Introduction: ABCG2 has a broad substrate specificity and is one of the most important efflux proteins modulating pharmacokinetics of drugs, nutrients and toxicokinetics of toxicants. ABCG2...

ABCG2/BCRP: variants, transporter interaction profile of substrates and inhibitors.

Quantitative assessment of drug-drug interactions (DDIs) involving breast cancer resistance protein (BCRP) inhibition is challenged by overlapping substrate/inhibitor specificity. This study used physiologically-based pharmacokinetic (PBPK) modeling to delineate the effects of inhibitor drugs on BCRP- and organic anion transporting polypeptide (OATP)1B-mediated disposition of rosuvastatin, which is a recommended BCRP clinical probe. Initial static model analysis using in vitro inhibition data suggested BCRP/OATP1B DDI risk while considering regulatory cutoff criteria for a majority of inhibitors assessed (25 of 27), which increased rosuvastatin plasma exposure to varying degree (~ 0-600%). However, rosuvastatin area under plasma concentration-time curve (AUC) was minimally impacted by BCRP inhibitors with calculated G-value (= gut concentration/inhibition potency) below 100. A comprehensive PBPK model accounting for intestinal (OATP2B1 and BCRP), hepatic (OATP1B, BCRP, and MRP4), and renal (OAT3) transport mechanisms was developed for rosuvastatin. Adopting in vitro inhibition data, rosuvastatin plasma AUC changes were predicted within 25% error for 9 of 12 inhibitors evaluated via PBPK modeling. This study illustrates the adequacy and utility of a mechanistic model-informed approach in quantitatively assessing BCRP-mediated DDIs.

Quantitative prediction of breast cancer resistant protein mediated drug-drug interactions using physiologically-based pharmacokinetic modeling.

Ipatasertib is a pan-AKT inhibitor in development for the treatment of cancer. Ipatasertib was metabolized by CYP3A4 to its major metabolite, M1 (G-037720), and was a P-gp substrate and OATP1B1/1B3 inhibitor in vitro. A phase I drug-drug interaction (DDI) study (n = 15) was conducted in healthy subjects to evaluate the effect of itraconazole (200-mg solution QD, 4 days), a strong CYP3A4 and P-gp inhibitor, on pharmacokinetics of ipatasertib (100-mg single dose). Itraconazole increased the Cmax and AUC0-∞ of ipatasertib by 2.3- and 5.5-fold, respectively, increased the half-life by 53%, and delayed the tmax by 1 hour. The Cmax and AUC0-72h of its metabolite M1 (G-037720) reduced by 91% and 68%, respectively. This study confirmed that CYP3A4 plays a major role in ipatasertib clearance. Furthermore, the interaction of ipatasertib with coproporphyrin (CP) I and CPIII, the two endogenous substrates of OATP1B1/1B3, was evaluated in this study. CPI and CPIII plasma levels were unchanged in the presence of ipatasertib, both at exposures of 100 mg and at higher exposures in combination with itraconazole. This indicated no in vivo inhibition of OATP1B1/1B3 by ipatasertib. Additionally, it was shown that CPI and CPIII were not P-gp substrates in vitro, and itraconazole had no effect on CPI and CPIII concentrations in vivo. The latter is an important finding because it will simplify interpretation of future DDI studies using CPI/CPIII as OATP1B1/1B3 biomarkers. SIGNIFICANCE STATEMENT This drug-drug interaction study in healthy volunteers demonstrated that CYP3A4 plays a major role in ipatasertib clearance, and that ipatasertib is not an organic anion transporting polypeptide 1B1/1B3 inhibitor. Furthermore, it was demonstrated that itraconazole, an inhibitor of CYP3A4 and several transporters, did not affect CPI/CPIII levels in vivo. This increases the understanding and application of these endogenous substrates as well as itraconazole in complex drug interaction studies.

https://jpet.aspetjournals.org/content/jpet/378/2/87.full.pdf

Evaluation of Ipatasertib Interactions with Itraconazole and Coproporphyrin I and III in a Single Drug Interaction Study in Healthy Subjects.

