Translating dosimetry of Dibenzo[def,p]chrysene (DBC) and metabolites across dose and species using physiologically based pharmacokinetic (PBPK) modeling

Pande, Paritosh; Madeen, Erin; Williams, David E.; Crowell, Susan; Ognibene, Ted; Turteltaub, Ken W; Corley, Richard A.; Smith, Jordan N.

doi:10.1016/j.taap.2021.115830

Cited by 5 publications

(11 citation statements)

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“…All other model parameters (compartment volumes, blood flows, absorption rates, partitioning coefficients, etc.) were assumed to be of a reference human of 73 kg and the same for BaP and DBC, two similar, highly lipophilic compounds (log Kow 6.13 and 7.71, respectively) [19]. modified to include absorption, distribution, metabolism, and elimination pathways for BaP (Figure 1).…”

Section: Pbpk Interaction Modelmentioning

confidence: 99%

“…All other model parameters (compartment volumes, blood flows, absorption rates, partitioning coefficients, etc.) were assumed to be of a reference human of 73 kg and the same for BaP and DBC, two similar, highly lipophilic compounds (log Kow 6.13 and 7.71, respectively) [19]. We modified previously published PAH mod els [18,19] to include competitive inhibition of the metabolism of both parent compounds (i.e., DBC inhibits BaP metabolism, and BaP inhibits DBC metabolism).…”

Section: Pbpk Interaction Modelmentioning

confidence: 99%

“…The interaction PBPK model was coded and implemented in Magnolia, Version 1.2.2 (Magnolia Sciences, LLC, Orlando, FL, USA). We modified previously published PAH models [18,19] to include competitive inhibition of the metabolism of both parent compounds (i.e., DBC inhibits BaP metabolism, and BaP inhibits DBC metabolism).…”

Section: Pbpk Interaction Modelmentioning

confidence: 99%

“…Res. Public Health 2022, 19, 8266 2 of 14 Some PAHs are procarcinogens, and the United States Environmental Protection Agency (US EPA) frequently assesses PAH mixture cancer risk using the Relative Potency Factor approach [9]. The Relative Potency Factor approach estimates cancer risk of a chemical mixture by summing doses of component mixture compounds after normalizing each component dose with a relative cancer potency of that component compared to an index compound [9].…”

Section: Introductionmentioning

confidence: 99%

“…To evaluate this objective, we measured inhibition coefficients ( K i ) of binary mixtures of PAHs using BaP and dibenzo[def,p]chrysene (DBC), a PAH with a Relative Potency Factor of 30, in human hepatic microsomes [ 9 ]. We developed a physiologically based pharmacokinetic (PBPK) interaction model by integrating two PBPK models of DBC and BaP with metabolism interaction terms [ 18 , 19 ]. This allowed us to account for the observed competitive inhibition of parent PAH metabolism in in vitro metabolism assays and to predict the internal dosimetry of these compounds.…”

Section: Introductionmentioning

confidence: 99%

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Competitive Metabolism of Polycyclic Aromatic Hydrocarbons (PAHs): An Assessment Using In Vitro Metabolism and Physiologically Based Pharmacokinetic (PBPK) Modeling

Smith

Gaither

Pande

2022

IJERPH

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Humans are routinely exposed to complex mixtures such as polycyclic aromatic hydrocarbons (PAHs) rather than to single compounds, as are often assessed for hazards. Cytochrome P450 enzymes (CYPs) metabolize PAHs, and multiple PAHs found in mixtures can compete as substrates for individual CYPs (e.g., CYP1A1, CYP1B1, etc.). The objective of this study was to assess competitive inhibition of metabolism of PAH mixtures in humans and evaluate a key assumption of the Relative Potency Factor approach that common human exposures will not cause interactions among mixture components. To test this objective, we co-incubated binary mixtures of benzo[a]pyrene (BaP) and dibenzo[def,p]chrysene (DBC) in human hepatic microsomes and measured rates of enzymatic BaP and DBC disappearance. We observed competitive inhibition of BaP and DBC metabolism and measured inhibition coefficients (Ki), observing that BaP inhibited DBC metabolism more potently than DBC inhibited BaP metabolism (0.061 vs. 0.44 µM Ki, respectively). We developed a physiologically based pharmacokinetic (PBPK) interaction model by integrating PBPK models of DBC and BaP and incorporating measured metabolism inhibition coefficients. The PBPK model predicts significant increases in BaP and DBC concentrations in blood AUCs following high oral doses of PAHs (≥100 mg), five orders of magnitude higher than typical human exposures. We also measured inhibition coefficients of Supermix-10, a mixture of the most abundant PAHs measured at the Portland Harbor Superfund Site, on BaP and DBC metabolism. We observed similar potencies of inhibition coefficients of Supermix-10 compared to BaP and DBC. Overall, results of this study demonstrate that these PAHs compete for the same enzymes and, at high doses, inhibit metabolism and alter internal dosimetry of exposed PAHs. This approach predicts that BaP and DBC exposures required to observe metabolic interaction are much higher than typical human exposures, consistent with assumptions used when applying the Relative Potency Factor approach for PAH mixture risk assessment.

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Section: Pbpk Interaction Modelmentioning

confidence: 99%

“…All other model parameters (compartment volumes, blood flows, absorption rates, partitioning coefficients, etc.) were assumed to be of a reference human of 73 kg and the same for BaP and DBC, two similar, highly lipophilic compounds (log Kow 6.13 and 7.71, respectively) [19]. We modified previously published PAH mod els [18,19] to include competitive inhibition of the metabolism of both parent compounds (i.e., DBC inhibits BaP metabolism, and BaP inhibits DBC metabolism).…”

Section: Pbpk Interaction Modelmentioning

confidence: 99%

Section: Pbpk Interaction Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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