Relative Induction Score Research Articles

Characterization of Correction Factors to Enable Assessment of Clinical Risk from In Vitro CYP3A4 Induction Data and Basic Drug-Drug Interaction Models.

Background and ObjectiveInduction of drug-metabolizing enzymes can lead to drug-drug interactions (DDIs); therefore, early assessment is often conducted. Previous reports focused on true positive cytochrome P450 3A (CYP3A) inducers leaving a gap in translation for in vitro inducers which do not manifest in clinical induction. The goal herein was to expand the in vitro induction dataset by including true negative clinical inducers to identify a correction factor to basic DDI models, which reduces false positives without impacting false negatives.MethodsTrue negative clinical inducers were identified through a literature search, in vitro induction parameters were generated in three human hepatocyte donors, and the performance of basic induction models proposed by regulatory agencies, concentration producing twofold induction (F2), basic static model (R3) and relative induction score (RIS), was used to characterize clinical induction risk.ResultsThe data demonstrated the importance of correcting for in vitro binding and metabolism to derive induction parameters. The aggregate analysis indicates that the RIS with a positive cut-off of < 0.7-fold area under the curve ratio (AUCR) provides the best quantitative prediction. Additionally, correction factors of ten and two times the unbound peak plasma concentration at steady state (Cmax,ss,u) can be confidently used to identify true positive inducers when referenced against the concentration resulting in twofold increase in messenger ribonucleic acid (mRNA) or using the R3 equation, respectively.ConclusionsThese iterative improvements, which reduce the number of false positives, could aid regulatory recommendations and limit unnecessary clinical explorations into CYP3A induction.Graphical abstract Supplementary InformationThe online version contains supplementary material available at 10.1007/s13318-022-00763-y.

Evaluation of Methods to Assess CYP3A Induction Risk in Clinical Practice Using in Vitro Induction Parameters.

Established guidelines have recommended a number of methods based on in vitro data to assess the CYP3A induction risk of new chemical entities in clinical practice. In this study, we evaluated the predictability of various assessment methods. We collected in vitro parameters from a variety of literature that includes data on 19 batches of hepatocytes. Clinical CYP3A induction was predicted using 3 direct approaches-the fold-change, basic model, and mechanistic static models-as well as 5 correlation approaches, including the relative induction score (RIS) and the relative factor (RF) method. These predictions were then compared with data from 30 clinical inductions. Collected in vitro parameters varied greatly between hepatocyte batches. Direct assessment methods using fixed cut-off values provided a lot of false predictions due to hepatocyte variability, which can overlook induction risk or lead to needless clinical drug-drug interaction (DDI) studies. On the other hand, correlation methods with the cut-off values set for each batch of hepatocytes accurately predicted the induction risk. Among these, the AUCu/inducer concentrations for half the maximum induction (EC50) and the RF methods which use the area under the curve (AUC) of the unbound inducers for calculating induction potential showed an especially good correlation with clinical induction. Correlation methods were better at predicting clinical induction risk than the other methods, regardless of hepatocyte variability. The AUCu/EC50 and the RF methods in particular had a small number of false predictions, and can therefore be used to assess induction risk along with the other correlation methods recommended in guidelines.

Evaluation of a pre-constructed relative induction score (RIS) curve for prediction of CYP3A4 induction response in vivo

Evaluation of a pre-constructed relative induction score (RIS) curve for prediction of CYP3A4 induction response in vivo

A Novel strategy for CYP3A4 Induction screening in drug discovery: use of heparg cells and simplified relative induction score method

A Novel strategy for CYP3A4 Induction screening in drug discovery: use of heparg cells and simplified relative induction score method

Quantitative Prediction of CYP3A4 Induction: Impact of Measured, Free, and Intracellular Perpetrator Concentrations from Human Hepatocyte Induction Studies on Drug-Drug Interaction Predictions.

