From biological potency absorbed components to artificial intelligence mining: a review of analytical strategies for the discovery and validation of quality marker in traditional Chinese medicine in the past decade

Abstract

Quality control of Traditional Chinese Medicine (TCM) is fundamental to ensuring its clinical efficacy, with TCM formulas being the primary form used in clinical practice. Current quality control methods for TCM formulas often rely on pharmacopoeial standards for individual medicinal materials, typically encompassing only characteristic or partial active ingredients. These methods fail to fully reflect the clinical efficacy of TCM formulas. Consequently, exploring the multiple efficacious components in TCM formulas and establishing the correlation between multi-component content and efficacy has become an urgent issue in the modern quality assessment of TCM formulas. The quality marker (Q-marker) has emerged as a crucial standard in this field, achieving notable success in recent years. This paper reviews recent progress in the development of the Q-marker system in TCM by highlighting strategies based on the correlation between efficacy and constituents, using analytical techniques to investigate the material basis and efficacy of TCM. However, the aforementioned methods inevitably involve human selection factors. With the widespread application of artificial intelligence (AI) learning algorithms, it is now possible to develop a modern quality evaluation method for the multi-component “efficacy-quality” correlation in TCM formulas. This approach leverages AI techniques to explore novel and quantifiable methods for scientific and rational quality control in TCM formulas. In this paper, important future directions and questions in this field are also discussed.