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SINGAPORE – A group of researchers in Singapore will leverage its artificial intelligence (AI) platform to evaluate 12 locally available drugs for a combination of drugs that can be used to treat Covid-19.
The interactive digital platform, known as IDentif.AI, takes advantage of artificial intelligence to calculate the most effective combination of drugs, along with their respective doses, from more than 530,000 possibilities.
Researchers, from the Institute of Digital Medicine (WisDM) at the National University of Singapore (NUS) Yong Loo Lin School of Medicine, found in an April study that the most optimal drug combination comprises remdesivir, lopinavir and ritonavir. which are used to treat patients with the human immunodeficiency virus (HIV).
Their findings were validated using live virus in cell culture, and it was preemptively approved for a clinical trial in Taiwan, should the need arise.
Professor Dean Ho, director of WisDM, told The Straits Times on Friday (October 16) that “the combination allowed for almost complete inhibition of the virus, but that remdesivir is not available, which is a challenge that we will address to continuing studies “.
Instead, the research team will evaluate a suite of 12 locally accessible drugs, ranging from antivirals to targeted therapies and other agents.
Remdesivir, which is among the few authorized treatments for Covid-19 so far, inhibited the virus by 15 percent as initially validated by IDentif.AI, thus being used as a benchmark for the new set of combinations. of drugs, Professor Ho said.
A clinical trial conducted by the World Health Organization on Thursday (October 15) found that remdesivir had little or no effect on the length of hospital stay or the chances of survival of patients with Covid-19, although the results of the trial have not yet been reviewed.
“Additionally, remdesivir must be administered in hospitals via intravenous infusion, which could make it difficult to implement if there are many Covid-19 patients in the community. Therefore, we are looking to investigate the drugs available in tablet form for that can be consumed orally, “said Professor Ho.
This also makes it easier to dispense and can potentially be administered at home, he added.
The study will be conducted on the new set of drug combinations in November.
In addition to using AI to optimize drug mix for infectious diseases such as Covid-19, the researchers were also able to leverage their technology to offer personalized treatments for cancer patients.
Using another platform known as Curate.AI, the doses of medications administered to patients can be modulated to produce optimal results throughout the duration of care.
Assistant Professor Raghav Sundar, NUS Department of Medicine and WisDM and consultant to the Department of Hematology-Oncology, National Cancer Institute at the National University of Singapore, said: “Dosing of drugs in cancer treatments is based on typically on the degree of side effects by the patient. With Curate.AI, each patient’s recommended dose is calibrated using clinical data generated from their individual response to treatment. “
For example, in a pilot clinical study conducted in collaboration with a US hospital, a patient with advanced prostate cancer was recommended a 50% reduction in the dose of an investigational inhibitor drug to increase efficacy. The patient was able to resume an active lifestyle as the lower dose was found to be more tolerable.
Similarly, a patient in Singapore who had advanced cancer was prescribed a reduced dose of nab-paclitaxel, a type of chemotherapy drug, which succeeded in halting the progression of the cancer and shrinking the size of his lung tumor. This allowed the patient to continue treatment for much longer compared to other patients who received the same drug.
These findings have led to a pilot clinical trial that is currently recruiting patients.
In another expanded study using Curate.AI, the team leveraged software known as the Multi-Attribute Task Battery, which comes in the form of a game with different intensity levels.
It will be tested in patients who have received radiation therapy for brain cancer to provide diagnostic information about individual patient responses, which can be used to personalize treatment.
The software could also be used as therapy for patients facing impaired cognitive and physical abilities, such as diabetes, cognitive decline, and Alzheimer’s disease.
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