Typically, concentration-response curves are based upon nominal inducer concentrations for in-vitro-to-in-vivo extrapolation of CYP3A4 induction. The limitation of this practice is that it assumes the hepatocyte culture model is a static system. We assessed whether correcting for: 1) changes in perpetrator concentration in the induction medium during the incubation period, 2) perpetrator binding to proteins in the induction medium, and 3) nonspecific binding of perpetrator can improve the accuracy of CYP3A4 induction predictions. Of the seven compounds used in this evaluation, significant parent loss and nonspecific binding were observed for rifampicin (29.3-38.3%), pioglitazone (64.3-78.6%), and rosiglitazone (57.1-75.5%). As a result, the free measured EC50 values (EC50u) of pioglitazone, rosiglitazone, and rifampicin were significantly lower than the nominal EC50 values. In general, the accuracy of the induction predictions, using multiple static models, improved when corrections were made for measured medium concentrations, medium protein binding, and nonspecific binding of the perpetrator, as evidenced by 18-29% reductions in the root mean square error. The relative induction score model performed better than the basic static and mechanistic static models, resulting in lower prediction error and no false-positive or false-negative predictions. However, even when the EC50u value was used, the induction prediction for bosentan, which is a substrate of organic anion transporter proteins, was overpredicted by approximately 2-fold. Accounting for the ratio of unbound intracellular concentrations to unbound medium concentrations (Kpuu,in vitro) (0.5-7.5) and the predicted multiple-dose Kpuu,in vivo (0.6) for bosentan resulted in induction predictions within 35% of the observed interaction.

Evaluation of a Novel Renewable Hepatic Cell Model for Prediction of Clinical CYP3A4 Induction Using a Correlation-Based Relative Induction Score Approach.

Metabolism enzyme induction-mediated drug-drug interactions need to be carefully characterized in vitro for drug candidates to predict in vivo safety risk and therapeutic efficiency. Currently, both the Food and Drug Administration and European Medicines Agency recommend using primary human hepatocytes as the gold standard in vitro test system for studying the induction potential of candidate drugs on cytochrome P450 (CYP), CYP3A4, CYP1A2, and CYP2B6. However, primary human hepatocytes are known to bear inherent limitations such as limited supply and large lot-to-lot variations, which result in an experimental burden to qualify new lots. To overcome these shortcomings, a renewable source of human hepatocytes (i.e., Corning HepatoCells) was developed from primary human hepatocytes and was evaluated for in vitro CYP3A4 induction using methods well established by the pharmaceutical industry. HepatoCells have shown mature hepatocyte-like morphology and demonstrated primary hepatocyte-like response to prototypical inducers of all three CYP enzymes with excellent consistency. Importantly, HepatoCells retain a phenobarbital-responsive nuclear translocation of human constitutive androstane receptor from the cytoplasm, characteristic to primary hepatocytes. To validate HepatoCells as a useful tool to predict potential clinical relevant CYP3A4 induction, we tested three different lots of HepatoCells with a group of clinical strong, moderate/weak CYP3A4 inducers, and noninducers. A relative induction score calibration curve-based approach was used for prediction. HepatoCells showed accurate prediction comparable to primary human hepatocytes. Together, these results demonstrate that Corning HepatoCells is a reliable in vitro model for drug-drug interaction studies during the early phase of drug testing.

Evaluation of CYP2B6 Induction and Prediction of Clinical Drug-Drug Interactions: Considerations from the IQ Consortium Induction Working Group-An Industry Perspective.

Drug-drug interactions (DDIs) due to CYP2B6 induction have recently gained prominence and clinical induction risk assessment is recommended by regulatory agencies. This work aimed to evaluate the potency of CYP2B6 versus CYP3A4 induction in vitro and from clinical studies and to assess the predictability of efavirenz versus bupropion as clinical probe substrates of CYP2B6 induction. The analysis indicates that the magnitude of CYP3A4 induction was higher than CYP2B6 both in vitro and in vivo. The magnitude of DDIs caused by induction could not be predicted for bupropion with static or dynamic models. On the other hand, the relative induction score, net effect, and physiologically based pharmacokinetics SimCYP models using efavirenz resulted in improved DDI predictions. Although bupropion and efavirenz have been used and are recommended by regulatory agencies as clinical CYP2B6 probe substrates for DDI studies, CYP3A4 contributes to the metabolism of both probes and is induced by all reference CYP2B6 inducers. Therefore, caution must be taken when interpreting clinical induction results because of the lack of selectivity of these probes. Although in vitro-in vivo extrapolation for efavirenz performed better than bupropion, interpretation of the clinical change in exposure is confounded by the coinduction of CYP2B6 and CYP3A4, as well as the increased contribution of CYP3A4 to efavirenz metabolism under induced conditions. Current methods and probe substrates preclude accurate prediction of CYP2B6 induction. Identification of a sensitive and selective clinical substrate for CYP2B6 (fraction metabolized > 0.9) is needed to improve in vitro-in vivo extrapolation for characterizing the potential for CYP2B6-mediated DDIs. Alternative strategies and a framework for evaluating the CYP2B6 induction risk are proposed.

