David Winkler is Professor of Biochemistry and Chemistry at La Trobe University, Professor of Pharmacy at the University of Nottingham, and Professor of Medicinal Chemistry at Monash University. He applies computational chemistry, AI, and machine learning to the design of drugs, agrochemicals, electrooptic materials, nanomaterials, green corrosion inhibitors, catalysts, and biomaterials. His is a recipient of an ACS Skolnik award, an RACI Adrien Albert and Distinguished Fellowship awards, RAEng (UK) Distinguished Fellowship, and the AMMA Medal. He has written >300 journal articles and book chapters (6 ISI Highly Cited), is an inventor on 25 patents and has an h-index of 70. He is 61st most highly ranked scientist in machine learning (ScholarGPS worldwide 2020-25)
OpenTox Virtual Conference 2026
Converting Nanotoxicity Data to Information Using Artificial Intelligence
Although decades of nanotoxicology research have generated extensive and diverse data sets, data is not equal to information. It is essential to extract critical information from vast data streams and machine learning (as subset of artificial intelligence algorithms) and molecular simulation play key roles in transforming these highly complex data into actionable information and in deciphering toxicity-related molecular mechanisms.
However, several obstacles must be overcome to fully realize the potential of these paradigm-changing methods. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases that hamper interoperability of data and constitute a roadblock to modelling, the scarcity of nanomaterials descriptors (mathematical features) that capture distributions of properties, and the inability to simulate NMs at realistic spatial and temporal scales. This paper will summarize these capability gaps, and the tools required to fill these gaps. Specifically, we discuss the applications of machine learning to nanotoxicology research and the development of safe-by-design protocols for nanomaterials development and commercialisation. I also provide a perspective on future trends and challenges.
Australia (National Enabling Technologies funding from DIISR), three European Union Horizon 2020 consortia– Resilient Value Chains 2023 INSIGHT: integrated models for development and assessment of high impact chemicals and materials; EU H2020 SABYDOMA: safety by design of nanomaterials: from lab manufacture to governance and communication, project 862296; Foundations for Tomorrow’s Industry: SEP-210487951 Proposal: 814572-2; Proposal acronym: NanoSolveIT, 2019, and EU COST Action MODENA–modelling the biological effects of nanoparticles, 2012.
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2. M. Hart, K. Idanwekhai, V.M. Alves, A.J.M. Miller, J.L. Dempsey, J.F. Cahoon, C.-H. Chen, D.A. Winkler, E.N. Muratov, A. Tropsha. Chem. Mater. 36, 9046 (2024)
3. E. Bilgi, D.A. Winkler, C. Oksel Karakus. J. Drug Target., 32, 66 (2024)
4. X. Yan, T. Yue, Y. Yin, H. Hao Zhu, G. Jiang, B. Yan, D.A. Winkler. Chem. Rev, 123, 8575 (2023).
5. J. van Rijn, A. Afantitis, M. Culha, M. Dusinska, T. Exner, N. Jealiazkova, E.M. Longhin, I. Lynch, G. Melagraki, P. Nymark, D.A. Winkler, H. Yilmaz, E. Willighagen.. J. Cheminfo., 14, 57 (2022).
6. C. Oksel Karakus, D.A. Winkler. Nano Fut. 5, 022002 (2021).
7. I. Lynch, A. Afantitis, T. Exner, M. Himly, V. Lobaskin, P. Doganis, D. Maier, N. Sanabria, A.G. Papadiamantis, A. Rybinska-Fryca, M. Gromelski, E. Willighagen, B.D. Johnston, M. Gulumian, M. Matzke, A.G. Etxabe, N. Bossa, A. Serra, D. Greco, I. Liampa, S. Harper, K. Tämm, A.C. Jensen, P. Kohonen, D.A. Winkler, L. Slater, H. Sarimveis, G. Melagraki. Nanomater., 10, 2493 (2020).
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9. T.C. Le, H. Yin, R. Chen, Y. Chen, L. Zhao, P.S. Casey, C. Chen, D.A. Winkler. Small, 12,3568 (2016).
10. D.A. Winkler. Toxicol. Appl. Pharmacol. 299, 96 (2016).
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12. D.A. Winkler, E. Mombelli, A. Pietroiusti, L. Tran, A. Worth, B. Fadeel, M.J. McCall. Toxicol. 313, 15 (2013).
13. T.C. Le, V.C. Epa, F.R. Burden, D.A. Winkler. Chem. Rev. 112, 2889 (2012).
14. V.C. Epa, F.R. Burden, C. Tassa, R. Weissleder, S. Shaw, D.A. Winkler. Nano Lett. 12, 5808‚ (2012).