Pharmacokinetic similarity of biologics: analysis using nonlinear mixed-effects modeling

Model-Based Bioequivalence Analysis to Assess and Predict the Relative Bioavailability of Valproic Acid Formulations

BACKGROUND AND OBJECTIVE

Model-based bioequivalence (MBBE) encompasses the use of nonlinear mixed effect models supporting the estimation of pharmacokinetic endpoints to assess the relative bioavailability between multi-source drug products. This application emerges as a valuable alternative to the standard non-compartmental analysis (NCA) in bioequivalence (BE) studies in which dense sampling is not possible. In this work, we aimed to assess the application of MBBE compared to traditional methods in evaluating the relative bioavailability of two formulations with different drug release properties. Additionally, we sought to predict the performance of a modified-release formulation in a multiple-dose scenario, leveraging data from a single-dose study.

METHODS

MBBE analysis was implemented to estimate the BE endpoints (90% CI for the Test/Reference geometric mean ratio, T/R GMR) in area under the concentration-time curve (AUC) and maximum concentration (Cmax) using data from a single-dose, 2-period, 2-sequence BE study performed in 14 healthy subjects between a locally developed valproic acid extended-release formulation (Test) and the brand-name delayed-release formulation (Reference).

RESULTS

Results were compared with the standard approach, revealing that MBBE analysis achieved higher discrimination between formulations for Cmax, addressing limitations of the experimental sampling design and highlighting an advantage for this model-based analysis even when rich data are available. Additionally, the bioequivalence outcome under the multiple-dose scenario was predicted through a simulation-based study for both total and unbound valproic acid concentrations, considering the impact of valproic acid saturable binding on BE conclusions.

CONCLUSIONS

The MBBE analysis was superior to the NCA approach in detecting product-related differences, overcoming limitations in the study experimental design. Predictions for the multiple-dose scenario preclude that the extended-release properties of the Test formulation would persist at steady state, resulting in lower peak-to-trough fluctuation and bioequivalent performance in terms of the extent of drug absorption. Overall, these results should discourage unnecessary experimentation in healthy subjects.

Evaluation of Truncated AUC as an Alternative Measure to Assess Pharmacokinetic Comparability in Bridging Biologic-Device Using Prefilled Syringes and Autoinjectors

Pharmacokinetic (PK) comparisons between therapeutic biologics have largely been based on the total area under the concentration-time curve (AUC) and the maximum concentration (Cmax ). For biologics with a long half-life, a PK comparability study may be long in duration and costly to conduct. The goal of this study was to evaluate whether a truncated AUC (tAUC) can be used to assess PK comparability when bridging prefilled syringe (PFS) and autoinjector (AI) treatment options for biologics with a long half-life. Fifteen biologics license applications (BLAs) were included to determine the concordance and geometric percent coefficient of variation (%CV) between tAUCs evaluated on days 7, 14, 21, and 28 and AUC evaluated to infinity (AUC0-inf ). Concordance is established if the tAUCs are comparable with AUC0-inf . Trial simulation was performed to examine the effect of the absorption rate constant (ka ) and sample size on the concordance of tAUCs. The tAUCs evaluated on day 14, 21, and 28 had 100% concordance with AUC0-inf for all 15 BLAs. The concordance of tAUC evaluated at day 7 was 87.5%. Based on the trial simulation, tAUC evaluated to day 28 post-dose can achieve high concordance (≥85%) for biologics exhibiting linear or nonlinear elimination with a ka of ≥0.1/day and with a sample size of 70 subjects per arm. tAUC appears to be a promising alternative PK measure, relative to AUC0-inf , for PK comparability assessments.

Pharmacokinetics and Pharmacodynamics of Bimagrumab (BYM338)

BACKGROUND

Bimagrumab is a human monoclonal antibody binding to the activin type II receptor with therapeutic potential in conditions of muscle wasting and obesity. This phase I study evaluated the pharmacokinetics (PK), pharmacodynamics (PD), and safety of various dose regimens of bimagrumab and routes of administration in healthy older adults.

METHODS

This was a randomized, double-blind, placebo-controlled, parallel-arm, multiple-dose study in older adult men and women (aged ≥ 70 years, body mass index [BMI] 18-34 kg/m²) with stable health and diet. The study comprised seven treatment groups (Cohorts 1-7). Participants received bimagrumab or placebo treatment every 4 weeks for three doses (Cohorts 1 [700 mg] and 2 [210 mg] intravenous infusion; Cohorts 3 [1500 mg] and 4 [525 mg] subcutaneous infusion), or every week for 12 doses (Cohorts 5 [300 mg], 6 [150 mg], and 7 [52.5 mg] subcutaneous bolus injection) and were followed up until week 20. Blood samples were collected for bimagrumab PK analysis. PD were assessed by dual energy X-ray absorptiometry to quantify the change from baseline in lean body mass (LBM) and fat body mass (FBM) compared with placebo. Safety was assessed throughout the study.

