{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T14:07:01Z","timestamp":1789049221164,"version":"build-2803163510"},"reference-count":318,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:00:00Z","timestamp":1788998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Oncologic drug development is lengthy (~14 years) and expensive (~1.2 billion USD) with low clinical trial success rates (4.1%). Big data and artificial intelligence (AI) are widely proposed as tools to address these challenges. In this review, we examine the current performance and future potential of big data and AI applied to preclinical discovery and development, clinical trials, and the regulatory approval process. We first examine the data foundation required for effective AI, including data harmonization, data commons, and analytical tools. We then assess preclinical applications spanning target identification, compound-library curation, virtual ligand screening, generative chemical design, and high-throughput and high-content screening. In clinical development, we consider the use of big data and AI for outcome prediction, trial design, external and synthetic control arms, adaptive monitoring, and in silico trials. Finally, we discuss how post-approval electronic health records can generate real-world data and real-world evidence to support drug repurposing and improve future oncology drug discovery. Big data is conventionally characterized by a series of \u201cVs.\u201d In this review, we have used seven \u201cVs\u201d spanning descriptive and constraining properties of big data and a singular outcome. We have proposed an eighth, Vernacular, a constraint defined as the combined alignment of data semantics and terminology, data representation, data exchange, and data governance across heterogeneous, independently generated datasets to promote interoperability and combined analysis. Although cancer data exhibit substantial Volume, Velocity, and Variety, they remain distributed across fragmented repositories that often cannot be readily integrated. We conclude with a discussion of tabulated resources currently available for the application of big data and AI to oncologic therapeutics.<\/jats:p>","DOI":"10.3390\/cancers18182939","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T13:04:57Z","timestamp":1789045497000},"page":"2939","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Big Data and Artificial Intelligence in Cancer Drug Discovery: Promise, Challenges, and Emerging Opportunities"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8681-5769","authenticated-orcid":false,"given":"Fakhar U.","family":"Singhera","sequence":"first","affiliation":[{"name":"Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA"},{"name":"Ellison Medical Institute, Los Angeles, CA 90064, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1902-9079","authenticated-orcid":false,"given":"Justin M.","family":"Overhulse","sequence":"additional","affiliation":[{"name":"Department of Chemistry, University of Southern California, Los Angeles, CA 90089, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Terrence M.","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Chemistry, University of Southern California, Los Angeles, CA 90089, USA"},{"name":"Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA 90033, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2699-9708","authenticated-orcid":false,"given":"Jonathan E.","family":"Katz","sequence":"additional","affiliation":[{"name":"Ellison Medical Institute, Los Angeles, CA 90064, USA"},{"name":"Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1515-0952","authenticated-orcid":false,"given":"Jerry S. H.","family":"Lee","sequence":"additional","affiliation":[{"name":"Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA"},{"name":"Ellison Medical Institute, Los Angeles, CA 90064, USA"},{"name":"Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA"},{"name":"Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3540-6663","authenticated-orcid":false,"given":"Charles E.","family":"McKenna","sequence":"additional","affiliation":[{"name":"Department of Chemistry, University of Southern California, Los Angeles, CA 90089, USA"},{"name":"Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA 90033, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"ref_1","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","unstructured":"(2026, May 07). Cancer Stat Facts: Cancer of Any Site, Available online: https:\/\/seer.cancer.gov\/statfacts\/html\/all.html."},{"key":"ref_3","first-page":"10","article-title":"Cancer statistics, 2025","volume":"75","author":"Siegel","year":"2025","journal-title":"CA Cancer J. 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