Utilization of OATP1B Biomarker Coproporphyrin-I to Guide Drug-Drug Interaction Risk Assessment: Evaluation by the Pharmaceutical Industry.

Drug-drug interactions (DDIs) involving hepatic organic anion transporting polypeptides 1B1/1B3 (OATP1B) can be substantial, however, challenges remain for predicting interaction risk. Emerging evidence suggests that endogenous biomarkers, particularly coproporphyrin-I (CP-I), can be used to assess in vivo OATP1B activity. The present work under the International Consortium for Innovation and Quality in Pharmaceutical Development was aimed primarily at assessing CP-I as a biomarker for informing OATP1B DDI risk. Literature and unpublished CP-I data along with pertinent in vitro and clinical DDI information were collected to identify DDIs primarily involving OATP1B inhibition and assess the relationship between OATP1B substrate drug and CP-I exposure changes. Static models to predict changes in exposure of CP-I, as a selective OATP1B substrate, were also evaluated. Significant correlations were observed between CP-I area under the curve ratio (AUCR) or maximum concentration ratio (Cmax R) and AUCR of substrate drugs. In general, the CP-I Cmax R was equal to or greater than the CP-I AUCR. CP-I Cmax R < 1.25 was associated with absence of OATP1B-mediated DDIs (AUCR < 1.25) with no false negative predictions. CP-I Cmax R < 2 was associated with weak OATP1B-mediated DDIs (AUCR < 2). A correlation was identified between CP-I exposure changes and OATP1B1 static DDI predictions. Recommendations for collecting and interpreting CP-I data are discussed, including a decision tree for guiding DDI risk assessment. In conclusion, measurement of CP-I is recommended to inform OATP1B inhibition potential. The current analysis identified changes in CP-I exposure that may be used to prioritize, delay, or replace clinical DDI studies.

Characterization of the modes of action and dose-response relationship for thiocyanate on the thyroid hormone levels in rats using a computational approach.

Current practices for evaluating the cumulative risk of thyroid-active chemical mixtures (perchlorate, thiocyanate, nitrate) focus on the inhibition of thyroidal iodide uptake via the sodium iodide symporter (NIS) as the mode of action for potency equivalence calculations. However, unlike perchlorate, thiocyanate presents additional modes of action within the thyroid that could contribute to the overall thyroid perturbation. We tested the hypothesis of whether assuming a single mode of action of thyroidal iodide uptake inhibition is sufficient for describing the observed dose-response relationship for thiocyanate and its effects on serum thyroxine levels. An interaction model was developed by linking a biologically based dose-response model for iodide and thyroid hormones to a thiocyanate physiologically based pharmacokinetic model. Each model, adapted from the literature, was restructured and recalibrated in a Bayesian framework for the current mode of actions study. For a chronic exposure scenario, NIS inhibition alone was found not to be sufficient to describe the dose-response relationship for thiocyanate. Inclusion of additional modes of action involving iodide flux across the thyroid membrane and inhibition of iodide organification via thyroid peroxidase showed only moderate improvements in capturing the dose-response at environmental thiocyanate doses of exposure and failed to capture trends at very high doses. Our findings emphasize the need for more mechanistic data for chronic exposure scenarios to characterize better the overall dose-response relationship for thiocyanate. Risk assessment approaches for thyroid-active chemical mixtures that rely on NIS inhibition as the single mode of action may over-predict the contribution of thiocyanate to thyroid disruption.