Exposure to cadmium (Cd), an environmental heavy metal pollutant, can cause significant toxicities and is a critical public health concern. Physiologically based toxicokinetic (PBTK) modeling has been used to understand and predict Cd body burdens. Although many human PBTK models of Cd were published in the last few decades – nearly all based on the original framework developed by Kjellström and Nordberg (K&N) in 1978 – caveats still remain across these models, limiting their effective and extended use as a modern in silico tool for Cd risk assessment. Main issues include lack of physiological blood flows, systemic rather than portal blood entry of gastrointestinal (GI) tract-absorbed Cd, part of urinary and fecal Cd being excreted directly from blood, and empirical adjustment to substantially lower overpredicted plasma Cd fractions. These issues compromise the model accuracy and make it less straightforward to incorporate physiological variabilities for populational models. Here, we aimed to address these limitations. We updated the model by incorporating blood flow to tissues, splitting each tissue into tissue blood and tissue proper sub-compartments, and making liver blood as the entry point of GI tract-absorbed Cd. We also added a filtrate sub-compartment to kidney to better describe urinary Cd excretion. The updated model was rigorously calibrated by using the dietary and cigarette-smoking Cd intakes, body growth, and blood, urinary, liver, and kidney Cd dosimetry data, all from the US population. Compared with the existing models, our model performs better in various aspects across sex, age, and smoking status, especially for blood, liver, and kidney Cd concentrations, as well as different blood Cd fractions. In summary, by addressing prior model limitations, our model enables more accurate quantitative predictions of internal Cd burdens for lifetime exposure and provides a much-improved framework for future extension into populational PBTK models and precision risk assessments of Cd exposure.
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