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A human next generation PBK model for PFOA.

Chrysanthi Pachoulide1, Carolina Vogs2, Aude Ratier3

  • 1Wageningen University and Research, Division of Toxicology, Wageningen, Netherlands.

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Summary
This summary is machine-generated.

Next Generation Physiologically Based Kinetic (NG-PBK) models offer a solution for assessing human health risks from per- and polyfluoroalkyl substances (PFAS). This study developed a novel NG-PBK model for perfluorooctanoic acid (PFOA) using only in vitro and in silico data.

Keywords:
Global sensitivity analysisHuman biomonitoringNext generation risk assessmentPerfluorooctanoic acidPhysiologically based kinetic modelRead-across

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Area of Science:

  • Environmental toxicology and risk assessment
  • Computational toxicology and modeling
  • Human health risk assessment

Background:

  • Assessing human health risks of per- and polyfluoroalkyl substances (PFAS) is complex due to their vast number, structural variety, and limited toxicity data.
  • Next Generation Physiologically Based Kinetic (NG-PBK) models offer a mechanistic approach to overcome data gaps and facilitate risk assessment.
  • Existing models often rely on animal or human data calibration, limiting their mechanistic application.

Purpose of the Study:

  • To develop and validate a Next Generation Physiologically Based Kinetic (NG-PBK) model for perfluorooctanoic acid (PFOA) in humans.
  • To parameterize the model exclusively using in vitro and in silico data, avoiding calibration with in vivo observations.
  • To demonstrate the model's utility for extrapolation to data-poor PFAS and integration with human biomonitoring (HBM) data for Next Generation Risk Assessment (NGRA).

Main Methods:

  • Development of a NG-PBK model incorporating key toxicokinetic processes: protein partitioning, lipid partitioning, entero-hepatic circulation, renal elimination, and menstruation.
  • Parameterization of the model using exclusively in vitro and in silico derived data.
  • Global sensitivity analysis to identify critical model parameters.

Main Results:

  • The developed NG-PBK model for PFOA was highly sensitive to unbound plasma fraction, active transport, and tissue-plasma partition coefficients.
  • Model predictions for serum concentrations and half-lives aligned with human volunteer and biomonitoring study findings.
  • The model demonstrated mechanistic robustness, achieving equivalence with existing validated PFOA-PBK models without in vivo calibration.

Conclusions:

  • The study successfully developed a mechanistic NG-PBK model for PFOA, relying solely on in vitro and in silico data.
  • This model accurately predicts PFOA toxicokinetics and serves as a foundation for extrapolating to other PFAS.
  • Integration with HBM data will enhance NGRA for PFAS, supporting the 3R principles by reducing reliance on in vivo studies.