Applicability of second-generation upcyte® human hepatocytes for use in CYP inhibition and induction studies.

Human upcyte® hepatocytes are proliferating hepatocytes that retain many characteristics of primary human hepatocytes. We conducted a comprehensive evaluation of the application of second-generation upcyte® hepatocytes from four donors for inhibition and induction assays using a selection of reference inhibitors and inducers. CYP1A2, CYP2B6, CYP2C9, and CYP3A4 were reproducibly inhibited in a concentration-dependent manner and the calculated IC50 values for each compound correctly classified them as potent inhibitors. Upcyte® hepatocytes were responsive to prototypical CYP1A2, CYP2B6, CYP2C9, and CYP3A4 inducers, confirming that they have functional AhR-, CAR-, and PXR-mediated CYP regulation. A panel of 11 inducers classified as potent, moderate or noninducers of CYP3A4 and CYP2B6 were tested. There was a good fit of data from upcyte® hepatocytes to three different predictive models for CYP3A4 induction, namely the Relative Induction Score (RIS), AUCu/F2, and Cmax,u/Ind50. In addition, PXR (rifampicin) and CAR-selective (carbamazepine and phenytoin) inducers of CYP3A4 and CYP2B6 induction, respectively, were demonstrated. In conclusion, these data support the use of second-generation upcyte® hepatocytes for CYP inhibition and induction assays. Under the culture conditions used, these cells expressed CYP activities that were equivalent to or higher than those measured in primary human hepatocyte cultures, which could be inhibited or induced by prototypical CYP inhibitors and inducers, respectively. Moreover, they can be used to predict in vivo CYP3A4 induction potential using three prediction models. Bulk availability of cells from multiple donors makes upcyte® hepatocytes suitable for DDI screening, as well as more in-depth mechanistic investigations.

Evaluation of calibration curve-based approaches to predict clinical inducers and noninducers of CYP3A4 with plated human hepatocytes.

Cytochrome P450 (P450) induction is often considered a liability in drug development. Using calibration curve-based approaches, we assessed the induction parameters R3 (a term indicating the amount of P450 induction in the liver, expressed as a ratio between 0 and 1), relative induction score, Cmax/EC50, and area under the curve (AUC)/F2 (the concentration causing 2-fold increase from baseline of the dose-response curve), derived from concentration-response curves of CYP3A4 mRNA and enzyme activity data in vitro, as predictors of CYP3A4 induction potential in vivo. Plated cryopreserved human hepatocytes from three donors were treated with 20 test compounds, including several clinical inducers and noninducers of CYP3A4. After the 2-day treatment, CYP3A4 mRNA levels and testosterone 6β-hydroxylase activity were determined by real-time reverse transcription polymerase chain reaction and liquid chromatography-tandem mass spectrometry analysis, respectively. Our results demonstrated a strong and predictive relationship between the extent of midazolam AUC change in humans and the various parameters calculated from both CYP3A4 mRNA and enzyme activity. The relationships exhibited with non-midazolam in vivo probes, in aggregate, were unsatisfactory. In general, the models yielded better fits when unbound rather than total plasma Cmax was used to calculate the induction parameters, as evidenced by higher R(2) and lower root mean square error (RMSE) and geometric mean fold error. With midazolam, the R3 cut-off value of 0.9, as suggested by US Food and Drug Administration guidance, effectively categorized strong inducers but was less effective in classifying midrange or weak inducers. This study supports the use of calibration curves generated from in vitro mRNA induction response curves to predict CYP3A4 induction potential in human. With the caveat that most compounds evaluated here were not strong inhibitors of enzyme activity, testosterone 6β-hydroxylase activity was also demonstrated to be a strong predictor of CYP3A4 induction potential in this assay model.

