Cheaper Faster Drug Development Validated By The Repositioning Of Drugs Against Neglected Tropical Diseases.


Autoria(s): Williams, Kevin; Bilsland, Elizabeth; Sparkes, Andrew; Aubrey, Wayne; Young, Michael; Soldatova, Larisa N; De Grave, Kurt; Ramon, Jan; de Clare, Michaela; Sirawaraporn, Worachart; Oliver, Stephen G; King, Ross D
Contribuinte(s)

UNIVERSIDADE DE ESTADUAL DE CAMPINAS

Data(s)

01/03/2015

27/11/2015

27/11/2015

Resumo

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.

12

20141289

Identificador

Journal Of The Royal Society, Interface / The Royal Society. v. 12, n. 104, p. 20141289, 2015-Mar.

1742-5662

10.1098/rsif.2014.1289

http://www.ncbi.nlm.nih.gov/pubmed/25652463

http://repositorio.unicamp.br/jspui/handle/REPOSIP/202100

25652463

Idioma(s)

eng

Relação

Journal Of The Royal Society, Interface / The Royal Society

J R Soc Interface

Direitos

fechado

Fonte

PubMed

Palavras-Chave #Artificial Intelligence #Drug Design #Quantitative Structure Activity Relationship
Tipo

Artigo de periódico