Decagon (the system of search of ghost effects in drugs)

2018: Start of a system

On July 10, 2018 scientists of Stanford University provided a system on the basis of artificial intelligence for forecasting of potential ghost effects of medicinal combinations. This system called by Decagon should help doctors and researchers to look for the best combinations of drugs for treatment of many diseases.

Though ghost effects of medicines are well-known, their combinations are usually poorly studied as the research of a set of medicines is at the same time simply inexpedient. However many patients (in the USA up to 11.9%) accept 5 and more medicines a day. Such polipragmaziya authentically worsens shared state of patients and is connected with high risk of unforeseen collateral reactions.

An AI system for identification of ghost effects of medicines is released

Researchers of Stanford University found a method to solve this problem, having studied as medicines influence metabolism. They developed the massive algorithm describing interaction of more than 19 thousand proteins of the person with each other with the participation of different medicines. Using more than 4 million known associations between medicines and ghost effects, the command using AI revealed patterns of emergence of ghost effects how medicines influence different proteins.

It is noted that several pharmaceutical companies began to use Decagon for identification of ghost effects, but only for combinations from two medicines. It is in the future going to finish a system that it could support more complex circuits. Researchers also hope to create more user-friendly interface of the program which can be used in clinical practice. For now the technology is tested in practice and prepares for mass implementation in programs of clinical trials within which complex medicinal circuits are developed and studied.^[1]

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