Investigation of acetaminophen toxicity in HepG2/ C3a microscale cultures using a system biology model of glutathione depletion

We have integrated in vitro and in silico information to investigate acetaminophen (APAP) and its metabolite N-acetyl-p-benzoquinone imine (NAPQI) toxicity in liver biochip. In previous works, we observed higher cytotoxicity of HepG2/C3a cultivated in biochips when exposed to 1 mM of APAP for 72 h as compared to Petri cultures. We complete our investigation with the present in silico approach to extend the mechanistic interpretation of the intracellular kinetics of the toxicity process. For that purpose, we propose a mathematical model based on the coupling of a drug pharmacokinetic model (PK) with a systemic biology model (SB) describing the reactive oxygen species (ROS) production by NAPQI and the subsequent glutathione (GSH) depletion. The SB model was parameterized using (i) transcriptomic data, (ii) qualitative results of time lapses ROS fluorescent curves for both control and 1-mM APAP-treated experiments, and (iii) additional GSH literature data. The PK model was parameterized (i) using the in vitro kinetic data (at 160 [micro]M, 1 mM, 10 mM), (ii) using the parameters resulting from a physiologically based pharmacokinetic (PBPK) literature model for APAP, and (iii) by literature data describing NAPQI formation. The PK-SB model predicted a ROS increase and GSH depletion due to the NAPQI formation. The transition from a detoxification phase and NAPQI and ROS accumulation was predicted for a NAPQI concentration ranging between 0.025 and 0.25 [micro]M in the cytosol. In parallel, we performed a dose response analysis in biochips that shows a reduction of the final hepatic cell number appeared in agreement with the time and doses associated with the switch of the NAPQI detoxification/accumulation. As a result, we were able to correlate in vitro extracellular APAP exposures with an intracellular in silico ROS accumulation using an integration of a coupled mathematical and experimental liver on chip approach