Predictive utility of in vitro rifampin induction data generated in fresh and cryopreserved human hepatocytes, Fa2N-4, and HepaRG cells

Physiologically based kinetic (PBK) modeling of propiconazole using a machine learning-enhanced read-across approach for interspecies extrapolation

A significant challenge in the traditional human health risk assessment of agrochemicals is the uncertainty in quantifying the interspecies differences between animal models and humans. To work toward a more accurate and animal-free risk determination, new approaches such as physiologically based kinetic (PBK) modeling have been used to perform dosimetry extrapolation from animals to humans. However, the regulatory use and acceptance of PBK modeling is limited for chemicals that lack in vivo animal pharmacokinetic (PK) data, given the inability to evaluate models. To address these challenges, this study developed PBK models in the absence of in vivo PK data for the fungicide propiconazole, an activator of constitutive androstane receptor (CAR)/pregnane X receptor (PXR). A fit-for-purpose read-across approach was integrated with hierarchical clustering - an unsupervised machine learning algorithm, to bridge the knowledge gap. The integration allowed the incorporation of a broad spectrum of attributes for analog consideration, and enabled the analog selection in a simple, reproducible, and objective manner. The applicability was evaluated and demonstrated using penconazole (source) and three pseudo-unknown target chemicals (epoxiconazole, tebuconazole and triadimefon). Applying this machine learning-enhanced read-across approach, difenoconazole was selected as the most appropriate analog for propiconazole. A mouse PBK model was developed and evaluated for difenoconazole (source), with the mode of action of CAR/PXR activation incorporated to simulate the in vivo autoinduction of metabolism. The difenoconazole mouse model then served as a template for constructing the propiconazole mouse model. A parallelogram approach was subsequently applied to develop the propiconazole rat and human models, enabling a quantitative assessment of interspecies differences in dosimetry. This integrated approach represents a substantial advancement toward refining risk assessment of propiconazole within the framework of animal alternative safety assessment strategies.

PBTK model-based analysis of CYP3A4 induction and the toxicokinetics of the pyrrolizidine alkaloid retrorsine in man

Cytochrome P450 (CYP)3A4 induction by drugs and pesticides plays a critical role in the enhancement of pyrrolizidine alkaloid (PA) toxicity as it leads to increased formation of hepatotoxic dehydro-PA metabolites. Addressing the need for a quantitative analysis of this interaction, we developed a physiologically-based toxicokinetic (PBTK) model. Specifically, the model describes the impact of the well-characterized CYP3A4 inducer rifampicin on the kinetics of retrorsine, which is a prototypic PA and contaminant in herbal teas. Based on consumption data, the kinetics after daily intake of retrorsine were simulated with concomitant rifampicin treatment. Strongest impact on retrorsine kinetics (plasma AUC24 and C max reduced to 67% and 74% compared to the rifampicin-free reference) was predicted directly after withdrawal of rifampicin. At this time point, the competitive inhibitory effect of rifampicin stopped, while CYP3A4 induction was still near its maximum. Due to the impacted metabolism kinetics, the cumulative formation of intestinal retrorsine CYP3A4 metabolites increased to 254% (from 10 to 25 nmol), while the cumulative formation of hepatic CYP3A4 metabolites was not affected (57 nmol). Return to baseline PA toxicokinetics was predicted 14 days after stop of a 14-day rifampicin treatment. In conclusion, the PBTK model showed to be a promising tool to assess the dynamic interplay of enzyme induction and toxification pathways.

Leveraging physiologically based pharmacokinetic modeling to optimize dosing for lopinavir/ritonavir with rifampin in pediatric patients

STUDY OBJECTIVE

Treatment of HIV and tuberculosis co-infection leads to significant mortality in pediatric patients, and treatment can be challenging due to the clinically significant drug-drug interaction (DDI) between lopinavir/ritonavir (LPV/RTV) and rifampin. Doubling LPV/RTV results in insufficient lopinavir trough concentrations in pediatric patients. The objective of this study was to leverage physiologically based pharmacokinetic (PBPK) modeling to optimize the adjusted doses of LPV/RTV in children receiving the WHO-revised doses of rifampin (15 mg/kg daily).

