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How artificial intelligence is changing drug discovery
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“AI is, for example, the major driver behind the current trend toward personalized medicine, with treatments being tailored to each patient's specific biological profile (Fleming, 2018;Lichfield, 2018).”
From Artificial Intelligence and Management: The Automation–Augmentation Paradox (2021) · cites this paper as Fleming, 2018
Experimental — accuracy not yet measuredIn the citing paper
“Many more examples are available [3,32,33,34,35,36,37], showing that AI-based methods can accelerate the drug discovery process and enable the development of more effective medications.”
From The role of AI in drug discovery: challenges, opportunities, and strategies (2023) · cites this paper as [37]
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Artificial Intelligence and Management: The Automation–Augmentation Paradox
Raisch, S., & Krakowski, S. (2021) · Academy of Management Review · doi:10.5465/amr.2018.0072 · Cited by 2,755
Artificial intelligence in drug discovery and development
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“Even then, nine out of ten therapeutic molecules fail Phase II clinical trials and regulatory approval [31,32].”
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Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Gupta, R., Srivastava, D., Sahu, M., Tiwari, S., Ambasta, R. K., & Kumar, P. (2021) · Molecular Diversity · doi:10.1007/s11030-021-10217-3 · Cited by 1,473
Deep learning: new computational modelling techniques for genomics
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The role of artificial intelligence in healthcare: a structured literature review
Secinaro, S. F., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01488-9 · Cited by 1,286
The ethics of AI in health care: A mapping review
Morley, J., Machado, C. C. V., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & Floridi, L. (2020) · Social Science & Medicine · doi:10.1016/j.socscimed.2020.113172 · Cited by 1,105
“…in diagnosis (Arieno et al., 2019; De Fauw et al., 2018; Kunapuli et al., 2018), drug discovery (Álvarez-Machancoses and Fernández-Martínez, 2019; Fleming, 2018), epidemiology (Hay et al., 2013), personalised medicine (Barton et al., 2019; Cowie et al., 2018; Dudley et al., 2015) and operational…”
BackgroundArtificial intelligence in drug development: Present status and future prospects
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Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100899 · Cited by 927
ADMET modeling approaches in drug discovery
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A Structure-Based Drug Discovery Paradigm
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“, a UK-based world class AI-driven drug design company [93] is collaborating with Sanofi to find a cure for metabolic disorders [94], and Clegene, another leading pharmaceutical company, aims to accelerate drug discovery in the areas of autoimmunity and oncology [95].”
BackgroundThe role of AI in drug discovery: challenges, opportunities, and strategies
Blanco-González, A., Cabezón, A., Seco-González, A., Conde-Torres, D., Antelo-Riveiro, P., Piñeiro, Á., & Garcia-Fandino, R. (2023) · Pharmaceuticals · doi:10.3390/ph16060891 · Cited by 690
“Many more examples are available 3,32–37 , showing that AI-based methods can accelerate the drug discovery process and enable the development of more effective medications.”
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Artificial intelligence in COVID-19 drug repurposing
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Exploiting machine learning for end-to-end drug discovery and development
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A drug-likeness toolbox facilitates ADMET study in drug discovery
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Artificial Intelligence and Personalized Medicine
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Big data and artificial intelligence modeling for drug discovery
Zhu, H. (2020) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010919-023324 · Cited by 455
“Drug attritions that happen in clinical studies induce great resource loss, and currently, nine out of ten drug candidates fail between phase I clinical trials and regulatory approval (2).”
BackgroundArtificial intelligence vs COVID-19: limitations, constraints and pitfalls
Naudé, W. (2020) · AI & SOCIETY · doi:10.1007/s00146-020-00978-0 · Cited by 368
“Even long before the COVID-19 outbreak, AI was lauded for its potential to contribute to new drug discovery, see e.g. Coldeway (2019), Fleming (2018), Segler et al. (2018) and Smith (2018).”
BackgroundEthnobotany and the Role of Plant Natural Products in Antibiotic Drug Discovery
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The significance of artificial intelligence in drug delivery system design
Hassanzadeh, P., Atyabi, F., & Dinarvand, R. (2019) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2019.05.001 · Cited by 326
Deep generative molecular design reshapes drug discovery
Zeng, X., Wang, F., Luo, Y., Kang, S.-G., Tang, J., Lightstone, F. C., Fang, E. F., Cornell, W., Nussinov, R., & Cheng, F. (2022) · Cell Reports Medicine · doi:10.1016/j.xcrm.2022.100794 · Cited by 295
Human-machine collaboration in managerial decision making
Haesevoets, T., De Cremer, D., Dierckx, K., & Van Hiel, A. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106730 · Cited by 280
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Combining Human and Artificial Intelligence: Hybrid Problem-Solving in Organizations
Raisch, S., & Fomina, K. (2024) · Academy of Management Review · doi:10.5465/amr.2021.0421 · Cited by 378
“Pharmaceutical companies including Pfizer, Roche, and Sanofi use them to discover drugs when there are either no drugs for a disease or the existing drugs have limited efficacy (Deng, Yang, Ojima, Samaras, & Wang, 2022; Fleming, 2018).”
