Researchers in Singapore have developed an artificial intelligence (AI) platform that could enable doctors to prescribe personalised treatments for cancer patients.
The technology platform is designed to improve the way drug combinations are put together, allowing doctors to determine the most effective drug combination for each patient more quickly.
Applying the platform towards drug-resistant multiple myeloma, a type of blood cancer, the researchers were able to establish new effective drug combinations, as well as identify the patients who may be more responsive to these treatments, in under a week, the National University of Singapore reports.
The Quadratic Phenotypic Optimisation Platform (QPOP) was developed by a multidisciplinary team comprising clinicians, engineers and molecular biologists. Using a small sample of blood or bone marrow from patients, it maps the drug response that a set of drug combinations will have on the specific patient’s cancer cells.
From 114 approved drugs, QPOP was able to identify a series of effective drug combinations, including a completely novel and unexpected combination that outperformed the standard of care regimen for relapsed myeloma. The platform was also used to fine-tune dosage ratios of the novel combination for optimal effectiveness.
While the novel combination was not the most effective treatment for all patient samples, QPOP was able to match the best drug combination to each patient — demonstrating proof-of-concept for personalised medicine.
Study leader Dr Edward Kai-Hua Chow, principal investigator at the Cancer Science Institute of Singapore, part of the National University of Singapore, said: “QPOP revolutionises the way in which drug combinations are designed and represents a key area in healthcare that can be transformed with AI.”
The findings have been published in the journal Science Translational Medicine.