MRTCM: A comprehensive dataset for probabilistic risk assessment of metals and metalloids in traditional Chinese medicine

Traditional Chinese medicine (TCM) is still considered a global complementary or alternative medical system, but exogenous hazardous contaminants remain in TCM even after decocting. Besides, it is time-consuming to conduct a risk assessment of trace elements in TCMs with a non-automatic approach due to the wide variety of TCMs. Here, we present MRTCM, a cloud-computing infrastructure for automating the probabilistic risk assessment of metals and metalloids in TCM. MRTCM includes a consumption database and a pollutant database involving forty million rows of consumption data and fourteen types of TCM potentially toxic elements concentrations. The algorithm of probabilistic risk assessment was also packaged in MRTCM to assess the risks of eight elements with Monte Carlo simulation. The results demonstrated that 96.64% and 99.46% had no noncarcinogenic risk (hazard indices (HI) were < 1.0) for animal and herbal medicines consumers, respectively. After twenty years of exposure, less than 1% of the total carcinogenic risk (CRt) was > 10-4 for TCM consumers, indicating that they are at potential risk for carcinogenicity. Sensitivity analysis revealed that annual consumption and concentration were the main variables affecting the assessment results. Ultimately, a priority management list of TCMs was also generated, indicating that more attention should be paid to the noncarcinogenic risks of As, Mn, and Hg and the carcinogenic risks of As and Cr in Pheretima and Cr in Arcae Conch. In general, MRTCM could significantly enhance the efficiency of risk assessment in TCM and provide reasonable guidance for policymakers to optimize risk management.