BackgroundHuang, J., Xu, Y., Xue, Y., Huang, Y., Li, X., Chen, X., Xu, Y., Zhang, D., Zhang, P., Zhao, J., et al. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00991-2 · Cited by 280
“The initial MIC values (MIC 0 ) for CRRI3, CRRI4, CRRI7 and penicillin are listed in Supplementary Table 15.”
BackgroundInfluentialArtificial intelligence for drug discovery: Resources, methods, and applications
Chen, W., Liu, X., Zhang, S., & Chen, S. (2023) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2023.02.019 · Cited by 301
“8 billion and 15 years on average.(1) The lowefficacy and high-cost characteristics of conventional methods have become the hurdles of drug discovery.”
BackgroundOpen access in silico tools to predict the ADMET profiling of drug candidates
Kar, S., & Leszczyński, J. (2020) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2020.1798926 · Cited by 262
“molecule drugs [2,4] and 59 NCE (comprised of 64% small molecule drugs) were approved in the years 2016 and 2018, respectively.”
BackgroundArtificial intelligence for aging and longevity research: Recent advances and perspectives
Zhavoronkov, A., Mamoshina, P., Vanhaelen, Q., Scheibye-Knudsen, M., Moskalev, A., & Aliper, A. (2019) · Ageing Research Reviews · doi:10.1016/j.arr.2018.11.003 · Cited by 246
“These examples illustrate that AI technologies can be applied at di ff erent levels, with the goal of facilitating the development of new pharmaceuticals quicker, cheaper, and more e ff ectively (Fleming, 2018).”
Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling
Zhao, L., Ciallella, H. L., Aleksunes, L. M., & Zhu, H. (2020) · Drug Discovery Today · doi:10.1016/j.drudis.2020.07.005 · Cited by 244
“…improvements in computational power coupled with improvements in artificial intelligence (Al) technology, including the development of various deep learning algorithms [117–119], positioned CADD studies to progress to a new stage and capitalize on the rich infrastructure of big data studies [120].”
BackgroundHigh-Throughput Screening Platforms in the Discovery of Novel Drugs for Neurodegenerative Diseases
Aldewachi, H. S., Al-Zidan, R. N., Conner, M. T., & Salman, M. M. (2021) · Bioengineering · doi:10.3390/bioengineering8020030 · Cited by 217
“Researchers discovered that one of the five tested compounds had prominent activity in slowing the neurological symptoms of ALS in a mice model [177].”
Humans as Creativity Gatekeepers: Are We Biased Against AI Creativity?
Magni, F., Park, J., & Chao, M. M. (2024) · Journal of Business and Psychology · doi:10.1007/s10869-023-09910-x · Cited by 201
“For instance, AI is currently being used to perform creative tasks in the scientific domain—e.g., to develop new compounds for medicines (Fleming, 2018; Popova et al., 2018).”
Embedded ethics: a proposal for integrating ethics into the development of medical AI
McLennan, S., Fiske, A., Tigard, D. W., Müller, R., Haddadin, S., & Buyx, A. (2022) · BMC Medical Ethics · doi:10.1186/s12910-022-00746-3 · Cited by 241
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“It already exhibits great potential in several health application fields, from clinical diagnosis (ÁlvarezMachancoses et al. 2019; Fleming 2018), high levels of precision in cancer prediction (Kuo et al.”
BackgroundDeep Learning Based Drug Screening for Novel Coronavirus 2019-nCov
Zhang, H., Saravanan, K. M., Yang, Y., Hossain, M. T., Li, J., Ren, X., Pan, Y., & Wei, Y. (2020) · Interdisciplinary Sciences: Computational Life Sciences · doi:10.1007/s12539-020-00376-6 · Cited by 122
Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns
Cova, T. F. G. G., & Pais, A. A. C. C. (2019) · Frontiers in Chemistry · doi:10.3389/fchem.2019.00809 · Cited by 193
“The latter have been applied for e.g., in QSAR models and drug design (Kadurin et al., 2017; Chen et al., 2018; Fleming, 2018; Green et al., 2018; Gupta et al., 2018; Li et al., 2018b; Lo et al., 2018; Popova et al., 2018; Simões et al., 2018) aiming at identifying systems, molecules and materials…”
BackgroundMethodInfluentialOverview of Recent Strategic Advances in Medicinal Chemistry
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Enhancing preclinical drug discovery with artificial intelligence
Vijayan, R., Kihlberg, J. O., Cross, J. B., & Poongavanam, V. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2021.11.023 · Cited by 191
“4 The use of AI technologies is driving new opportunities across the drug discovery and development continuum, starting from target identi fi cation through to preclinical development (Fig.”
