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Scientists' Robotically Driven System Could Reduce Cost of Discovering Drug and Target Interactions

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This image shows distinct drug effects identified by the computer and organized to display similarities.

Researchers at Carnegie Mellon University researchers said they have created the first robotically driven experimentation system to determine the effects of a large number of drugs on many proteins.

Credit: Carnegie Mellon University

Carnegie Mellon University researchers say they have created the first robotically-driven experimentation system to determine the effects of drugs on many proteins.

They say the initiative has led to a reduction in the number of necessary experiments by 70 percent.

The model enables a computer to select which experiments to do, and the experiments are then carried out using liquid-handling robots and an automated microscope.

The machine-learning algorithm studied the possible interactions between 96 drugs and 96 cultured mammalian cell clones with different, fluorescently tagged proteins. A total of 9,216 experiments were possible, each consisting of acquiring images for a given cell clone in the presence of a given drug. The challenge for the algorithm was to learn how proteins were affected in each of the experiments, without performing all of them.

The first round of experiments began by collecting images of each clone for one of the drugs, and images were represented by numerical features that captured the protein's location in the cell. The algorithm repeated the process for 30 rounds, completing 2,697 out of the 9,216 possible experiments. As it progressively performed the experiments, it identified more phenotypes and more patterns in how sets of proteins were affected by sets of drugs.

From Carnegie Mellon University
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Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA


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