Designing Drugs Using a Robot Scientist

Primary supervisor

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Funding

  • Competition Funded Project (Students Worldwide)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Project description

A Robot Scientist is a physically implemented robotic system that applies techniques from artificial intelligence to execute cycles of automated scientific experimentation. We developed the first Robot Scientist `Adam?, Adam was the first machine to discover novel scientific knowledge. More recently we have developed the Robot Scientist "Eve" for drug design. Eve?s focus has been on neglected tropical diseases such as malaria, African sleeping sickness, etc. Eve?s greatest limitation is that to test its QSAR hypotheses it can only select compounds from its library: it cannot synthesise new compounds. This is restrictive because even the largest compound libraries in the world have only a few million compounds, whereas the potential number of compounds that could be synthesised is probably at least 1060. Laboratory automation equipment is beginning to be become available that could synthesise almost arbitrary compounds, and these could be integrated with Eve.

Constructive machine learning
The goal is to develop machine learning software to select compounds for automatic synthesis to test hypotheses about what compounds will make good drugs. This type of machine learning has been little explored as it is `active? (selects experiments), and `constructive? (selects from an almost infinite set of examples).

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