Rare diseases affect less than 1 in 2,000 people. However, with more than 7,000 different types identified, their global impact is huge. In the Asia-Pacific region, approximately 258 million people suffer from rare diseases, the highest number in the world, with more than 45 million people in Southeast Asia alone. This large number highlights major treatment challenges, as the diversity of patient populations leads to huge health care disparities and increases the challenge of clinical trial recruitment.
In addition, in small patient groups, each patient is different, and the condition of individual patients changes over time. This highlights the urgent need for accessible and personalized treatments for this patient group, while also highlighting the profound challenges faced in developing treatments for patients with rare diseases.
To meet the need for effective treatment of rare diseases without using large amounts of population data, researchers at the Institute of Digital Medicine (WisDM) at NUS Medicine at the National University of Singapore used a small amount of data from the following institutions: guiding the treatment of a patient with a rare disease and achieving promising results.
Under the co-leadership of Professor Dean Ho, Director of WisDM at the National University of Singapore School of Medicine, the team used an artificial intelligence (AI) derivative platform, CURATE.AI.
Unlike traditional artificial intelligence models that rely on large data sets, CURATE.AI uses small data to dynamically adjust treatment doses based on individual patient responses. Since the trial began in October 2021, a significant improvement in the patient’s red blood cell levels has been observed and the patient was able to avoid blood transfusions. It is important that patients do not suffer serious side effects as a result of treatment and that the number of hospitalizations is reduced.
In the trial, the research team worked with clinicians at the National University of Singapore Cancer Institute (NCIS) to determine the patient’s drug dose based on guidance from the CURATE.AI platform. Drug doses are selected prospectively based on patients ‘own responses, making this treatment strategy the first of its kind.
Compared to the total dose under standard treatment regimens, the recommended drug dose for this trial was low and well tolerated by patients, demonstrating durable disease control. As a result, patients saved approximately US$8,000 (approximately S$10,500) in drug costs during the first two years of treatment.
Treatment trials recommended by CURATE-AI are ongoing and are now open to recruit new suitable patients. Results collected during the first two years of the trial were published in the journal npj Digital Medicine.
Professor He said: “No two patients are the same, and even the same patient will change over time. It is crucial that treatment develops with the patient. Our research highlights the effectiveness of using small data to treat extremely rare diseases-the approach to CURATE.AI uses small data sets to customize treatments, making up for the shortcomings of traditional big data methods and the inability to conduct large-scale trials due to limited patient populations, providing practical solutions for urgent and challenging development needs. Personalized strategies for rare diseases.”
Professor Ho is also the Chairman of the Department of Biomedical Engineering, School of Design and Engineering, National University of Singapore, and the Director of the N.1 Institute of Health, National University of Singapore.
Dr. Sanjay de Mel, senior consultant in the Department of Hematology and Oncology at NCIS and clinical leader of the trial, added: “When treating patients with Waldenberg’s macroglobulinemia, it is crucial to achieve a good treatment response while minimizing side effects. Therefore, there may be significant differences in the way patients ‘bodies handle treatment and the types of side effects experienced, so a personalized drug dosing approach is needed to address this individual difference.”
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Original text:https://medicalxpress.com/news/2024-09-ai-platform-results-effectively-patient.html
More information: Agata Blasiak et al., Personalized dose selection for the first patient with Fahrenheit’s macroglobulinemia in the PRECISE CURATE.AI trial, npj Digital Medicine (2024). DOI：10.1038/s41746-024-01195-5
Journal information: npj Digital Medicine
Provided by National University of Singapore
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