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An Integrated AIVIVE-PBPK-QIVIVE Framework with HTTK Validation for Probabilistic Risk Assessment of Neodymium
Ning Wang1, Jing Leng1, Hui-Min Zhang1
1Institute of Chemical Safety Evaluation/Key Laboratory of Environmental and Health Impact Assessment of New Pollutants, Shanghai Municipal Center for Disease Control and Prevention, 1399 at Shenhong Road, Shanghai 201107, China.
Abstract:
Rare earth elements (REEs) are critical to modern industries but pose growing health risks due to increasing environmental release, and neodymium nitrate (Nd(NO3)3), a representative REE compound, lacks comprehensive toxicological data. To address this, we developed an integrated computational toxicology framework combining artificial intelligence-enhanced in vitro to in vivo extrapolation (AIVIVE), physiologically based pharmacokinetic (PBPK) modeling, quantitative in vitro to in vivo extrapolation (QIVIVE), and high-throughput toxicokinetic (HTTK) validation for mechanism-based risk assessment. A closed-loop "model-informed experimental design" was employed, where AIVIVE, using conditional generative adversarial networks (cGAN) predicted toxicity pathways from multiomics data, experimental determination of key toxicokinetic parameters (plasma protein binding and partition coefficients) calibrated HTTK predictions, and a PBPK-QIVIVE framework incorporating nonlinear features extrapolated in vitro EC50 to human equivalent doses (HED), with Monte Carlo simulation and Sobol sensitivity analysis quantifying uncertainty. Results showed AIVIVE predicted transcriptomic responses with high fidelity (cosine similarity = 0.9986) and identified p53, apoptosis, and ferroptosis pathways with >85% accuracy. Experimental calibration revealed significant nonlinearity: plasma unbound fraction (fu) exhibited a U-shaped concentration dependence (0.556 at 1 μg/mL → 0.176 at 10 μg/mL → 0.965 at 100 μg/mL), while cellular partition coefficients (K) displayed an inverted U-shape (0.048-0.079). HTTK substantially underestimated fu (∼15-fold) and partition coefficients (2.4-5.5-fold). The integrated framework predicted a median HED of 0.032 mg/kg/day (95% CI: 0.012-0.098), with an 18% probability of exceeding the high-risk threshold (0.1 mg/kg/day). Sensitivity analysis identified fu (65%), K (22%), and EC50 (11%) as the dominant uncertainty sources. Probabilistic integration with exposure data indicated a high safety margin for the general population but concerns for mining area residents (100% probability of margin of exposure <100). This framework addresses the challenges of evaluating metals with nonlinear kinetics, reduces reliance on animal testing, and supports regulatory decisions, proposing an occupational exposure limit of 0.05 mg/m3 for neodymium nitrate.
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