After I completed my PhD in Computational Chemistry at the University of Lund and postdoctoral research at the University of Cambridge and the Czech Academy of Sciences, I joined AstraZeneca in 2004. I currently lead the Discovery Sciences Computational Chemistry 团队 within BioPharmaceuticals R&D, providing computational solutions for drug discovery.

I am passionate 关于 pushing the boundaries of using artificial intelligence and machine learning in drug discovery. A key focus for me has been on building both the 团队 within BioPharmaceuticals R&D and collaborating with external experts to advance innovation in drug design and synthesis.

Through a pioneering collaboration with the University of Muenster, my 团队 demonstrated the first application of recurrent Neural Networks to molecular design which has been published in two recent, highly-cited 文章s. This methodology allows us to design novel drug molecules using machine learning to navigate the b阅读th of chemical space and to exploit our vast knowledge base.


I am fascinated by applying the latest artificial intelligence and machine learning technologies to drug discovery. It has the potential, together with further progress in automation, to transform the drug discovery process.

Ola Engkvist Associate Director, Computational Chemistry, Discovery Sciences, R&D
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Key Achievements

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2018

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2018

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2009

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Computational prediction of chemical reactions: current status and outlook.英雄联盟外围投注

Drug Discovery Today. 2018; 23(6): 1203-1218. Engkvist O, Norrby P-O, Selmi N et al. Publication link: https://www.sciencedirect.com/science/文章/pii/S1359644617305068

The rise of deep learning in drug discovery.英雄联盟外围投注

 Drug Discovery Today. 2018; 23(6): 1241-1250. Chen H, Engkvist O, Wang Y, et al. Publication link: https://www.sciencedirect.com/science/文章/pii/S1359644617303598

Molecular de-novo design through deep reinforcement learning.英雄联盟外围投注

Journal of Cheminformatics. 2017; 9(48). Olivecrona M, Blaschke T, Engkvist O, Chen H. Publication link: https://jcheminf.biomedcentral.com/文章s/10.1186/s13321-017-0235-x

Application of Generative Autoencoder in De Novo Molecular Design.英雄联盟外围投注

Molecular Informatics. 2018; 37(1-2): 1700123. Blaschke T, Olivecrona M, Engkvist O et al. Publication link: https://onlinelibrary.wiley.com/doi/full/10.1002/minf.201700123

BIGCHEM: Challenges and Opportunities for Big Data Analysis in Chemistry.英雄联盟外围投注

Molecular Informatics. 2016; 35(11-12): 615-621, Tetko I.V., Engkvist O, Koch U et al. Publication link: https://onlinelibrary.wiley.com/doi/full/10.1002/minf.201600073