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  • A trivalent approach for determining in vitro toxicology: Examination of oxime K027.

A trivalent approach for determining in vitro toxicology: Examination of oxime K027.

Journal of applied toxicology : JAT (2014-05-24)
Adriana Prado, Georg A Petroianu, Dietrich E Lorke, Jeremy W Chambers
要旨

Unforeseen toxic effects contribute to compound attrition during preclinical evaluation and clinical trials. Consequently, there is a need to correlate in vitro toxicity to in vivo and clinical outcomes quickly and effectively. We propose an expedited evaluation of physiological parameters in vitro that will improve the ability to predict in vivo toxicity of potential therapeutics. By monitoring metabolism, mitochondrial physiology and cell viability, our approach provides insight to the extent of drug toxicity in vitro. To implement our approach, we used human hepatocellular carcinoma cells (HepG2) and neuroblastoma cells (SH-SY5Y) to monitor hepato- and neurotoxicity of the experimental oxime K027. We utilized a trivalent approach to measure metabolism, mitochondrial stress and induction of apoptosis in 96-well formats. Any change in these three areas may suggest drug-induced toxicity in vivo. K027 and pralidoxime, an oxime currently in clinical use, had no effect on glycolysis or oxygen consumption in HepG2 and SH-SY5Y cells. Similarly, these oximes did not induce oxidant generation nor alter mitochondrial membrane potential. Further, K027 and pralidoxime failed to activate effector caspases, and these oximes did not alter viability. The chemotherapeutic agent, docetaxel, negatively affected metabolism, mitochondrial physiology and viability. Our studies present a streamlined high-throughput trivalent approach for predicting toxicity in vitro, and this approach reveals that K027 has no measurable hepatotoxicity or neurotoxicity in vitro, which correlates with their in vivo data. This approach could eliminate toxic drugs from consideration for in vivo preclinical evaluation faster than existing toxicity prediction panels and ultimately prevent unnecessary experimentation.

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