New AI Technology Helps Match Tumors To The Best Known Drugs Combo

New AI Technology Helps Match Tumors To The Best Known Drugs Combo

Published: 25-Nov-2020 | Published By: Market Research Store

It has been found that approximately 4% of the cancer therapeutic drugs that are under development earn approval by the U.S. Food and Drug Administration (FDA). The current issue is the combination of certain drugs for the patients in a smart way. According to ProfessorTrey Ideker from University of California San Diego School of Medicine and Moores Cancer Center, for cancer predicting which drug will be effective, unique, and attack the complex core workings of a tumor tissue is almost impossible. Thus, the team has developed DrugCell, which is a new artificial intelligence (AI) system which is designed to help match the tumors to the appropriate drug combinations that is likely to make sense to humans.

The AI systems are usually referred to as 'black boxes' as they are only predictive and their efficiency is still doubtful. The AI systems are trained to get hold of images that are exact copy of the real-time images. Thus, for making the use of AI in healthcare to the fullest it is important to understand the functionality and the outcomes of the black box. The correct information about the right pathway, recommended drugs, and positive drug response or its rejection will help develop new effective drugs to fight off cancer. The Dcell is the previous version of DrugCell that used yeast cell's genes and mutations to predict cellular behaviors. However, the next generation DrugCell is so well trained using 1,200 tumor cell linesreaction to 700 FDA-approved or experimental therapeutic drugs such that almost 500,000 cell line/drug pairings could be obtained.

Using this new AI system and the input data about a tumor,the best approved drug, the biological pathways that control reaction to that drug, and groupings of drugs to appropriately cure the malignancy is possible. The precision cancer therapy assessed by the Molecular Tumor Board help recommend treatment based on the patient's distinctive genomic alterations and other data. The results obtained from DrugCell’s ability to translate the laboratory cell lines information are quite extraordinary, thereby turning it into a diagnostic tool.

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