DESIGN

Adult and pediatric PBPK models for LPV/RTV with rifampin were developed, including CYP3A and P-glycoprotein inhibition and induction.

SETTING (OR DATA SOURCE)

Data for LPV/RTV model development and evaluation were available from the pediatric AIDS Clinical Trials Group.

PATIENTS

Dosing simulations were next performed to optimize dosing in children (2 months to 8 years of age).

INTERVENTION

Exposure following super-boosted LPV/RTV with 10 and 15 mg/kg PO daily rifampin was simulated.

MEASUREMENTS AND MAIN RESULTS

Simulated parameters were within twofold observations for LPV, RTV, and rifampin in adults and children ≥2 weeks old. The model predicted that, in healthy adults receiving 400/100 mg oral LPV/RTV twice daily (BID), co-treatment with 600 mg oral rifampin daily decreased the steady-state area under the concentration vs. time curve of LPV by 79%, in line with the observed change of 75%. Simulated and observed concentration profiles were comparable for LPV/RTV (230/57.5 mg/m2 ) PO BID without rifampin and 230/230 mg/m2 LPV/RTV PO BID with 10 mg/kg PO daily rifampin in pediatric patients. Sixteen mg/kg of super-boosted LPV (LPV/RTV 1:1) PO BID with 15 mg/kg PO daily rifampin achieved simulated LPV troughs >1 mg/L in ≥93% of virtual children weighing 3.0-24.9 kg, which was comparable with 10 mg/kg PO daily rifampin.

CONCLUSIONS

Super-boosted LPV/RTV with 15 mg/kg rifampin achieves therapeutic LPV troughs in HIV/TB-infected simulated children.

Physiologically based pharmacokinetic modeling of brivaracetam and its interactions with rifampin based on CYP2C19 phenotypes

Brivaracetam (BRV), a third-generation antiepileptic drug (AED), is primarily metabolized through amidase hydrolysis and CYP2C19-mediated hydroxylation in vivo. This study utilized physiologically based pharmacokinetic (PBPK) modeling to explore the pharmacokinetics of BRV and drug interactions between BRV and rifampin (RIF), a CYP2C19 inducer, based on CYP2C19 genetic polymorphisms. A PBPK model of BRV was developed in the general population and in individuals with different CYP2C19 phenotypes by adjusting catalytic rate constants (k_cat), and the model was validated with observed clinical data. The model was then extrapolated to predict BRV steady-state plasma concentration in individuals with different CYP2C19 phenotypes, with or without coadministration of RIF. The developed model adequately described BRV exposure in the abovementioned populations. The predicted steady-state area under the curve (AUC_τ-ss) increases by 20% in heterozygous extensive metabolizers (hEMs) and 55% in poor metabolizers (PMs), compared to homozygous extensive metabolizer (EMs). When coadministered with RIF, the model predicted the most significant magnitude of drug-drug interaction (DDI) in EMs, while the exposure change of BRV was minimal in PMs. Referencing the recommended concentration for therapeutic drug monitoring (TDM), we concluded that the current clinical maintenance dose of BRV is acceptable regardless of CYP2C19 polymorphisms and coadministration with RIF.

Prediction of Rivaroxaban-Rifampin Interaction After Major Orthopedic Surgery: Physiologically Based Pharmacokinetic Modeling and Simulation

Rivaroxaban is commonly used for the prophylaxis of venous thromboembolism (VTE) for patients undergoing major orthopedic surgery. Rivaroxaban is primarily eliminated by hepatic CYP450 metabolism and renal excretion. Rifampin is a commonly used antibiotic for prosthetic joint infections (PJI) and a potent inducer of CYP450 enzymes. Clinical data about drug-drug interactions of rivaroxaban and rifampin are limited. The present study is to describe DDI of rivaroxaban and rifampin in several prosthetic joint infections patients undergoing major orthopedic surgery. We retrospectively identified six patients concomitantly administered with rivaroxaban and rifampin between 2019 and 2020. Plasma samples of these patients with accurate sampling time were chosen from the biobank and plasma levels of rivaroxaban were measured at each time point. A physiologically based pharmacokinetic model for the rivaroxaban-rifampin interaction was developed to predict the optimal dosing regimen of rivaroxaban in the case of co-medication with rifampin. The model was validated by the observed plasma concentration of rivaroxaban from the above patients. From this model, it could be simulated that when rifampin starts or stops, gradually changing rivaroxaban dose during the first few days would elevate the efficacy and safety of rivaroxaban.