BackgroundAdvances in artificial intelligence for drug delivery and development: A comprehensive review
Gholap, A. D., Uddin, M. J., Faiyazuddin, M., Omri, A., Gowri, S., & Khalid, M. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108702 · Cited by 197
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“Empirical Strategy and Identification The data used for our primary analysis cover the years between 2010 and 2019, which capture the period of rapid advances in AI technologies (Fleming 2018).”
Artificial Intelligence (AI) in Pharmacy: An Overview of Innovations
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Deep learning tools for advancing drug discovery and development
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“Another such DL-based tool called FRnet-DTI, which is a CNN-based classifier for drug target interaction prediction and uses an auto-encoder-based feature manipulation (Rayhan et al. 2020, 2018).”
BackgroundMethodTribulations and future opportunities for artificial intelligence in precision medicine
Carini, C., & Seyhan, A. A. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-05067-0 · Cited by 221
“Numerous other examples highlight the capacity of AI-based methods to expedite drug screening and discovery [92] and enhance the development of more effective therapies, drug combinations for drug synergies [93, 94], and drug repurposing [88, 95–103] for various other diseases [104–110].”
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Automated De Novo Drug Design: Are We Nearly There Yet?
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Artificial intelligence and machine learning applications in biopharmaceutical manufacturing
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Evaluating artificial intelligence in medicine: phases of clinical research
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An Overview of Artificial Intelligence in Oncology
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“Examples range from new drug discoveries (Fleming 2018, Paul et al. 2020) to skin cancer detection (Esteva et al. 2017), automated screening of diabetic retinopathy (Gulshan et al. 2016, 2019), fracture detection in radiographs (Badgeley et al. 2019, Qi et al. 2020, Olczak et al. 2021), detecting…”
BackgroundIn silico approaches and tools for the prediction of drug metabolism and fate: A review
Kazmi, S. R., Ren, J., Yu, M., Jung, C., & Na, D. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.01.008 · Cited by 128
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Three Problems with Big Data and Artificial Intelligence in Medicine
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You Can’t Have AI Both Ways: Balancing Health Data Privacy and Access Fairly
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“…personalized medicine, clinical research, drug development, administrative processes, and the mitigation of health disparities (Shibata & Wada, 2011; Fleming, 2018; Shortliffe & Sepúlveda, 2018; Davenport & Kalakota, 2019; Fiske, Henningsen, & Buyx, 2019; Liu et al., 2019; Schork, 2019; Woo, 2019).”
Current Strategies of Antiviral Drug Discovery for COVID-19
Mei, M., & Tan, X. (2021) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2021.671263 · Cited by 111
“In the big data era, artificial intelligence (AI) algorithms are increasingly being applied for rapid and cost-effective drug discovery (Fleming, 2018).”
BackgroundReinventing Innovation Management: The Impact of Self-Innovating Artificial Intelligence
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Artificial Intelligence (AI) in Drugs and Pharmaceuticals
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Is College Education Less Necessary with AI? Evidence from Firm-Level Labor Structure Changes
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“In recent years, artificial intelligence (AI) has propelled technology and business innovations in many industries, including healthcare [22, 32], higher education [62], and financial services [29].”
BackgroundNext-generation business models for artificial intelligence start-ups in the healthcare industry
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“Moreover, AI can create value where it previously did not exist and can benefit from unstructured data, such as in drug discovery (Noorbakhsh-Sabet et al., 2019; Fleming, 2018; Jing et al., 2018).”
BackgroundMethodInfluentialDiscovering small-molecule therapeutics against SARS-CoV-2
Tiwari, V., Beer, J. C., Sankaranarayanan, N. V., Swanson-Mungerson, M. A., & Desai, U. R. (2020) · Drug Discovery Today · doi:10.1016/j.drudis.2020.06.017 · Cited by 95
Artificial Intelligence and Machine Learning Applied at the Point of Care
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“Despite the popularity of AI/ML/DL technologies (Fleming, 2018) and the positive press of many applications to healthcare and the pharmaceutical and medical devices industry, a large proportion of researchers have yet to uncover the full capabilities Frontiers in Pharmacology | www.frontiersin.org…”
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Machine Learning in Drug Discovery and Development Part 1: A Primer
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Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade
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Challenges and Opportunities in Central Nervous System Drug Discovery
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“There is evidence that some of these systems have superior diagnostic and predictive capabilities when compared to human experts (Esteva et al. 2017; Fleming 2018; Rajpurkar et al. 2017; Tschandl et al. 2019).”
