Schizophrenia is a brain disorder that involves a disturbance of thinking and perception. In the total global burden of disease, such mental illness accounts for over 13%, which is even higher than vascular diseases and cancer, ranking first in the global disease burden. According to statistics from the Health Insurance Administration, Ministry of Health and Welfare in 2019, the number of patients with schizophrenia in Taiwan was as high as 106,000, and the average cost of medical treatment per person was as high as 108,500 NT dollars, causing heavy pressure and financial burdens on patients’ families.
Patients with schizophrenia generally have positive, negative, and cognitive symptoms. Nowadays, positive symptoms can already be treated with corresponding available drugs. However, negative and cognitive symptoms have yet to be properly treated. After years of research, Professor Zeng Yufeng and her team found that in the brain of schizophrenia patients, the activity of D-amino acid oxidase (DAO) significantly increases, making the function of N-methyl-D-aspartate (NMDA) receptor low. As a result, Professor Zeng led the team to use artificial intelligence to simulate the structure of NMDA receptors. Moreover, the team used big data and machine learning to search and compare street drugs, improve the shortcomings of traditional drugs, and develop a series of DAO inhibitors (DAOIs) small molecule compounds. Among them, the drug numbered RS-D7 can effectively enhance the function of NMDA receptors and improve animal behavior patterns in both cell tests and animal tests. In a clinical trial of 24 patients with schizophrenia, the symptoms of the patients were significantly improved within four weeks, confirming that the drug could alleviate the negative and cognitive symptoms of the patients by 100%.
The clinical usage of RS-D7 is safe. It is a small molecule compound that can be constantly used alone or in combination with other psychiatric drugs. If the new drug developed can be launched as scheduled in the future, it will benefit many patients suffering from schizophrenia and their families, improve the quality and efficacy of mental illness medical care, and reduce huge social costs.
思覺失調症患者普遍會出現正性、負性與認知功能失調等症狀，其中正性症狀已有對應的市售藥物能加以治療。然而，負性症狀和認知功能失調至今卻仍沒有合適的治療藥物。通過多年的研究，曾宇鳳教授及其團隊發現在思覺失調症患者的腦部中，其胺基酸氧化酶 (DAO) 的表現量及活性會明顯增加，使得N-甲基-D-天冬胺酸 (NMDA) 的受體功能低下。因此，曾教授帶領團隊，使用AI技術模擬NMDA受體結構，再以AI大數據與機器學習的方式搜尋比對市售藥物，改良傳統藥物的缺點，開發並合成一系列的DAO抑制劑 (DAOIs) 小分子化合物。在此之中，編號RS-D7的藥物在細胞試驗及動物試驗中，皆可以有效提升NMDA受體功能並改善動物行為模式。在24位思覺失調症病患的的臨床試驗中，患者在4週內症狀顯著改善，證實此藥物能100%緩解病患的負性症狀與認知功能失調。