AI3SD Video: Combining robotics and machine learning for accelerated drug discovery
AI3SD Video: Combining robotics and machine learning for accelerated drug discovery
Artificial intelligence has an increasing impact on drug discovery and development, offering opportunities to identify novel targets, hit, and lead-like compounds in accelerated timeframes. However, the success of any AI/ ML model depends on the quality of the input data, and the speed with which in silico predictions can be validated in vitro.
The talk will cover laboratory automation and robotics and the benefits they offer in terms of quality and speed of data generation synergise with AI/ ML-powered drug discovery approaches. The talk will cover some of the general trends in the industry, and also highlight successfully implemented case studies that show the how the combination of robotics and AI/ ML lead to accelerated project timelines and superior research outputs.
AI, AI3SD Event, Artificial Intelligence, Chemistry, Drug Discovery, Machine Intelligence, Machine Learning, Materials Discovery, ML, Scientific Discovery
Fleming, Thomas
24950a3d-3329-44b0-a682-86b99f194e5c
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
3 November 2021
Fleming, Thomas
24950a3d-3329-44b0-a682-86b99f194e5c
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Fleming, Thomas
(2021)
AI3SD Video: Combining robotics and machine learning for accelerated drug discovery.
Frey, Jeremy G., Kanza, Samantha and Niranjan, Mahesan
(eds.)
AI3SD Autumn Seminar Series 2021.
13 Oct - 15 Dec 2021.
(doi:10.5258/SOTON/AI3SD0160).
Record type:
Conference or Workshop Item
(Other)
Abstract
Artificial intelligence has an increasing impact on drug discovery and development, offering opportunities to identify novel targets, hit, and lead-like compounds in accelerated timeframes. However, the success of any AI/ ML model depends on the quality of the input data, and the speed with which in silico predictions can be validated in vitro.
The talk will cover laboratory automation and robotics and the benefits they offer in terms of quality and speed of data generation synergise with AI/ ML-powered drug discovery approaches. The talk will cover some of the general trends in the industry, and also highlight successfully implemented case studies that show the how the combination of robotics and AI/ ML lead to accelerated project timelines and superior research outputs.
Video
AI3SDAutumnSeminar-031121-TomFleming
- Version of Record
More information
Published date: 3 November 2021
Additional Information:
Tom Fleming MChem is the COO of biotech platform company Arctoris, which he co-founded in Oxford in 2016. Tom’s background is in cancer research, having worked in academia as well as at leading CROs and pharmaceutical corporations. A chemical biologist by training, he has unique insights into preclinical drug discovery, including the critical steps from target identification and high-throughput screening up to lead optimization. Tom was a Fellow of the Royal Commission of 1851 at the University of Oxford, and is a SME Leader of the Royal Academy of Engineering.
Venue - Dates:
AI3SD Autumn Seminar Series 2021, 2021-10-13 - 2021-12-15
Keywords:
AI, AI3SD Event, Artificial Intelligence, Chemistry, Drug Discovery, Machine Intelligence, Machine Learning, Materials Discovery, ML, Scientific Discovery
Identifiers
Local EPrints ID: 452735
URI: http://eprints.soton.ac.uk/id/eprint/452735
PURE UUID: 83a14fbc-2f0f-4bcd-94c8-ce3cf5822ea0
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Date deposited: 17 Dec 2021 17:39
Last modified: 17 Mar 2024 03:51
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Author:
Thomas Fleming
Editor:
Mahesan Niranjan
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