AI Technique Used to Successfully Treat Metastatic Cancer Patient: Study

Singaporean researchers have harnessed the power of artificial intelligence (AI) to successfully treat a patient with advanced cancer, completely halting disease progression.

The CURATE.AI platform, developed by the National University of Singapore (NUS), halted the progression of advanced cancer by continuously optimising novel drug combination.

In a clinical study, a patient suffering with metastatic castration-resistant prostate cancer (MCRPC) was given a novel drug combination consisting of investigational drug ZEN-3694 and enzalutamide - approved drug for prostate cancer.

The team utilised CURATE.AI to continuously identify the optimal doses of each drug to result in a durable response, allowing the patient to resume a completely normal and active lifestyle.

"Dynamic dosing in cancer therapy is not commonly used. In fact, drug dosing changes in oncology are typically performed only to reduce toxicity," said lead author Dean Ho, Professor at the NUS.

"CURATE.AI uniquely modifies drug dosing to increase efficacy. Our clinical study has shown that dosing can profoundly affect the efficacy and safety of the treatment," Ho added.

A patient's clinical profile changes over time. Patients respond to chemotherapy differently from one another. In fact, many patients do not respond at all to the drug combination because the dosages, which can profoundly impact efficacy, are not suitable for them.

"Therefore, while fixed dose combination therapy represents a standard of care, it may also serve as a barrier to realising truly optimal and personalised medicine," Ho explained, in a paper published in the journal Advanced Therapeutics.

The CURATE.AI platform uses the patient's own clinical data - such as their drug doses and corresponding changes to tumour sizes or levels of cancer biomarkers in the blood - to calibrate his or her unique response to treatment.

This calibration is then used to create an individualised CURATE.AI profile or map, which identifies the drug doses that enable the best possible treatment outcome at any given point in time.