A multi-compartment physiologically based pharmacokinetic (PBPK) model coupled with Fourier-ARIMA (auto regressive integrated moving average) for estimation and prediction of polychlorinated biphenyls (PCB) concentration in tuna

Polychlorinated biphenyls (PCBs) are persistent environmental contaminants that accumulate in aquatic organisms, posing health risks to humans through the consumption of fish and other aquatic animals. As a top predator, tuna is particularly susceptible to PCB bioaccumulation due to its position in the food chain, highlighting the importance of accurate contamination prediction. This study introduces a novel hybrid methodology that integrates a six-compartment PBPK-inspired model with a Fourier-ARIMA statistical framework to estimate and forecast PCB concentrations in tuna tissues, including blood, muscle, gill, intestine, kidney, and liver, within one year. The PBPK-inspired model simulates physiological bioaccumulation mechanisms, while the Fourier-ARIMA approach improves prediction accuracy by capturing both long-term periodic trends (Fourier) and short-term variations (ARIMA). Simulated concentrations were compared against published experimental data, and a cumulative distribution function (CDF)-based risk assessment was conducted, benchmarked against regulatory thresholds established by the U.S. EPA (47 and 210 ng/g) and WHO (20 ng/g). The model estimated the highest PCB concentrations in the liver (750 ng/g) and kidney (270 ng/g), with muscle tissue showing lower levels (17 ng/g). Probabilistic analysis revealed the liver to be the primary site of PCB accumulation, with approximately 85 % of modeled concentrations exceeding the EPA high-risk benchmark (210 ng/g). In contrast, muscle tissue, the main edible portion, exhibited uniformly low levels, remaining below the WHO threshold of 20 ng/g throughout, suggesting limited dietary exposure risk. This hybrid modeling approach supports dynamic, tissue-level trend prediction and probabilistic risk evaluation, making it a valuable tool for assessing and managing PCB contamination in marine ecosystems.