & Meier, C. (2026) · Drug Discovery Today · doi:10.1016/j.drudis.2025.104593 · Cited by 3 · see citing works

Learning from the successes and failures of early artificial intelligence (AI) adoption for drug discovery in Big BioPharma

Braddock, M., & Jeziorski, K. (2026) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2026.2624023 · Cited by 3 · see citing works

Foundation models and AI agents in oncology drug discovery

Ghanwatkar, Y., Rajdeo, P., & Mahato, R. I. (2026) · Drug Discovery Today · doi:10.1016/j.drudis.2026.104655 · Cited by 3 · see citing works

Beyond accuracy: comprehensive alignment for AI-driven molecular design

Zhang, Q. H., Zhuang, X., Zhou, C., Zhu, Y., Xu, T., Li, T., Liu, D., Liu, S., Ding, K., Li, M., et al. (2026) · AI for Science · doi:10.1088/3050-287x/ae5f37 · Cited by 3 · see citing works

Antibacterial drug discovery: challenges and preclinical promises from synthetic small molecules

Fernandes, G., Kim, S., dos Santos, J. L., Wang, Y., Soudy, C., Redmond, J. M., Castagnolo, D., & Todd, M. H. (2026) · Chemical Society Reviews · doi:10.1039/d5cs00617a · Cited by 3 · see citing works

Artificial intelligence in drug discovery: from algorithmic foundations to clinical translation

Mao, Z., & Yan, L. (2026) · Frontiers in Pharmacology · doi:10.3389/fphar.2026.1870527 · Cited by 3 · see citing works

Large language medicine: defining a new paradigm in human health

Guni, A., Hu, W., Morley, J., Cohen, I. G., Barnaghi, P. M., & Ashrafian, H. (2026) · Frontiers in Science · doi:10.3389/fsci.2026.1810095 · Cited by 3 · see citing works

Machine learning: Python tools for studying biomolecules and drug design

Ryzhkov, F. V., Ryzhkova, Y. E., & Elinson, M. N. (2025) · Molecular Diversity · doi:10.1007/s11030-025-11199-2 · Cited by 3 · see citing works

Identifying Structure–Activity Relationships for Cyanine-Derived Antibiotics Using Machine Learning and Commercial Large Language Models

Lathem, A., Medvedeva, A., Santos, A. L., Li, B., Si, T., Kolomeisky, A. B., & Tour, J. M. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c01321 · Cited by 2 · see citing works

AI-Driven Innovations in Translational Research: Accelerating Bench-to-Bedside Pipelines Through Predictive Modelling and Digital Biomarkers

Judijanto, L. (2025) · European Journal of Applied Science Engineering and Technology · doi:10.59324/ejaset.2025.3(6).09 · Cited by 2 · see citing works

ViVo: A Temporal Modeling Framework That Boosts Statistical Power and Minimizes Animal Usage

Canudo‐Barreras, G., Romanos, E., Herrera, R. P., & Gimeno, M. C. (2025) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5c03326 · Cited by 2 · see citing works

Translational readthrough using TRIDs - Achievements and challenges for the treatment of inherited retinal disorders

Nagel‐Wolfrum, K., Wenck, N., & Zorin, M. (2026) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2026.101455 · Cited by 2 · see citing works

Intelligent Manufacturing Systems for Pharmaceuticals

Yingngam, B. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0298-8.ch004 · Cited by 2 · see citing works

Decade of AI in Drug Discovery: Hype or Reality?

Laroia, L. (2026) · International Journal of Pharmaceutical Sciences and Drug Research · doi:10.25004/ijpsdr.2026.180303 · Cited by 1 · see citing works

Artificial Intelligence in Drug Discovery and Development: From Computational Promise to Clinical Translation – A Pharmacological Perspective

Arora, S., Sharma, S., & Jayant, R. (2026) · doi:10.67796/jph.v1i2.16

Artificial intelligence–enabled drug discovery: A growing but largely early-stage clinical pipeline

Haque, W. Z., Sai-Palm, K., Rana, I., Esposito, A., Verlingue, L., Garassino, M. C., & Veronesi, P. (2026) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2026.103223

Success stories of AI in drug discovery - where do things stand?

Mak, K.-K., Balijepalli, M. K., & Pichika, M. R. (2022) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2022.1985108 · Cited by 51 · see citing works

Pharmaceuticals and Artificial Intelligence: From Faster Design to Better Odds, and What Remains UnprovenPreprint

Ghorbani, P. (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.23517152