Lumiracoxib

Acyl glucuronide (AG) is a reactive metabolite that causes idiosyncratic drug toxicity (IDT). Although the instability of AG is used to predict the IDT risk of novel drug candidates, it sometimes overestimates the IDT risk. We investigated whether the rate of enzymatic AG hydrolysis in human liver microsomes (HLM) can predict the risk of IDT. We used 16 drugs classified into three categories in terms of IDT risk: drugs withdrawn from the market owing to severe IDT (withdrawn, WDN) and drugs still being on the market, regardless of IDT risk (warning, WA) or not (safe, SA). AG was incubated with HLM, and the resulting parent drugs for AG hydrolysis were quantified using HPLC. The rate of enzymatic AG hydrolysis in the HLM of WDN was higher than that in WA and SA, and no difference was observed between WA and SA. We categorized WA and SA as commercially available (CA) drugs and performed a logistic regression analysis. The rate of enzymatic AG hydrolysis in HLM significantly distinguished WDN drugs from CA drugs, with an estimated classification value of 0.189 nmol/min/mg protein. In conclusion, the rate of enzymatic AG hydrolysis in HLM may be useful for predicting the risk in drug development.

Recent emphasis on the development of safe-and-sustainable-by-design chemicals highlights the need for methods facilitating the early assessment of persistence. Activated sludge experiments have been proposed as a time- and resource-efficient way to predict half-lives in simulation studies. Here, this persistence "read-across" approach was developed to be more broadly and robustly applicable. We evaluated 21 previously used reference plant protection products (PPPs) for their broader applicability in calibrating regression and classification models for predicting half-lives in soil (DT50_OECD307) and water-sediment systems (DT50_OECD308) based on their half-life in sludge and the organic carbon-water partition coefficient K_OC as predictors. The calibrated regression models showed satisfactory predictions of DT50_OECD307 for another 22 test PPPs. Performance was less satisfying for the prediction of DT50_OECD308 for 46 active pharmaceutical ingredients (APIs), suggesting a need for expanding the set of calibration substances and more experimental K_OC values. The classification models mostly correctly classified persistent and non-persistent test compounds for both PPPs and APIs, which is relevant for early-stage screening of persistence. Transformation products of the reference compounds in activated sludge samples were consistent with the reported degradation pathways in soil, particularly with respect to major aerobic, enzyme-catalyzed transformation reactions. Overall, "reading across" biotransformation in environmental compartments such as soils or sediments from experiments with activated sludge outperformed three widely used in silico approaches for estimating half-lives and hence has immediate potential to support early assessment of biodegradability when aiming to develop chemicals that are safe and sustainable by design.