RESULTS

Eighty-four of 91 (92.3%) randomized participants (mean age 74.5 years; BMI 28.0 kg/m²) completed the study. Demographic characteristics were generally balanced across the groups. A target-mediated drug disposition profile was observed following both intravenous and subcutaneous administration. The absolute subcutaneous bioavailability was estimated at approximately 40%. LBM increased by 4-6% (1.5-2 kg) from baseline throughout the treatment period for intravenous and subcutaneous regimens, except for the 52.5 mg subcutaneous dose, which did not differ from placebo. Concurrently, there was a decrease in FBM (approximately 2-3 kg) for all intravenous and subcutaneous regimens. Bimagrumab was generally safe and well tolerated; adverse events were mostly mild to moderate in severity.

CONCLUSIONS

Dose levels of bimagrumab administered weekly subcutaneously resulted in PK profiles and PD effects comparable with monthly intravenous dosing, which supports the feasibility of the subcutaneous route of administration for bimagrumab for future clinical development.

Impact of model misspecification on model-based tests in PK studies with parallel design: real case and simulation studies

This article evaluates the performance of pharmacokinetic (PK) equivalence testing between two formulations of a drug through the Two-One Sided Tests (TOST) by a model-based approach (MB-TOST), as an alternative to the classical non-compartmental approach (NCA-TOST), for a sparse design with a few time points per subject. We focused on the impact of model misspecification and the relevance of model selection for the reference data. We first analysed PK data from phase I studies of gantenerumab, a monoclonal antibody for the treatment of Alzheimer’s disease. Using the original rich sample data, we compared MB-TOST to NCA-TOST for validation. Then, the analysis was repeated on a sparse subset of the original data with MB-TOST. This analysis inspired a simulation study with rich and sparse designs. With rich designs, we compared NCA-TOST and MB-TOST in terms of type I error and study power. With both designs, we explored the impact of misspecifying the model on the performance of MB-TOST and adding a model selection step. Using the observed data, the results of both approaches were in general concordance. MB-TOST results were robust with sparse designs when the underlying PK structural model was correctly specified. Using the simulated data with a rich design, the type I error of NCA-TOST was close to the nominal level. When using the simulated model, the type I error of MB-TOST was controlled on rich and sparse designs, but using a misspecified model led to inflated type I errors. Adding a model selection step on the reference data reduced the inflation. MB-TOST appears as a robust alternative to NCA-TOST, provided that the PK model is correctly specified and the test drug has the same PK structural model as the reference drug.

Allometric scaling of therapeutic monoclonal antibodies in preclinical and clinical settings

Constant technological advancement enabled the production of therapeutic monoclonal antibodies (mAbs) and will continue to contribute to their rapid expansion. Compared to small-molecule drugs, mAbs have favorable characteristics, but also more complex pharmacokinetics (PK), e.g., target-mediated nonlinear elimination and recycling by neonatal Fc-receptor. This review briefly discusses mAb biology, similarities and differences in PK processes across species and within human, and provides a detailed overview of allometric scaling approaches for translating mAb PK from preclinical species to human and extrapolating from adults to children. The approaches described here will remain vital in mAb drug development, although more data are needed, for example, from very young patients and mAbs with nonlinear PK, to allow for more confident conclusions and contribute to further growth of this field. Improving mAb PK predictions will facilitate better planning of (pediatric) clinical studies and enable progression toward the ultimate goal of expediting drug development.

Efficient model-based bioequivalence testing

The classical approach to analyze pharmacokinetic (PK) data in bioequivalence studies aiming to compare two different formulations is to perform noncompartmental analysis (NCA) followed by two one-sided tests (TOST). In this regard, the PK parameters area under the curve (AUC) and $C_{\max}$ are obtained for both treatment groups and their geometric mean ratios are considered. According to current guidelines by the U.S. Food and Drug Administration and the European Medicines Agency, the formulations are declared to be sufficiently similar if the $90\%$ confidence interval for these ratios falls between $0.8$ and $1.25 $. As NCA is not a reliable approach in case of sparse designs, a model-based alternative has already been proposed for the estimation of $\rm AUC$ and $C_{\max}$ using nonlinear mixed effects models. Here we propose another, more powerful test than the TOST and demonstrate its superiority through a simulation study both for NCA and model-based approaches. For products with high variability on PK parameters, this method appears to have closer type I errors to the conventionally accepted significance level of $0.05$, suggesting its potential use in situations where conventional bioequivalence analysis is not applicable.

