A new computer tool has been developed to predict how some cancers may respond to an investigational treatment before it has even been administered to a patient.
First reported by FirstWord Pharma, the computer program is capable of predicting how tumors could become resistant to treatment before it would ever become evident in a clinical trial. The computer model was developed at The Institute of Cancer Research. The program, which has been described in a new article published in the journal Cell Chemical Biology, could conceivably allow researchers to begin “working on second-generation drugs to tackle treatment resistance before the first-generation drug is taken to patients,” FirstWord Pharma reported.
Not only that, but the program could also lead to a development of tests that would determine whether or not patients had certain mutations in their cancer that would be resistant to some potential treatments. That determination would allow for the earliest chances of delivering personalized medicines to a patient, FirstWord Pharma said. The computer program was also able to predict which part of a cancer tumor might have multiple mutations that would require multiple treatment options. The computer program “prioritized mutations” in these areas based on the likelihood of their having been formed in the cancer type under investigation, according to the report.
“Our new approach can predict which mutations are likely to arise in response to drug treatment in different types of tumors,” Teresa Kaserer, a scientific officer at the London-based cancer institute told FirstWord Pharma. “This will be hugely beneficial in designing new cancer drugs. Instead of reacting to what we see in the clinic – when it’s too late as patients have stopped responding to treatment – we can use our computational method to predict during the drug design stage how resistance will arise.”
Kaserer told the publication that the success of the computer program means researchers can develop tests that will select patients for particular treatments and better monitor them while they are taking the medication.
“This could be great news for patients, who could be switched to a second generation drug as soon as a resistance mutation appears,” Kaserer said.
As part of the program development, researchers tested the computer model on existing cancer drugs and drug targets. That included 17 different drugs that target cancer-related proteins, such as MAPK1, KIT, EGFR, Abl and ALK, FirstWord Pharma said. The program was able to “accurately predict many of the mutations that doctors see in the clinic” according to the article. For the MAPK protein, the computer was able to predict many that were generated in the lab, FirstWord Pharma added.
A Product Manager with expertise in pharma marketing and sales operations