Scientists have achieved significant progress in overcoming a major barrier to tapping the potential of Traditional Chinese Medicine [TCM] and India’s Ayurvedic medicine for the development of new and more effective modern drugs. Their report appears in ACS’ Journal of Chemical Information and Modeling.
Andreas Bender and colleagues note that TCM medicines have been clinically tested as effective medicines. In the world’s largest international clinical trial, for instance, scientists concluded that Artesunate, a derivative of the Chinese herb qinghao, should replace quinine as a treatment for severe malaria in both adults and children worldwide. Traditional medicines for over thousands of years have benefited human health. However, knowledge about how these medicines work in the body is missing. Since their ‘mode of action’ [MOA] is not clear, it limits their use. Information about a drug’s MOA is important for better understanding of both; the beneficial effects and side effects.
The team describes an algorithm that can help explain how these substances work in the body. This algorithm can help understand the MOA of traditional anti-inflammatory medicines. The algorithm is a step-by-step process to analyse data, which the scientists applied to predict how the active chemical ingredients in traditional medicines affect biological processes. By establishing the MOA of these compounds, the gap between the Western and traditional medicine can be reduced, the report concluded. Examples in the report include anti-cancer medicines in Ayurveda and ‘replenishing’ medicines from TCM.