Population pharmacokinetics of adalimumab biosimilar adalimumab-adbm and reference product in healthy subjects and patients with rheumatoid arthritis to assess pharmacokinetic similarity

AIMS

Adalimumab-adbm is a monoclonal antibody developed as a biosimilar to adalimumab (Humira, AbbVie Inc.). The key objectives of this study were using a population pharmacokinetic (PPK) approach to assess pharmacokinetic (PK) similarity between adalimumab-adbm and Humira in patients with active rheumatoid arthritis (RA), to quantify the effects of potential covariates on adalimumab PK and to assess the impact of switching treatment from Humira to adalimumab-adbm on PK.

METHODS

A PPK model was firstly developed using intensive PK data from the phase-1 study in healthy subjects (NCT02045979). PPK models were developed separately for phase-3 base study (NCT02137226) and its extension study (NCT02640612) in patients with active RA.

RESULTS

PPK models were developed for adalimumab from adalimumab-adbm and Humira treatment in healthy subjects and RA patients. Weight and anti-drug antibodies were found to be important predictors of adalimumab clearance. Adalimumab PK was similar between adalimumab-adbm and Humira. The estimated effect of Humira on clearance, relative to the adalimumab-adbm, was 1.02 (i.e., Humira has 0.02 greater clearance). Similarly, the effect of treatment arms (switching) on clearance was estimated to be 1.00 and 0.997 for Humira:Humira:BI and Humira:BI:BI arms, respectively, relative to the BI:BI:BI arm (BI refers to adalimumab-adbm) in the phase-3 extension study.

CONCLUSION

PK similarity between adalimumab-adbm and Humira in patients with active RA was demonstrated using PPK approach. Adalimumab PK was also similar when switching treatment from Humira to adalimumab-adbm at either week 24 or 48.

Performing and interpreting individual pharmacokinetic profiles in patients with Hemophilia A or B: Rationale and general considerations

OBJECTIVES

In a separate document, we have provided specific guidance on performing individual pharmacokinetic (PK) studies using limited samples in persons with hemophilia with the goal to optimize prophylaxis with clotting factor concentrates. This paper, intended for clinicians, aims to describe how to interpret and apply PK properties obtained in persons with hemophilia.

METHODS

The members of the Working Party on population PK (PopPK) of the ISTH SSC Subcommittee on Factor VIII and IX and rare bleeding disorders, together with additional hemophilia and PK experts, completed a survey and ranking exercise whereby key areas of interest in the field were identified. The group had regular web conferences to refine the manuscript's scope and structure, taking into account comments from the external feedback to the earlier document.

RESULTS

Many clinical decisions in hemophilia are based on some form of explicit or implicit PK assessment. Individual patient PK profiles can be analyzed through traditional or PopPK methods, with the latter providing the advantage of fewer samples needing to be collected on any prophylaxis regimen, and without the need the for a washout period. The most useful presentation of PK results for clinical decision making are a curve of the factor activity level over time, the time to achieve a certain activity level, or related parameters like half-life or exposure (AUC). Software platforms have been developed to deliver this information to clinicians at the point of care. Key characteristics of studies measuring average PK parameters were reviewed, outlining what makes a credible head-to-head comparison among different concentrates. Large data collections of PK and treatment outcomes currently ongoing will advance care in the future.

CONCLUSIONS

Traditionally used to compare different concentrates, PK can support tailoring of hemophilia treatment by individual profiling, which is greatly simplified by adopting a PopPK/Bayesian method and limited sampling protocol.

Application of Pharmacometric Analysis in the Design of Clinical Pharmacology Studies for Biosimilar Development

