Sign up for Englemed updates from TwitterSign up for Englemed updates from Facebook
Contact Englemed
Our contact email address.
We can provide a specialist, tailored health and medical news service for your site.
Click here for more information
RSS graphic XML Graphic Add to Google
About Englemed news services - services and policies.
Englemed News Blog - Ten years and counting.
Diary of a reluctant allergy sufferer - How the British National Health Service deals with allergy.
BookshopFor books on women's health, healthy eating ideas, mental health issues, diabetes, etc click here

WWW Englemed
Copyright Notice. All reports, text and layout copyright Englemed Ltd, 52 Perry Avenue, Birmingham UK B42 2NE. Co Registered in England No 7053778 Some photos copyright Englemed Ltd, others may be used with permission of copyright owners.
Disclaimer: Englemed is a news service and does not provide health advice. Advice should be taken from a medical professional or appropriate health professional about any course of treatment or therapy.
New insights into COVID-19 infectiousness
Fri August 19th - British researchers have unveiled the first real-world study to estimate how long people are infectious with mild COVID-19. More
Gene variant that protects against heart disease
Fri August 19th - A gene variant has been identified that helps to protect against heart diseases. More
On 09/10/2020 William Haworth wrote:
How long is recovery time after proceedure... on Ablation cuts atrial fibrillat...
On 08/02/2018 David Kelly wrote:
Would you like to write a piece about this to be i... on Researchers unveil new pain re...
On 23/10/2017 Cristina Pereira wrote: on HIV breakthrough - MRC...
On 12/09/2017 Aparna srikantam wrote:
Brilliant finding! indeed a break through in under... on Leprosy research breakthrough...
On 01/07/2017 Annetta wrote:
I have been diagnosed with COPD for over 12 years.... on Seaweed plan for antimicrobial...

Test predicts effective cancer drug combinations in 48 hours

Tuesday April 5th 2022

A prototype artificial intelligence test has been developed that can predict in 48 hours which drug combinations are likely to work for cancer patients, British scientists have announced.

Scientists at The Institute of Cancer Research, London used AI to analyse large-scale protein data from tumour samples, which predicted patients’ response to drugs more accurately than is currently possible.

They tested the new technique on individual cancer cells in the lab and tumour cells freshly isolated from lung fluid in people with non-small cell lung cancer.

Their study, published in the latest edition of Molecular Cancer Therapeutics, involved carrying out proteomic analyses in 52 important proteins before training machine learning algorithms to define the key protein changes that predict drug responses.

The algorithm was first used to predict how sensitive cells were to individual cancer drugs and it was found the technique could predict individual drug responses more accurately than genetic features, such as mutations in key genes EGFR, KRAS and PIK3CA, which are three genetic markers used in the clinic to predict drug responses in lung cancer.

The research team went on to predict sensitivity to drug combinations, using 21 different two-drug combinations in lung cancer cells with different gene faults, such as mutations in EGFR and KRAS.

Out of the 252 total drug combinations, 128 showed some level of synergy. Of these, the AI test correctly identified the top five ranked combinations 57% of the time and the top 10 ranked combinations 83% of the time.

The test successfully previously promising combinations, such as combining trametinib and capivasertib, or gefitinib and everolimus, in non-small cell lung cancer cell lines with EGFR mutations.

Possible new combinations were also identified, such as vemurafenib and capivasertib, which could potentially be effective for non-small cell lung cancer cell lines with no mutations in EGFR or KRAS.

The new study establishes proof of concept but the test will need further validation and researchers are already planning a larger follow-up study to test 15 drugs and to examine 12,000 proteins involved in signal transduction.

Study leader Professor Udai Banerji, professor of molecular cancer pharmacology at The Institute of Cancer Research, London, and consultant medical oncologist at The Royal Marsden NHS Foundation Trust, said the test has the potential to guide doctors in their judgments on which treatments are most likely to benefit individual cancer patients.

“It is an important step to move forward from our current focus on using genetic mutations to predict response,” said Prof Banerji.

“Our findings show that our innovative approach is feasible and makes more accurate predictions than genetic analysis for patients with non-small cell lung cancer. Before this test can enter the clinic and guide personalised treatment, we will need to further validate our findings – for example, by carrying out a study where we run the test in patients already getting a treatment to check if the predictions are correct.”

The study was funded by the National Institute for Health Research (NIHR), Wellcome, Cancer Research UK and by The Institute of Cancer Research (ICR).

Professor Kristian Helin, chief executive of The ICR, said: “This new study is a great example of interdisciplinary collaboration, in integrating our understanding of cancer biology, AI and clinical medicine to provide proof of concept for a new test that can predict which combination treatments are most likely to work for patients.

“It demonstrates the potential power of AI and protein analysis to personalise treatment and could be an important step in helping us tackle drug resistance – hopefully helping us offer patients smarter, more personalised treatment options.”

Molecular Cancer Therapeutics 4 April 2022

Tags: Cancer | Pharmaceuticals | UK News

Printer friendly page Printer friendly page

Comment on this article:

<a>,<b> & <p> tags allowed
Please enter the letters displayed:
(not case sensitive)