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Smart robot accelerates cancer treatment research by finding optimal treatment combinations

Reporter: Aviva Lev-Ari, PhD, RN

A new smart research system developed at Uppsala University accelerates research on cancer treatments by finding optimal treatment drug combinations. It was developed by a research group led by Mats Gustafsson, Professor of Medical Bioinformatics.

The “lab robot” system plans and conducts experiments with many substances, and draws its own conclusions from the results. The idea is to gradually refine combinations of substances so that they kill cancer cells without harming healthy cells.

Instead of just combining a couple of substances at a time, the new lab robot can handle about a dozen drugs simultaneously. The future aim is to handle many more, preferably hundreds. The method is iterative search for anti-cancer drug combinations. The procedure starts by generating an initial generation (population) of drug combinations randomly or guided by biological prior knowledge and assumptions. In each iteration the aim is to propose a new generation of drug combinations based on the results obtained so far. The procedure iterates through a number of generations until a stop criterion for a predefined fitness function is satisfied.

There are a few such laboratories in the world with this type of lab robot, but researchers “have only used the systems to look for combinations that kill the cancer cells, not taking the side effects into account,” says Gustafsson.

The next step: Make the robot system more automated and smarter. The scientists also want to build more knowledge into the guiding algorithm of the robot, such as prior knowledge about drug targets and disease pathways.

For patients with the same cancer type returning multiple times, sometimes the cancer cells develop resistance against the pharmacotherapy used. The new robot systems may also become important in the efforts to find new drug compounds that make these resistant cells sensitive again.

The research is described in an open-access article published Tuesday (Sept. 22, 2015) in Scientific Reports.

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