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The dark side of AI identity: Investigating when and why AI identity entitles unethical behavior
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Use of artificial intelligence to enhance phenotypic drug discovery
Malandraki-Miller, S., & Riley, P. R. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2021.01.013 · Cited by 84
Integration of AI and traditional medicine in drug discovery
Khan, S. R., Rijjal, D. A., Piro, A., & Wheeler, M. B. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2021.01.008 · Cited by 79
DeepMalaria: Artificial Intelligence Driven Discovery of Potent Antiplasmodials
Arshadi, A. K., Salem, M., Collins, J., Yuan, J. S., & Chakrabarti, D. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.01526 · Cited by 78
“The validation dataset consists of the results from previously performed HTS in University of Central Florida at the Chakrabarti Laboratory, consisting of natural-products, kinase inhibitors from commercial vendors Asinex (Winston-Salem, NC)and ChemDiv (San Diego, CA) libraries.”
BackgroundInfluentialRole of Artificial Intelligence in Kidney Disease
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“The continued rapid growth in computer-processing power over the past two decades, the availability of large data sets and the development of advanced algorithms have driven major improvements in machine learning[3].”
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Advances in preclinical approaches to Chagas disease drug discovery
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The Debate on the Ethics of AI in Health Care: a Reconstruction and Critical Review
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“…cases for AI in health care — including AI assistance in health maintenance (Chun 2020), precision medicine (Abramoff, Lavin, Birch, Shah, and Folk 2018), and drug discovery (e.g., P fi zer ’ s use of IBM Watson; Fleming 2018) — demonstrate how this new technology is already disrupting the industry.”
BackgroundJebreen, K., Radwan, E., Kammoun-Rebai, W., Alattar, E., Radwan, A., Safi, W., Radwan, W., & Alajez, M. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05465-4 · Cited by 63
“AI applications in medicine have the potential to support a variety of tasks such as clinical research [5], therapy [6], administrative procedures [7], and drug development [8] due to their capacity to learn from large sets of clinical data.”
BackgroundArtificial Intelligence for Biology
Hassoun, S., Jefferson, F., Shi, X., Stucky, B., Wang, J., & Rosa, E. (2022) · Integrative and Comparative Biology · doi:10.1093/icb/icab188 · Cited by 64
Enhanced Graph Isomorphism Network for Molecular ADMET Properties Prediction
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“dollars in recent years [6], [7], respectively.”
Wang, B., Zhang, T., Liu, Q., Sutcharitchan, C., Zhou, Z., Zhang, D., & Li, S. (2024) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2024.101144 · Cited by 68
Niazi, S. K. (2025) · Pharmaceuticals · doi:10.3390/ph18091271 · Cited by 61
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“Currently, to develop one new market-approval prescription medicine takes more than 10 years and costs about $2.6 billion [1].”
BackgroundInfluentialAn adaptive graph learning method for automated molecular interactions and properties predictions
Li, Y., Hsieh, C., Lu, R., Gong, X., Wang, X., Li, P., Liu, S., Tian, Y., Jiang, D., Yan, J., et al. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00501-8 · Cited by 62
“Given the perturbed test set M′ with properties Q′, we predict the property set P′ by equation (5):”
MethodInfluential
Metadata
- Authors
- Fleming, N.
- Corresponding author
- Fleming, Nic
- Venue
- Nature
- Published
- 2018-05-30
- Volume
- 557
- Issue
- 7707
- Pages
- S55-S57
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2806834952
- Cited by
- 546
- References
- 0
- Citations by year
- 2026: 41 · 2025: 49 · 2024: 81 · 2023: 95 · 2022: 97 · 2021: 81 · 2020: 56 · 2019: 38 · 2018: 7
- FWCI
- 34.22
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence, drug discovery, machine learning, pharmaceuticals, computer-aided drug design
- MeSH terms
- Machine Learning, Algorithms, Amyotrophic Lateral Sclerosis, Animals, Artificial Intelligence, Automation, Drug Industry, Humans, Neoplasms, Pattern Recognition, Automated, Robotics, Efficiency, Organizational, Mice, Drug Discovery, Precision Medicine
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