This article provides an overview of four case studies to demonstrate the utility of pharmacometric analysis in biosimilar development to help design sensitive clinical pharmacology studies for the demonstration of biosimilarity. The two major factors that determine the sensitivity of a clinical pharmacokinetic/pharmacodynamic (PK/PD) study to demonstrate biosimilarity are the size of the potential difference to be detected (signal) and the inter-subject variability (noise), both of which can be characterized and predicted using pharmacometric approaches. To maximize the chance to detect any potential difference between the proposed biosimilar and the reference drug, the dose selected for the clinical pharmacology study should fall on the steep part of the dose-response curve. Pharmacometric analysis can be used to characterize the dose-response relationship using PD- or PK/PD-linked models. The understanding of the PD endpoints in terms of dynamic range of the response and the location of the studied dose on the dose-response curve can provide strategic advantage in the trial design. To reduce the inter-subject variability (noise), pharmacometric analysis can help avoid high variability associated with low doses, and decrease variability by controlling certain covariates in the inclusion/exclusion criteria. Pharmacometric analysis also can help select or justify margins for the equivalence test of PD endpoints. Pharmacometric analysis will assume an ever-increasing role in the clinical development of biosimilar drugs, as it helps to ensure that sufficient sensitivity is built into the study design to detect potential PK and PD differences.

Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies

PURPOSE

Population pharmacokinetic analyses (PPK) have been used to establish bioequivalence for small molecules and some biologicals. We investigated whether PPK could also be useful in biosimilarity testing for monoclonal antibodies (MAbs).

METHODS

Data from a biosimilarity trial with two trastuzumab products were used to build population pharmacokinetic models. First, a combined model was developed and similarity between test and reference product was evaluated by performing a covariate analysis with trastuzumab drug product (test or reference) on all model parameters. Next, two separate models were developed, one for each drug product. The model structure and parameters were compared and evaluated for differences.

RESULTS

Drug product could not be identified as statistically significant covariate on any parameter in the combined model, and the addition of drug product as covariate did not improve the model fit. A similar structural model described both the test and reference data best. Only minor differences were found between the estimated parameters from these separate models.

CONCLUSIONS

PPK can also be used to support a biosimilarity claim for a MAb. However, in contrast to the standard non-compartmental analysis, there is less experience with a PPK approach. Here, we describe two methods of how PPK can be incorporated in biosimilarity testing for complex therapeutics.

Population Pharmacokinetic Analysis of the Oral Absorption Process and Explaining Intra-Subject Variability in Plasma Exposures of Imatinib in Healthy Volunteers

BACKGROUND AND OBJECTIVE

Imatinib mesylate is presently the first-line treatment for chronic myeloid leukemia (CML). The aim of this study was to investigate the absorption and distribution kinetics of imatinib in healthy Iranian volunteers using nonlinear mixed effects modeling (NLMEM) to assess the overall, intra- and inter-subject variabilities in pharmacokinetic parameters after oral administration.

METHODS

This analysis was based on data from 24 healthy subjects who participated in a bioequivalence study after administering a single dose of 200 mg of each formulation. Imatinib concentrations were quantified using a validated liquid chromatography method. To simultaneously describe the imatinib pharmacokinetic profiles obtained with both formulations, a population pharmacokinetic model was applied to data using SAEM algorithm implemented in MONOLIX, whilst simulations were used by numerical solving of ordinary differential equations to calculate secondary parameters in individuals for bioequivalence studies.

RESULTS

According to goodness-of-fit criteria, a two-compartment open model with sequential zero- then first-order absorption and first-order elimination was used as the structural pharmacokinetic model. Inter-individual variability (IIV) was considered for all parameters. Typical population estimates (% IIV) were fraction of the drug absorbed with a zero-order kinetic (Fr) of 0.153 (47.9 %) in period (Tk0) of 0.714 h (47.4 %), first-order absorption rate constant (k a) of 0.94 h(-1)(31.2 %), oral clearance of 19 L/h (27.9 %), central volume of distribution (V c/F) of 139 L (21.5 %), apparent peripheral volume of distribution (V p/F) of 130 L (29.7 %) and the apparent inter-compartment clearance (Q/F) of 29.6 L/h (41.8 %). Body mass index (BMI) was the only covariate found to significantly affect V p /F. The coefficient of variation for intra-individual plasma exposure (AUC0-∞) was 27.8 %.

CONCLUSIONS

Analyses using NLMEM for imatinib exhibited absorption complexities such as two input rates and medium to high intra-individual variability in drug exposure.

The use of pharmacometrics to optimize biosimilar development

Pharmacometric approaches can assist in biosimilar development by leveraging quantitative knowledge of the originator product characteristics such as dose-exposure and exposure-response information to support a targeted approach to clinical studies. The degree to which these approaches can be applied relies on the level of information known about the originator and information that supports application of the originator model to the biosimilar. A model-based approach testing the hypothesis that the biosimilar PK and/or PK/PD profile is similar to the originator in the target patient population is aligned with the central comparability exercise required for the biosimilar approval. This Commentary details the key opportunities in study design and study analysis where pharmacometrics approaches can aid biosimilar development.