Robo-Scientist Accelerates Disease Research

While science has established the parasitic causes of many tropical diseases, they remain a leading cause of death in less developed countries – because the drug discovery process is costly and time-intensive.  “Eve,” an artificially intelligent robot designed by the University of Cambridge (United Kingdom),  has been demonstrated as successful in discovering that an anti-cancer drug inhibits a key molecule known as DHFR in the malaria parasite.  Eve is designed to automate early-stage drug design. First, she systematically tests each member from a large set of compounds in the standard brute-force way of conventional mass screening. The compounds are screened against assays (tests) designed to be automatically engineered, and can be generated much faster and more cheaply than the bespoke assays that are currently standard. This enables more types of assay to be applied, more efficient use of screening facilities to be made, and thereby increases the probability of a discovery within a given budget.  Eve’s robotic system is capable of screening over 10,000 compounds per day. However, while simple to automate, mass screening is still relatively slow and wasteful of resources as every compound in the library is tested. It is also unintelligent, as it makes no use of what is learnt during screening. To improve this process, Eve selects at random a subset of the library to find compounds that pass the first assay; any ‘hits’ are re-tested multiple times to reduce the probability of false positives. Taking this set of confirmed hits, Eve uses statistics and machine learning to predict new structures that might score better against the assays.  Submitting that: “Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing,” the study authors write that: “Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases.”