John P. Overington

ORCID iD
https://orcid.org/0000-0002-5859-1064
  • Also known as
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jpo

Sources:
John P. Overington (2015-06-26)

  • Country
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United Kingdom

Sources:
John P. Overington (2016-01-24)

  • Keywords
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chemical biology,

Sources:
John P. Overington (2015-01-08)

bioinformatics,

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John P. Overington (2015-01-08)

drug discovery,

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John P. Overington (2015-01-08)

chemoinformatics,

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John P. Overington (2015-01-08)

structural biology

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John P. Overington (2015-01-08)

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John P. Overington (2017-04-02)

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Scopus Author ID: 7004362915

Sources:
Scopus - Elsevier (2013-07-23)

ResearcherID: G-8607-2015

Sources:
ResearcherID (2015-06-26)

Biography

John studied Chemistry at the University of Bath (1987), and then completed a PhD at Birkbeck College, University of London, in the Department of Crystallography (1990). There he developed automated approaches to protein modelling, and explored sequence-structure relationships, particularly the constraints applied by the local physical environment of a residue in a mutational trajectory. John then held a postdoctoral position at the Imperial Cancer Research Fund (now part of CRUK). John then joined Pfizer (1992), originally as a computational chemist, progressing to a role where he led a large and highly multidisciplinary group combining rational drug design with structural biology. During this time, John explored the reasons for target/drug attrition and the falling productivity of the pharmaceutical industry. In 2000 John moved to the biotech company, Inpharmatica, where he led the development of a series of computational and data platforms to improve drug discovery; these included the medicinal chemistry database StARLite. In 2008 John was central to the transfer of this database to the EMBL-EBI, where the successor is now known as ChEMBL. While there his work expanded into large-scale patent informatics with the Open patent database SureChEMBL. John then moved (2015) to a London-based Artificial Intelligence technology company - Stratified Medical (later renamed BenevolentAI), where he continued his translational drug discovery informatics R&D activities, applying machine learning methods to the development of novel biomedical data extraction and integration strategies, and integrating deep learning and other machine learning approaches to drug target validation and drug optimisation. In 2017 John joined the UK's Medicine Discovery Catapult as CIO, where he leads the development and application of informatics approaches to promote and support innovative, fast-to-patient drug discovery in the UK through collaborative projects across the applied R&D community.
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