IIT-M technology to play "Pivot"al role in delivering individualized care to cancer patients

Safalta Expert Published by: Aryan Rana Updated Mon, 11 Jul 2022 11:22 PM IST

Highlights

An AI-based tool will help clinicians develop individualized treatment plans for patients. The "Pivot" is based on a machine learning model that divides genes into cancer-causing oncogenes, cancer-preventive tumour suppressors, and neutral genes.

Researchers at IIT Madras have created a ground-breaking technique that may pinpoint a person's cancer-causing genes. The "Pivot," an AI-based tool, will assist clinicians in developing individualized treatment plans for patients based on patient DNA profiles. The tool is based on a machine learning model that divides genes into cancer-causing oncogenes, cancer-preventive tumour suppressors, and neutral genes.  If you are preparing for competitive exams and looking for expert guidance, you can download our General Knowledge Free Ebook Download Now.

Source: Safalta.com



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Major Points:

  • The model will analyze data such as the frequency with which a gene mutates, its properties, the kinds of mutations, and the number of detrimental mutations in order to find the gene that causes cancer in a person or, more specifically, to identify rare genes that cause cancer.
  • It is well knowledge that current cancer treatments will have a negative impact on the patient's general health.
  • According to the research team, selecting the drug and therapy regimen that will have the greatest positive influence on a patient's prognosis can be made easier by identifying the genes responsible for the growth and spread of cancer in patients.
  • In order to assess how frequently the gene has mutated, samples from various patients are traditionally analyzed in order to track down a cancer-causing gene.
  • If the IIT-M scientists had benefited greatly from publicly accessible cancer genome data from websites like ICGS, then additional Indian cancer genome data—which is still absent on a local platform—is required for the tool to be used effectively.

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The majority of the genetic data used to feed the model comes from The Cancer Genome Atlas Program and The International Cancer Genome Consortium (ICGC) (TCGA).

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