Evaluation of Various Static and Dynamic Modeling Methods to Predict Clinical CYP3A Induction Using In Vitro CYP3A4 mRNA Induction Data

Several drug-drug interaction (DDI) prediction models were evaluated for their ability to identify drugs with cytochrome P450 (CYP)3A induction liability based on in vitro mRNA data. The drug interaction magnitudes of CYP3A substrates from 28 clinical trials were predicted using (i) correlation approaches (ratio of the in vivo peak plasma concentration (Cmax) to in vitro half-maximal effective concentration (EC50); and relative induction score), (ii) a basic static model (calculated R3 value), (iii) a mechanistic static model (net effect), and (iv) mechanistic dynamic (physiologically based pharmacokinetic) modeling. All models performed with high fidelity and predicted few false negatives or false positives. The correlation approaches and basic static model resulted in no false negatives when total Cmax was incorporated; these models may be sufficient to conservatively identify clinical CYP3A induction liability. Mechanistic models that include CYP inactivation in addition to induction resulted in DDI predictions with less accuracy, likely due to an overprediction of the inactivation effect.

Utility of DPX2 Cells for Predicting CYP3A Induction-Mediated Drug-Drug Interactions and Associated Structure-Activity Relationships

The increase in cytochrome P450 (P450) enzyme activity noted upon exposure to therapeutics can elicit marked drug-drug interactions (DDIs) that may ultimately result in poor clinical outcome or adverse drug effects. As such, in vitro model systems that can rapidly and accurately determine whether potential therapeutics activate the human pregnane X receptor (PXR) and thus induce CYP3A P450 levels are highly sought after tools for drug discovery. To that end, we assessed whether DPX2 cells, a HepG2-derived cell line stably integrated with a PXR expression vector plus a luciferase reporter, could detect agents that not only cause PXR activation/CYP3A induction but also elicit clinical DDIs. All 20 clinical inducers and 9 of 15 clinical noninducers examined activated PXR in DPX2 cells (E(max) > 8-fold), although activation parameters obtained with the noninducers were not predictive of DDI. The relative induction score, calculated by combining PXR activation parameters (EC(50) and E(max)) in DPX2 cells for seven inducers plus four noninducers with their efficacious total plasma concentrations, strongly correlated (R(2) = 0.90) with the magnitude of induction of midazolam clearance. Thus, the DPX cell-based PXR activation system is not only capable of distinguishing potential inducers in a high-throughput manner but can also differentiate among compounds in predicting the magnitude of induction-mediated DDIs, providing a means for structure-activity relationship screening during discovery and development.

Generation of proliferating human hepatocytes using upcyte® technology: characterisation and applications in induction and cytotoxicity assays

We have developed a novel technique which causes primary human hepatocytes to proliferate by transducing them with genes that upregulate their proliferation.Upcyte® hepatocytes did not form colonies in soft agar and are not immortalised anchorage-independent cells. Confluent cultures expressed liver-specific proteins, produced urea and stored glycogen.CYP activities were low but similar to that in 5-day cultures of primary human hepatocytes. CYP1A2 and CYP3A4 were inducible; moreover, upcyte® hepatocytes predicted the in vivo induction potencies of known CYP3A4 inducers using the “relative induction score” prediction model. Placing cells into 3D culture increased their basal CYP2B6 and CYP3A4 basal activities and induction responses.Phase 2 activities (UGTs, SULTs and GSTs) were comparable to activities in freshly isolated hepatocytes.Upcyte® hepatocytes were markedly more sensitive to the hepatotoxin, α-amanitin, than HepG2 cells, indicating functional OATP1B3 uptake. The cytotoxicity of aflatoxin B1, was decreased in upcyte® hepatocytes by co-incubation with the CYP3A4 inhibitor, ketoconazole. Upcyte® hepatocytes also differentiated between ten hepatotoxic and eight non-hepatotoxic compounds.In conclusion, upcyte® hepatocyte cultures have a differentiated phenotype and exhibit functional phase 1 and 2 activities. These data support the use of upcyte® hepatocytes for CYP induction and cytotoxicity screening.

