Drug-induced liver injury (DILI) is one of the leading causes of the termination of drug development programs. Consequently, identifying the risk of DILI in humans for drug candidates during the early stages of the development process would greatly reduce the drug attrition rate in the pharmaceutical industry but would require the implementation of new research and development strategies. In this regard, several in silico models have been proposed as alternative means in prioritizing drug candidates. Because the accuracy and utility of a predictive model rests largely on how to annotate the potential of a drug to cause DILI in a reliable and consistent way, the Food and Drug Administration-approved drug labeling was given prominence. Out of 387 drugs annotated, 197 drugs were used to develop a quantitative structure-activity relationship (QSAR) model and the model was subsequently challenged by the left of drugs serving as an external validation set with an overall prediction accuracy of 68.9%. The performance of the model was further assessed by the use of 2 additional independent validation sets, and the 3 validation data sets have a total of 483 unique drugs. We observed that the QSAR model's performance varied for drugs with different therapeutic uses; however, it achieved a better estimated accuracy (73.6%) as well as negative predictive value (77.0%) when focusing only on these therapeutic categories with high prediction confidence. Thus, the model's applicability domain was defined. Taken collectively, the developed QSAR model has the potential utility to prioritize compound's risk for DILI in humans, particularly for the high-confidence therapeutic subgroups like analgesics, antibacterial agents, and antihistamines.

Coal fly ash (CFA) provides important resources of gallium, which is regarded as an irreplaceable material in many technologies. A prospective roasting reagent assisted acid leaching process was proposed for the purpose of extracting gallium. The extraction efficiency of gallium by NaF (sodium fluoride) roasting followed by HNO3 (nitric acid) leaching process was demonstrated. The effect of roasting temperature, roasting time, the NaF-CFA mass ratio, acid leaching temperature, acid leaching time, and acid concentration were investigated. The results revealed that under optimal conditions (roasting temperature of 800 °C, roasting time of 10 min, acid leaching in 2 mol/L HNO3 for 1 h, and the NaF-CFA mass ratio of 0.75:1), 94% of gallium was extracted. Compared to previous studies, the process is a cost-effective method which can greatly shorten reaction time. It can reduce environmental pollution as it requires fewer acid reagents with low concentration and additives. It is expected to provide a method for the extraction of gallium from CFA.

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