Assessing OATP1B1- and OATP1B3-Mediated Drug-Drug Interaction Potential of Vemurafenib Using R-Value and Physiologically-Based Pharmacokinetic Models

Organic anion transporting polypeptides (OATP) 1B1 and OATP1B3 are important determinants of transporter-mediated drug-drug interactions (DDIs). Current studies assessed the OATP1B1 and OATP1B3-mediated DDI potential of vemurafenib, a kinase inhibitor drug with high protein binding and low aqueous solubility, using R-value and physiologically-based pharmacokinetic (PBPK) models. The total half-maximal inhibitory concentration (IC50,total) values of vemurafenib against OATP1B1 and OATP1B3 were determined in 100% human plasma in transporter-overexpressing human embryonic kidney 293 stable cell lines. The unbound fraction of vemurafenib in human plasma before (fu,plasma) and after addition into the uptake assay plate (fu,plasma,inc) were determined by rapid equilibrium dialysis. There was no statistically significant difference between fu,plasma and fu,plasma,inc. Vemurafenib IC50,total values against OATP1B1 and OATP1B3 are 175 ± 82 and 231 ± 26 μM, respectively. The R-values [R = 1 + fu,plasma × Iin,max/(fu,plasma,inc × IC50,total)] were then simplified as R = 1+Iin,max/IC50,total, and were 1.76 and 1.57 for OATP1B1 and OATP1B3, respectively. The simulated pravastatin AUC ratio was 1.28 when a single dose of pravastatin (40 mg) was co-administered with vemurafenib (960 mg, twice daily) at steady-state, compared to pravastatin alone. Both R-value and PBPK models predict that vemurafenib has the potential to cause OATP1B1- and OATP1B3-mediated DDIs.

Hepatocytic transcriptional signatures predict comparative drug interaction potential of rifamycin antibiotics

Current strategies to treat tuberculosis (TB) and co-morbidities involve multidrug combination therapies. Rifamycin antibiotics are a key component of TB therapy and a common source of drug–drug interactions (DDIs) due to induction of drug metabolizing enzymes (DMEs). Management of rifamycin DDIs are complex, particularly in patients with co-morbidities, and differences in DDI potential between rifamycin antibiotics are not well established. DME profiles induced in response to tuberculosis antibiotics (rifampin, rifabutin and rifapentine) were compared in primary human hepatocytes. We identified rifamycin induced DMEs, cytochrome P450 (CYP) 2C8/3A4/3A5, SULT2A, and UGT1A4/1A5 and predicted lower DDIs of rifapentine with 58 clinical drugs used to treat co-morbidities in TB patients. Transcriptional networks and upstream regulator analyses showed FOXA3, HNF4α, NR1I2, NR1I3, NR3C1 and RXRα as key transcriptional regulators of rifamycin induced DMEs. Our study findings are an important resource to design effective medication regimens to treat common co-conditions in TB patients.

MicroRNA Mediated Changes in Drug Metabolism and Target Gene Expression by Efavirenz and Rifampicin In Vitro: Clinical Implications

Efavirenz (EFV) and rifampicin (RMP) are widely prescribed in Africa for treatment of HIV/AIDS and tuberculosis epidemics. Exposure to medicines can alter drug metabolism, for example, through changes in expression of microRNAs. We report, in this study, novel observations on the ways in which EFV and RMP change microRNA expression signatures in vitro in HepaRG cells. Additionally, we discuss the clinical implications of changes in expression of drug-metabolizing enzyme genes, such as CYP3A4, CYP3A5, UGT1A1, CYP2B6, and NR1I3. Differentiated HepaRG cells were treated with EFV (6.4 μM) or RMP (24.4 μM) for 24 h. Treatment of HepaRG cells with EFV resulted in a significant increase in messenger RNA (mRNA) expression for CYP3A4 (12.51-fold, p = 0.002), CYP3A5 (2.10-fold, p = 0.019), and UGT1A1 (2.52-fold, p = 0.005), whereas NR1I3 expression decreased (0.41-fold, p = 0.02). On the other hand, treatment of HepaRG cells with RMP resulted in a significant increase in mRNA expression for CYP2B6 (6.68-fold, p = 0.007) and CYP3A4 (111.96-fold, p = 0.001), whereas NR1I3 expression decreased (0.46-fold, p = 0.033). These data point to several important clinical implications through changes in drug/drug interaction risks and achieving optimal therapeutics. All in all, this study shows that differential expression of microRNAs after treatment with EFV and RMP adds another layer of complexity that should be incorporated in pharmacogenomic algorithms to render drug response more predictable.