Solute carrier (SLC) transporters present as the loci of important drug–drug interactions (DDIs). Therefore, sponsors generate in vitro half‐maximal inhibitory concentration (IC50) data and apply regulatory agency‐guided “static” methods to assess DDI risk and the need for a formal clinical DDI study. Because such methods are conservative and high false‐positive rates are likely (e.g., DDI study triggered when liver SLC R value ≥ 1.04 and renal SLC maximal unbound plasma (Cmax,u)/IC50 ratio ≥ 0.02), investigators have attempted to deploy plasma‐ and urine‐based SLC biomarkers in phase I studies to de‐risk DDI and obviate the need for drug probe‐based studies. In this regard, it was possible to generate in‐house in vitro SLC IC50 data for various clinically (biomarker)‐qualified perpetrator drugs, under standard assay conditions, and then estimate “% inhibition” for each SLC and relate it empirically to published clinical biomarker data (area under the plasma concentration vs. time curve (AUC) ratio (AUCR, AUCinhibitor/AUCreference) and % decrease in renal clearance (ΔCLrenal)). After such a “calibration” exercise, it was determined that only compounds with high R values (> 1.5) and Cmax,u/IC50 ratios (> 0.5) are likely to significantly modulate liver (AUCR > 1.25) and renal (ΔCLrenal > 25%) biomarkers and evoke DDI risk. The % inhibition approach supports integration of liver and renal SLC data and allows one to generate pan‐SLC inhibition signatures for different test perpetrators (e.g., SLC % inhibition ranking). In turn, such signatures can guide the selection of the most appropriate individual (or combinations of) biomarkers for testing in phase I studies.

Reimagining the Framework Supporting the Static Analysis of Transporter Drug Interaction Risk; Integrated Use of Biomarkers to Generate Pan‐Transporter Inhibition Signatures

In light of an ever-increasing exposure to chemicals, the topic of potential mixture toxicity has gained increased attention, particularly as the toxicological toolbox to address such questions has vastly improved. Routinely toxicological risk assessments will rely on the analysis of individual compounds with mixture effects being considered only in those specific cases where co-exposure is foreseeable, for example for pesticides or food contact materials. In the field of pesticides, active substances are summarized in so-called cumulative assessment groups (CAG) which are primarily based on their toxicodynamic properties, that is, respective target organs and mode of action (MoA). In this context, compounds causing toxicity by a similar MoA are assumed to follow a model of dose/concentration addition (DACA). However, the respective approach inherently falls short of addressing cases where there are dissimilar or independent MoAs resulting in wider toxicokinetic effects. Yet, the latter are often the underlying cause when effects deviate from the DACA model. In the present manuscript, we therefore suggest additionally to consider toxicokinetic effects (especially related to xenobiotic metabolism and transporter interaction) for the grouping of substances to predict mixture toxicity. In line with the concept of MoA-based CAGs, we propose common kinetics groups (CKGs) as an additional tool for grouping of chemicals and mixture prioritization. Fundamentals of the CKG concept are discussed, along with challenges for its implementation, and methodological approaches and examples are explored. 

/pdf/an-approach-for-mixture-testing-and-prioritization-based-on-1tdgpug8.pdf

An approach for mixture testing and prioritization based on common kinetic groups

Organic anion-transporting polypeptide (OATP) 1B1/3-mediated drug-drug interaction (DDI) potential is evaluated in vivo with rosuvastatin (RST) as a probe substrate in clinical studies. We calibrated our assay with RST and estradiol 17-β-D-glucuronide (E217βG)/cholecystokinin-8 (CCK8) as in vitro probes for qualitative and quantitative prediction of OATP1B-mediated DDI potential for RST. In vitro OATP1B1/1B3 inhibition using E217βG and CCK8 yielded higher area under the curve (AUC) ratio (AUCR) values numerically with the static model, but all probes performed similarly from a qualitative cutoff-based prediction, as described in regulatory guidances. However, the magnitudes of DDI were not captured satisfactorily. Considering that clearance of RST is also mediated by gut breast cancer resistance protein (BCRP), inhibition of BCRP was also incorporated in the DDI prediction if the gut inhibitor concentrations were 10 × IC50 for BCRP inhibition. This combined static model closely predicted the magnitude of RST DDI with root-mean-square error values of 0.767-0.812 and 1.24-1.31 with and without BCRP inhibition, respectively, for in vitro-in vivo correlation of DDI. Physiologically based pharmacokinetic (PBPK) modeling was also used to simulate DDI between RST and rifampicin, asunaprevir, and velpatasvir. Predicted AUCR for rifampicin and asunaprevir was within 1.5-fold of that observed, whereas that for velpatasvir showed a 2-fold underprediction. Overall, the combined static model incorporating both OATP1B and BCRP inhibition provides a quick and simple mathematical approach to quantitatively predict the magnitude of transporter-mediated DDI for RST for routine application. PBPK complements the static model and provides a framework for studying molecules when a dynamic model is needed. SIGNIFICANCE STATEMENT: Using 22 drugs, we show that a static model for organic anion-transporting polypeptide (OATP) 1B1/1B3 inhibition can qualitatively predict potential for drug-drug interaction (DDI) using a cutoff-based approach, as in regulatory guidances. However, consideration of both OATP1B1/3 and gut breast cancer resistance protein inhibition provided a better prediction of the magnitude of the transporter-mediated DDI of these inhibitors with rosuvastatin. Based on these results, we have proposed an empirical mechanistic-static approach for a more reliable prediction of transporter-mediated DDI liability with rosuvastatin that drug development teams can leverage.

https://dmd.aspetjournals.org/content/dmd/early/2020/10/09/dmd.120.000149.full.pdf

Calibrating the In Vitro-In Vivo Correlation for OATP-Mediated Drug-Drug Interactions with Rosuvastatin Using Static and PBPK Models.

