Impact of hepatic and renal impairment on the pharmacokinetics and tolerability of eliglustat therapy for Gaucher disease type 1

Dose Optimization Informed by PBPK Modeling: State-of-the Art and Future

Model-informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically-based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug-drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials.

Design and conduct considerations for studies in patients with hepatic impairment

Despite the liver being the primary site for clearance of xenobiotics utilizing a myriad of mechanisms ranging from cytochrome P450 enzyme pathways, glucuronidation, and biliary excretion, there is a dearth of information available as to how the severity of hepatic impairment (HI) can alter drug absorption and disposition (i.e., pharmacokinetics [PK]) as well as their efficacy and safety or pharmacodynamics (PD). In general, regulatory agencies recommend conducting PK studies in subjects with HI when hepatic metabolism/excretion accounts for more than 20% of drug elimination or if the drug has a narrow therapeutic range. In this tutorial, we provide an overview of the global regulatory landscape, clinical measures for hepatic function assessment, methods to stage HI severity, and consequently the impact on labeling. In addition, we provide an in-depth practical guidance for designing and conducting clinical trials for patients with HI and on the application of modeling and simulation strategies in lieu of dedicated trials for dosing recommendations in patients with HI.

Recommendations for oral treatment for adult patients with type 1 Gaucher disease

This work is a review of the scientific evidence on the oral treatment of adult patients with Gaucher disease type 1 (GD1) with a clinical guideline format according to the Agree II regulations. It describes the main differences between the two oral treatments currently available for treating this disease (miglustat and eliglustat). This review reminds us that the criteria for starting oral treatment in patients with GD1 must be assessed individually. Although miglustat and eliglustat are both glucosylceramide synthase (GCS) enzyme inhibitors, they have different mechanisms of action and pharmacological properties and should never be considered equivalent. Miglustat is indicated in patients with non-severe GD1 who cannot receive other first-line treatments, while eliglustat is indicated as first-line treatment for patients with GD1 of any severity without the need for prior stabilization with enzyme replacement therapy (ERT). It is important to emphasize that in order to start treatment with eliglustat, we must know the CYP2D6 metabolic phenotype and its association with drugs metabolized through the CYP2D6 and CYP3A4 cytochromes-or alternatively those that use P-Glycoprotein must be evaluated on an individual basis. During pregnancy, the use of eliglustat should be avoided; only ERT can be used. Unlike miglustat, whose adverse effects have limited its use, eliglustat has not only demonstrated similar efficacy to ERT but has also been shown to improve the quality of life of patients with GD1.

Review article: time to revisit Child-Pugh score as the basis for predicting drug clearance in hepatic impairment

BACKGROUND

Prescription information for many drugs entering the market lacks dosage guidance for hepatic impairment. Dedicated studies for assessing the fate of drugs in hepatic impairment commonly stratify patients using Child-Pugh score. Child-Pugh is a prognostic clinical score with limitations in reflecting the liver's metabolic capacity.

AIMS

To demonstrate the need for better drug dosing approaches in hepatic impairment, summarise the current status, identify knowledge gaps related to drug kinetic parameters in hepatic impairment, propose solutions for predicting the liver disease impact on drug exposure and discuss barriers to dosing guidance in those patients.

METHODS

Relevant reports on dosage adjustment in hepatic impairment were analysed concerning the prediction of the impairment impact on drug kinetics using physiologically-based pharmacokinetic (PBPK) modelling.

RESULTS

PBPK models are suggested as a potential framework to understand drug clearance changes in hepatic impairment. Quantifying changes in abundance and activity of drug-metabolising enzymes and transporters, understanding the impact of shunting, and accounting for interindividual variations in drug absorption could help in extending the success of these models in hepatically-impaired populations. These variables might not correlate with Child-Pugh score as a whole. Therefore, new metabolic activity markers, imaging techniques and other scoring systems are proposed to either support or substitute Child-Pugh score.

CONCLUSIONS

Many physiological changes in hepatic impairment determining the fate of drugs do not necessarily correlate with Child-Pugh score. Quantifying these changes in individual patients is essential in future hepatic impairment studies. Further studies assessing Child-Pugh alternatives are recommended to allow better prediction of drug exposure.

Sources of Interindividual Variability

The efficacy, safety, and tolerability of drugs are dependent on numerous factors that influence their disposition. A dose that is efficacious and safe for one individual may result in sub-therapeutic or toxic blood concentrations in others. A significant source of this variability in drug response is drug metabolism, where differences in presystemic and systemic biotransformation efficiency result in variable degrees of systemic exposure (e.g., AUC, C_max, and/or C_min) following administration of a fixed dose.Interindividual differences in drug biotransformation have been studied extensively. It is recognized that both intrinsic factors (e.g., genetics, age, sex, and disease states) and extrinsic factors (e.g., diet , chemical exposures from the environment, and the microbiome) play a significant role. For drug-metabolizing enzymes, genetic variation can result in the complete absence or enhanced expression of a functional enzyme. In addition, upregulation and downregulation of gene expression, in response to an altered cellular environment, can achieve the same range of metabolic function (phenotype), but often in a less predictable and time-dependent manner. Understanding the mechanistic basis for variability in drug disposition and response is essential if we are to move beyond the era of empirical, trial-and-error dose selection and into an age of personalized medicine that will improve outcomes in maintaining health and treating disease.

How a concentration-effect analysis of data from the eliglustat thorough electrocardiographic study was used to support dosing recommendations

Eliglustat is a first-line oral treatment for adults with Gaucher disease type 1 who have cytochrome P450 (CYP) 2D6 extensive, intermediate, or poor metabolizer phenotypes. Per International Conference on Harmonisation (ICH) E14 guidance, a Phase 1 thorough electrocardiographic (ECG) study was done during drug development to assess eliglustat's effects on cardiac repolarization by measuring ECG intervals in healthy adult subjects. Using data from the thorough ECG study, we performed pharmacokinetic/pharmacodynamic-ECG modeling to establish the relationship between eliglustat concentrations and their effects on ECG intervals. We then used that concentration-response relationship to predict the effects of eliglustat on each ECG interval for each CYP2D6 metabolizer phenotype (the main determinant of eliglustat exposure) and in different drug-drug interaction scenarios. These predictions, together with other exposure-related factors, contributed to the CYP2D6 phenotype-based dosing recommendations for eliglustat, including dose adjustments and contraindications when co-administered with drugs metabolized by the CYP2D6 and CYP3A pathways.