New mode of data-intelligence fusion research on clinical “toxic” Chinese medicines: The proposal of evidence-based Chinese medicine toxicology

Abstract

<p indent="0mm">The safety issues of Chinese medicine have always been regarded as a vital issue, which has been restricting the development of the Chinese medicine industry and has long had implications for public health. This is especially true for the clinical drug application of “toxic” Chinese medicines which are generally acknowledged as being a fairly complicated and hazard-prone area. These distinguishing features of “toxic” Chinese medicines noted above have limited the safe and rational clinical drug application of traditional Chinese medicine. However, previous research approaches have been subject to many limitations such as insufficient integration of basic research with clinical research, the lack of leadership and guidance for the system view and overall view. These trends of current academic studies show that there are plenty of serious difficulties in transforming the research data into effective evidence, to support the present demand for the rational clinical drug application for “toxic” Chinese medicines. In the wake of the inclusion of data as one of the elements in the scope of market-oriented reform, the scientific and technological innovation in the area of big data has occasioned the birth of data science. This will generate new opportunities for the development of the traditional Chinese medicine industry. Our team is in the early stages of developing a methodological system for traditional Chinese medicine evidence-based research which is based on the “four syndromes”, with characteristics of “syndrome production-syndrome differentiation-syndrome and application-syndrome verification”. This paper is guided by traditional Chinese medicine theory, drawing on the experience from the concept of evidence-based medicine, and introducing multidisciplinary and interdisciplinary technologies, such as digital twins, and artificial intelligence. Based on these parameters, our team further proposes the research concept of evidence-based Chinese medicine toxicology, and plans to build up one new mode of data-intelligence fusion research on clinical “toxic” Chinese medicines. To be specific, multi-disciplinary research methods will be applied, such as conventional toxicology, translational toxicology, toxicological genomics and clinical medicine. The research data of “toxic” Chinese medicines will subsequently be analyzed, which could include studies on clinical characteristics, toxic substance basis, toxicokinetics, toxic molecular mechanisms and toxicity-effect conversion regulation. Further, the integrative transformation between data and evidence will be carried out with the help of artificial intelligence, a disease-syndrome digital twin modeling system and other evidence-based toxicological technologies. Thus, the evaluation and prediction method using multiple and integrated evidence for “toxic” Chinese medicines will be set up, and then, the research method and technical path of evidence-based Chinese medicine toxicology will be refined, by being built around the core of data-intelligence fusion. In conclusion, this article designates data as the foundation and intelligence as the navigation, to provide new ideas and a reference base for the safety research into Chinese medicine.