Friction at water–carbon interfaces remains a major puzzle with theories and simulations unable to explain experimental trends in nanoscale waterflow. A recent theoretical framework—quantum friction (QF)—proposes to resolve these experimental observations by considering nonadiabatic coupling between dielectric fluctuations in water and graphitic surfaces. Here, using a classical model that enables fine-tuning of the solid’s dielectric spectrum, we provide evidence from simulations in general support of QF. In particular, as features in the solid’s dielectric spectrum begin to overlap with water’s librational and Debye modes, we find an increase in friction in line with that proposed by QF. At the microscopic level, we find that this contribution to friction manifests more distinctly in the dynamics of the solid’s charge density than that of water. Our findings suggest that experimental signatures of QF may be more pronounced in the solid’s response rather than liquid water’s.

/pdf/classical-quantum-friction-at-water-carbon-interfaces-5w72kxr2.pdf

Classical Quantum Friction at Water–Carbon Interfaces

Correlation Analysis of Potential Breast Cancer Resistance Protein Probes in Different Monolayer Systems.

ABCB4 is almost exclusively expressed in the liver, where it plays an essential role in bile formation by transporting phospholipids into the bile. ABCB4 polymorphisms and deficiencies in humans are associated with a wide spectrum of hepatobiliary disorders, attesting to its crucial physiological function. Inhibition of ABCB4 by drugs may lead to cholestasis and drug-induced liver injury (DILI), although compared with other drug transporters, there are only a few identified substrates and inhibitors of ABCB4. Since ABCB4 shares up to 76% identity and 86% similarity in the amino acid sequence with ABCB1, also known to have common drug substrates and inhibitors, we aimed to develop an ABCB4 expressing Abcb1-knockout MDCKII cell line for transcellular transport assays. This in vitro system allows the screening of ABCB4-specific drug substrates and inhibitors independently of ABCB1 activity. Abcb1KO-MDCKII-ABCB4 cells constitute a reproducible, conclusive, and easy to use assay to study drug interactions with digoxin as a substrate. Screening a set of drugs with different DILI outcomes proved that this assay is applicable to test ABCB4 inhibitory potency. Our results are consistent with prior findings concerning hepatotoxicity causality and provide new insights for identifying drugs as potential ABCB4 inhibitors and substrates.

/pdf/a-unique-in-vitro-assay-to-investigate-abcb4-transport-28igfhvc.pdf

A Unique In Vitro Assay to Investigate ABCB4 Transport Function

Electrochemical carbon dioxide capture has recently emerged as a promising alternative approach to conventional energy-intensive carbon capture methods. A common electrochemical capture approach is to employ redox-active molecules such as quinones. Upon electrochemical reduction, quinones become activated for the capture of CO 2 through a chemical reaction. A key dis-advantage of this method is the possibility of side-reactions with oxygen, which is present in almost all gas mixtures of interest for carbon capture. This is-sue can potentially be mitigated by fine-tuning redox potentials through the introduction of electron-withdrawing groups on the quinone ring. In this article, we investigate the thermodynamics of the electron transfer and chemical steps of CO 2 capture in different quinone derivatives with a range of substituents. By combining density functional theory calculations and cyclic voltammetry experiments, we support a previously described trade-off between redox potentials and the strength of CO 2 capture. We show that redox potentials can readily be tuned to more positive values to impart stability to oxygen, but as a consequence, significant decreases in CO 2 binding free energies are observed. Our calculations support this effect for a large series of anthraquinones and benzoquinones, with different trade-off relationships observed for the two classes of molecules. These trade-offs must be taken into consideration for the design of improved redox-active molecules for electrochemical CO 2 capture.

Annamaria Bui

Papers

Calibrating the In Vitro-In Vivo Correlation for OATP-Mediated Drug-Drug Interactions with Rosuvastatin Using Static and PBPK Models.

Classical Quantum Friction at Water–Carbon Interfaces

Correlation Analysis of Potential Breast Cancer Resistance Protein Probes in Different Monolayer Systems.

A Unique In Vitro Assay to Investigate ABCB4 Transport Function

Trade-off between redox potential and strength of electrochemical CO 2 capture in quinones