Evaluation of a novel PXR-knockout in HepaRG™ cells

The nuclear pregnane X receptor (PXR) regulates the expression of genes involved in the metabolism, hepatobiliary disposition, and toxicity of drugs and endogenous compounds. PXR is a promiscuous nuclear hormone receptor (NHR) with significant ligand and DNA‐binding crosstalk with the constitutive androstane receptor (CAR); hence, defining the precise role of PXR in gene regulation is challenging. Here, utilising a novel PXR‐knockout (KO) HepaRG cell line, real‐time PCR analysis was conducted to determine PXR involvement for a range of inducers. The selective PXR agonist rifampicin, a selective CAR activator, 6‐(4‐chlorophenyl)imidazo[2,1‐b][1,3]thiazole‐5‐carbaldehyde O‐(3,4‐dichlorobenzyl)oxime (CITCO), and dual activators of CAR and PXR including phenobarbital (PB) were analyzed. HepaRG control cells (5F clone) were responsive to prototypical inducers of CYP2B6 and CYP3A4. No response was observed in the PXR‐KO cells treated with rifampicin. Induction of CYP3A4 by PB, artemisinin, and phenytoin was also much reduced in PXR‐KO cells, while the response to CITCO was maintained. This finding is in agreement with the abolition of functional PXR expression. The apparent EC₅₀ values for PB were in agreement between the cell lines; however, CITCO was ~threefold (0.3 μmol/L vs. 1 μmol/L) lower in the PXR‐KO cells compared with the 5F cells for CYP2B6 induction. Results presented support the application of the novel PXR‐KO cells in the definitive assignment of PXR‐mediated CYP2B6 and CYP3A4 induction. Utilization of such cell lines will allow advancement in composing structure activity relationships rather than relying predominantly on pharmacological manipulations and provide in‐depth mechanistic evaluation.

Contextualizing Hepatocyte Functionality of Cryopreserved HepaRG Cell Cultures

Over the last decade HepaRG cells have emerged as a promising alternative to primary human hepatocytes (PHH) and have been featured in over 300 research publications. Most of these reports employed freshly differentiated HepaRG cells that require time-consuming culture (∼28 days) for full differentiation. Recently, a cryopreserved, predifferentiated format of HepaRG cells (termed here "cryo-HepaRG") has emerged as a new model that improves global availability and experimental flexibility; however, it is largely unknown whether HepaRG cells in this format fully retain their hepatic characteristics. Therefore, we systematically investigated the hepatocyte functionality of cryo-HepaRG cultures in context with the range of interindividual variation observed with PHH in both sandwich-culture and suspension formats. These evaluations uncovered a novel adaptation period for the cryo-HepaRG format and demonstrated the impact of extracellular matrix on cryo-HepaRG functionality. Pharmacologically important drug-metabolizing alleles were genotyped in HepaRG cells and poor metabolizer alleles for CYP2D6, CYP2C9, and CYP3A5 were identified and consistent with higher frequency alleles found in individuals of Caucasian decent. We observed liver enzyme inducibility with aryl hydrocarbon receptor, constitutive androstane receptor (CAR), and pregnane X receptor activators comparable to that of sandwich-cultured PHH. Finally, we show for the first time that cryo-HepaRG supports proper CAR cytosolic sequestration and translocation to hepatocyte nuclei in response to phenobarbital treatment. Taken together, these data reveal important considerations for the use of this cell model and demonstrate that cryo-HepaRG are suitable for metabolism and toxicology screening.

