The use of CURATE.AI, an artificial intelligence (AI) program that assists physicians in determining suitable and customized chemotherapy doses for patients, has produced positive outcomes, according to the National University of Singapore (NUS). Clinical staff from the National University Cancer Institute, Singapore (NCIS), a unit of the National University Health System, are involved in the study (NUHS).
The objective of CURATE.AI is to potentially identify more treatment responders and determine the appropriate doses for patients to maximize efficacy and lengthen the period during which a patient is receptive to treatment. For some patients, these doses can be less than the previously prescribed high levels. Dr. Dean Ho, the head of the NUS Department of Biomedical Engineering and a co-corresponding author of the study, said, “We hope to help doctors quickly identify the optimal doses that are customized for each patient at different stages of the treatment cycle using CURATE.AI, which is efficacy-driven.
The objective, according to Dr. Ho, is to enhance both patient and treatment outcomes. On the basis of the patient’s characteristics, chemotherapy is typically given in predetermined doses. However, these toxicity-guided doses might not produce the best possible therapeutic response.
The CURATE.AI was developed by Dr. Ho and his colleagues. He described the platform as an optimization software that combines clinical data from patients, such as medication kind, dose, and cancer biomarkers, to produce a personalized digital profile that can be used to adjust the appropriate dose throughout chemotherapy treatment. An essential component of using AI in medicine is having clinicians participate directly in the creation of customized datasets. The pilot trial is a positive first step in integrating CURATE.AI into the clinical workflow of dynamic dosage selection in the treatment of solid tumors.
The main objective of CURATE.
AI will make it possible for patients to receive completely individualized dosing, while also enabling physicians to choose the right dose for each patient without adding to their workload. Clinicians are able to spend more time with the patient and caregiver as a result.
Additionally, CURATE. AI calibrates medication dosage based on each patient’s clinical data. Different pharmacological doses are administered to each patient, and their responses are tracked. To generate a digital patient profile, this information is integrated with clinical information. By connecting medication dose to efficacy and safety, it optimizes treatment outcomes for each digital profile. Throughout treatment, the dose could alter.
During the pilot experiment, which took place at the National University Hospital from August 2020 to April 2022, clinicians were free to accept or reject CURATE.AI dose recommendations depending on their clinical judgment. A prospective and interventional study that uses an AI-based strategy for human treatment was presented at the 2022 American Society of Clinical Oncology (ASCO) Annual Meeting with the findings of the pilot experiment. The meeting will include presentations on the most recent developments in cancer research. ASCO is a major professional organisation for those who care for cancer patients.
The study also found that patients adhered to recommended doses at rates of between 80% and 100% when they received the recommended dosages on time. These early results are promising for the downstream application of CURATE. utilizing artificial intelligence in medicine.
The NUS team will proceed with a more extensive, randomized experiment after taking this first step toward integrating CURATE.AI into clinical workflows for dose selection in solid tumor treatment to further confirm the platform’s performance. Clinical trials involving individuals with multiple myeloma, another kind of cancer, as well as illnesses including hypertension will also be carried out by the study team. A trial to optimize the dose of personalized immunotherapy for solid malignancies will soon start, which is noteworthy.
