Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases

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Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases. / Williams, Kevin Stewart; Bilsland, Elizabeth ; Sparkes, Andrew Charles; Aubrey, Wayne; Young, Michael; Soldatova, Larisa Nikolaevna; de Grave, Kurt; Ramon, Jan; de Clare, Michaela ; Sirawaraporn, Worachart; Oliver, Stephen G.; King, Ross.

In: Interface, Vol. 12, No. 104, 20141289, 03.03.2015.

Research output: Contribution to journalArticlepeer-review

Harvard

Williams, KS, Bilsland, E, Sparkes, AC, Aubrey, W, Young, M, Soldatova, LN, de Grave, K, Ramon, J, de Clare, M, Sirawaraporn, W, Oliver, SG & King, R 2015, 'Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases', Interface, vol. 12, no. 104, 20141289. https://doi.org/10.1098/rsif.2014.1289

APA

Williams, K. S., Bilsland, E., Sparkes, A. C., Aubrey, W., Young, M., Soldatova, L. N., de Grave, K., Ramon, J., de Clare, M., Sirawaraporn, W., Oliver, S. G., & King, R. (2015). Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases. Interface, 12(104), [20141289]. https://doi.org/10.1098/rsif.2014.1289

Author

Williams, Kevin Stewart ; Bilsland, Elizabeth ; Sparkes, Andrew Charles ; Aubrey, Wayne ; Young, Michael ; Soldatova, Larisa Nikolaevna ; de Grave, Kurt ; Ramon, Jan ; de Clare, Michaela ; Sirawaraporn, Worachart ; Oliver, Stephen G. ; King, Ross. / Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases. In: Interface. 2015 ; Vol. 12, No. 104.

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@article{4c84737dd99b41548696c127c24a48fc,
title = "Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases",
abstract = "There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax",
keywords = "drug design, artificial intelligence, quantitative structure activity relationship",
author = "Williams, {Kevin Stewart} and Elizabeth Bilsland and Sparkes, {Andrew Charles} and Wayne Aubrey and Michael Young and Soldatova, {Larisa Nikolaevna} and {de Grave}, Kurt and Jan Ramon and {de Clare}, Michaela and Worachart Sirawaraporn and Oliver, {Stephen G.} and Ross King",
note = "UK Biotechnology and Biological Sciences Research Council (BB/F008228/1; European Commission under the FP7 Collaborative Programme, UNICELLSYS; KU Leuven (GOA/08/008); ERC (240186)",
year = "2015",
month = mar,
day = "3",
doi = "10.1098/rsif.2014.1289",
language = "English",
volume = "12",
journal = "Interface",
issn = "1742-5689",
publisher = "Royal Society",
number = "104",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases

AU - Williams, Kevin Stewart

AU - Bilsland, Elizabeth

AU - Sparkes, Andrew Charles

AU - Aubrey, Wayne

AU - Young, Michael

AU - Soldatova, Larisa Nikolaevna

AU - de Grave, Kurt

AU - Ramon, Jan

AU - de Clare, Michaela

AU - Sirawaraporn, Worachart

AU - Oliver, Stephen G.

AU - King, Ross

N1 - UK Biotechnology and Biological Sciences Research Council (BB/F008228/1; European Commission under the FP7 Collaborative Programme, UNICELLSYS; KU Leuven (GOA/08/008); ERC (240186)

PY - 2015/3/3

Y1 - 2015/3/3

N2 - There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax

AB - There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax

KW - drug design

KW - artificial intelligence

KW - quantitative structure activity relationship

UR - http://hdl.handle.net/2160/41956

U2 - 10.1098/rsif.2014.1289

DO - 10.1098/rsif.2014.1289

M3 - Article

VL - 12

JO - Interface

JF - Interface

SN - 1742-5689

IS - 104

M1 - 20141289

ER -

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