Evaluation of CYP3A4 inhibition and hepatotoxicity using DMSO-treated human hepatoma HuH-7 cells

A human hepatoma cell line (HuH-7) was evaluated as a metabolically competent cell model to investigate cytochrome P450 3A4 (CYP3A4) inhibition, induction, and hepatotoxicity. First, CYP3A4 gene expression and activity were determined in HuH-7 cells under three culture conditions: 1-week culture, 3-week culture, or 1 % dimethyl sulfoxide (DMSO) treatment. HuH-7 cells treated with DMSO for 2 weeks after confluence expressed the highest CYP3A4 gene expression and activity compared to the other two culture conditions. Furthermore, CYP3A4 activity in DMSO-treated HuH-7 cells was compared to that in a human hepatoma cell line (HepG2/C3A) and human bipotent progenitor cell line (HepaRG), which yielded the following ranking: HepaRG > DMSO-treated HuH-7 >> HepG2/C3A cells. The effects of three known CYP3A4 inhibitors were evaluated using DMSO-treated HuH-7 cells. CYP3A4 enzyme inhibition in HuH-7 cells was further compared to human recombinant CYP3A4, indicating similar potency for reversible inhibitors (IC 50 within 2.5-fold), but different potency for the irreversible inhibitor. Next, induction of CYP3A4 activity was compared between DMSO-treated HuH-7 and HepaRG cells using two known inducers. DMSO-treated HuH-7 cells yielded minimal CYP3A4 induction compared to that in the HepaRG cells after 48-h treatments. Finally, the cytotoxicity of five known hepatotoxicants was evaluated in DMSO-treated HuH-7, HepG2/C3A, and HepaRG cells, and significant differences in cytotoxic sensitivity were observed. Overall, DMSO-treated HuH-7 cells are a valuable model for medium- or high-throughput screening of chemicals for CYP3A4 inhibition and hepatotoxicity.

A mechanistic physiologically based pharmacokinetic-enzyme turnover model involving both intestine and liver to predict CYP3A induction-mediated drug-drug interactions

Cytochrome P450 (CYP) 3A induction-mediated drug-drug interaction (DDI) is one of the major concerns in drug development and clinical practice. The aim of the present study was to develop a novel mechanistic physiologically based pharmacokinetic (PBPK)-enzyme turnover model involving both intestinal and hepatic CYP3A induction to quantitatively predict magnitude of CYP3A induction-mediated DDIs from in vitro data. The contribution of intestinal P-glycoprotein (P-gp) was also incorporated into the PBPK model. First, the pharmacokinetic profiles of three inducers and 14 CYP3A substrates were predicted successfully using the developed model, with the predicted area under the plasma concentration-time curve (AUC) [area under the plasma concentration-time curve] and the peak concentration (Cmax ) [the peak concentration] in accordance with reported values. The model was further applied to predict DDIs between the three inducers and 14 CYP3A substrates. Results showed that predicted AUC and Cmax ratios in the presence and absence of inducer were within twofold of observed values for 17 (74%) of the 23 DDI studies, and for 14 (82%) of the 17 DDI studies, respectively. All the results gave us a conclusion that the developed mechanistic PBPK-enzyme turnover model showed great advantages on quantitative prediction of CYP3A induction-mediated DDIs.

Rifampicin alters the expression of reference genes used to normalize real-time quantitative RT-PCR data

Suitable reference genes for correct quantification of reverse transcription PCR (qRT-PCR) have to be constantly expressed in all samples under investigation. Thus, it is mandatory to determine expression stability of control genes before normalization. We aimed to establish optimum inducing concentrations for the prototypical enzyme and drug transporter inducer rifampicin in LS180 cells and concurrently assessed reference gene stability under rifampicin treatment. LS180 cells were treated with increasing concentrations of rifampicin (up to 200 μM), and expression of eight different reference genes and some target genes (CYP3A4, ABCB1, and ABCC1) was quantified using real-time qRT-PCR. To check whether the results can be generalized, HepG2 cells were also investigated. We demonstrated that higher concentrations of rifampicin (>50 μM) change the expression of reference genes and thus may complicate and adulterate normalization of qRT-PCR data. The results stress the need for proper validation of potential reference genes in respective cells, tissues, and particular experimental conditions. Programs like geNorm and NormFinder alone do not warrant an adequate choice of the most suitable reference gene. Scrutiny of the reference gene expression and plausibility of the data remain necessary and protect from erroneous quantification and misinterpretation of qRT-PCR data.