The Use of HepaRG and Human Hepatocyte Data in Predicting CYP Induction Drug-Drug Interactions via Static Equation and Dynamic Mechanistic Modelling Approaches

The method of predicting CYP induction drug-drug interactions (DDIs) from a relative induction score (RIS) calibration has been developed to provide a novel model facilitating predictions for any CYP-inducer substrate combination by inclusion of parameters such as the fraction of hepatic clearance mediated by a specific CYP and fraction of the dose escaping intestinal extraction. In vitro HepaRG CYP3A4 induction data were used as a basis for the approach and a large number of DDIs were well predicted. Primary human hepatocyte data were also used to make predictions, using the HepaRG calibration as a foundation. Similar predictive accuracy suggests that HepaRG and primary hepatocyte data can be used inter-changeably within the same laboratory. A comparison of this 'indirect' calibration method with a direct in vitro-in vivo scaling approach was made and investigations undertaken to define the most appropriate in vivo inducer concentration to use. Additionally, a reasonably effective prediction model based on F(2) (the concentration of inducer taken to increase the CYP mRNA 2-fold above background) was established. An accurate prediction for the CYP1A2-dependent omeprazole-caffeine interaction was also made, demonstrating that the methods are useful for the evaluation of DDIs from induction involving mechanisms other than PXR activation. Finally, a dynamic mechanistic model accounting for the simultaneous influence of CYP induction and reversible and irreversible CYP inhibition in both the liver and intestine was written to provide a prediction of the overall DDI when several interactions occur concurrently. The rationale for using the various models described, alongside commercially available prediction tools, at various stages of the drug discovery process is described.

PREDICTION OF DRUG-DRUG INTERACTIONS FROM IN VITRO INDUCTION DATA

Cytochrome P450 induction-mediated drug-drug interaction (DDI) is one of the major concerns in clinical practice and for the pharmaceutical industry. Previously, a novel approach [the relative induction score (RIS)] was developed using the Fa2N-4 immortalized human hepatocyte line and proposed as a tool for predicting magnitude of clinical DDIs caused by induction of CYP3A. The approach is based on combining in vitro induction parameters (EC(50) and E(max)) with the efficacious free plasma concentrations to calculate a relative induction score, which is correlated to the magnitude of clinical DDI for midazolam or ethinyl estradiol. To expand the applicability of the RIS model, we have measured induction caused by ten drugs in two different lots of human cryopreserved hepatocytes and correlated the data to clinical DDIs using the RIS. The results demonstrated that, as with Fa2N-4 hepatocytes, sigmoidal relationships can be derived between RIS and magnitude of induction of midazolam and ethinyl estradiol clearance in cryopreserved human hepatocytes. This study demonstrates the general applicability of the relative induction score approach using the human cryopreserved hepatocyte model to predict clinical DDI.

Use of Immortalized Human Hepatocytes to Predict the Magnitude of Clinical Drug-Drug Interactions Caused by CYP3A4 Induction

Cytochrome P4503A4 (CYP3A4) is the principal drug-metabolizing enzyme in human liver. Drug-drug interactions (DDIs) caused by induction of CYP3A4 can result in decreased exposure to coadministered drugs, with potential loss of efficacy. Immortalized hepatocytes (Fa2N-4 cells) have been proposed as a tool to identify CYP3A4 inducers. The purpose of the current studies was to characterize the effect of known inducers on CYP3A4 in Fa2N-4 cells, and to determine whether these in vitro data could reliably project the magnitude of DDIs caused by induction. Twenty-four compounds were chosen for these studies, based on previously published data using primary human hepatocytes. Eighteen compounds had been shown to be positive for induction, and six compounds had been shown to be negative for induction. In Fa2N-4 cells, all 18 positive controls produced greater than 2-fold maximal CYP3A4 induction, and all 6 negative controls produced less than 1.5-fold maximal CYP3A4 induction. Subsequent studies were conducted to determine the relationship between in vitro induction data and in vivo induction response. The approach was to relate in vitro induction data (E(max) and EC(50) values) with efficacious free plasma concentrations to calculate a relative induction score. This score was then correlated with decreases in area under the plasma concentration versus time curve values for coadministered CYP3A4 object drugs (midazolam or ethinylestradiol) from previously published clinical DDI studies. Excellent correlations (r(2) values >0.92) were obtained, suggesting that Fa2N-4 cells can be used for identification of inducers as well as prediction of the magnitude of clinical DDIs.