AI Test Pinpoints More Cancers Targeted by Astra, Glaxo Drugs

Advertisement
By John Lauerman, Bloomberg | Updated: 16 April 2019 14:04 IST

Using artificial intelligence to pinpoint tumour cells with reduced ability to repair their own DNA can help identify tens of thousands of patients who would benefit from treatment with drugs from AstraZeneca and GlaxoSmithKline, researchers said.

Analysing genetic tests with a machine-learning algorithm helps target cancers that are vulnerable to treatment with drugs called PARP inhibitors, according to a study from scientists at Harvard Medical School in Boston and the UK's University of Cambridge.

Advertisement

Oncology is among the fastest-growing fields in the pharmaceutical industry, with an armada of newly developed treatments sending annual sales surging to about $133 billion. Doctors and scientists are searching for more hints of how to deploy the costly drugs that sometimes shrink tumours in just a fraction of patients.

Oncologists often determine whether patients will receive PARP inhibitors like Astra's Lynparza or Glaxo's Zejula by testing for flaws in certain gene mutations that block cells from fixing their own DNA using a specific mechanism. Yet many tumours without those mutations may also have the same genetic repair deficit, but are harder to find because there's no specific gene test.

Advertisement

The algorithm finds patterns in tumours that show whether they have a deficiency in homologous DNA repair, which makes them susceptible to treatment by PARP inhibitors, researchers led by Harvard research fellow Doga Gulhan said Monday in the journal Nature Genetics. The technique can be applied to genetic tests that are already performed on many tumours, the researchers said.

Of 270,000 breast cancers diagnosed in 2018, about 13,500 to 27,000 were attributed to so-called BRCA mutations, and thus could be targeted with PARP inhibitors, the researchers said. Using computer simulation analysis, they identified as many as 54,000 more with normal BRCA genes that had defects in homologous repair, and might be treated with the new cancer drugs.

Advertisement

Analysts estimate Lynparza sales of $1.1 billion this year, and Zejula sales of $314 million. Clovis Oncology Inc.'s Rubraca, another PARP inhibitor, is estimated to sell $147 million.

© 2019 Bloomberg LP

 

Get your daily dose of tech news, reviews, and insights, in under 80 characters on Gadgets 360 Turbo. Connect with fellow tech lovers on our Forum. Follow us on X, Facebook, WhatsApp, Threads and Google News for instant updates. Catch all the action on our YouTube channel.

Further reading: Cancer
Advertisement

Related Stories

Popular Mobile Brands
  1. Here's When the Motorola Razr Fold, Lenovo Legion Y70 Will Launch in China
  2. Best Premium Laser Printers Available in India
  3. Motorola Razr Fold Pre-Order Listing Reveal Launch Date, Pricing, Offers
  4. YouTuber Demonstrates Flaw That Allows Money to Be Stolen From Locked iPhone
  5. Best Mobiles Under Rs. 40,000 in India
  6. YouTube Finally Lets You Turn Off Shorts From Your Feed With This Setting
  1. OnePlus Nord CE 6 Lite Appears on Geekbench With Dimensity 7400 Chip, Android 16
  2. Meta’s Planned Facial Recognition Feature for Smart Glasses Faces Opposition From Privacy Orgs
  3. Vivo X300 Ultra Pricing Surfaces Online via Retail Listing in Europe
  4. YouTube's New Option Lets Users Effectively Turn Off Shorts From Their Feed
  5. South Korea Plans Blockchain-Based Payments for Government Spending
  6. Amazon Launches AI Store to Help Users Discover and Shop AI-Powered Devices
  7. Motorola Razr Fold, Lenovo Legion Y70 to Launch Alongside Y900 Tablet During Lenovo's May 19 Event
  8. Apple Tap-to-Pay Vulnerability Demonstrated on Video as YouTuber Steals $10,000 From a Locked iPhone
  9. Adobe’s New Firefly AI Assistant Can Perform Complex Design Tasks With Text Prompts
  10. Crimson Desert Has Sold Over 5 Million Copies, Pearl Abyss Confirms
Download Our Apps
Available in Hindi
© Copyright Red Pixels Ventures Limited 2026. All rights reserved.