Evaluation of model‐based bioequivalence approach for single sample pharmacokinetic studies

Abstract

In a traditional pharmacokinetic (PK) bioequivalence (BE) study, a two-way crossover study is conducted, PK parameters (namely the area under the timeconcentration curve [AUC] and the maximal concentration [C max ]) are obtained by noncompartmental analysis (NCA), and the BE analysis is performed using the two one-sided test (TOST) method. For ophthalmic drugs, however, only one sample of aqueous humor, in one eye, per eye can be obtained in each patient, which precludes the traditional BE analysis. To circumvent this issue, the U.S.Food and Drug Administration (FDA) has proposed an approach coupling NCA with either parametric or nonparametric bootstrap (NCA bootstrap). The modelbased TOST (MB-TOST) has previously been proposed and evaluated successfully for various settings of sparse PK BE studies. In this paper, we evaluate, via simulations, MB-TOST in the specific setting of single sample PK BE study and compare its performance to NCA bootstrap. We performed BE study simulations using a published PK model and parameter values and evaluated multiple scenarios, including study design (parallel or crossover), sampling times (5 or 10 spread across the dosing interval), and geometric mean ratio (of 0.8, 0.9, 1, and 1.25). Using the simulated structural PK model, MB-TOST performed similarly to NCA bootstrap for AUC. For C max , the latter tended to be conservative and less powerful. Our research suggests that MB-TOST may be considered as an alternative BE approach for single sample PK studies, provided that the PK model is correctly specified and the test drug has the same structural model as the reference drug. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?In bioequivalence (BE) studies for generic drug development of ophthalmic products, one sample of aqueous humor is taken at a certain timepoint per eye for measurement of drug concentration. Currently, the U.S. Food and Drug Administration (FDA) recommends a nonparametric or parametric bootstrap

Advances in quantitative methods and modeling for complex generic drugs and opportunities to hybridize learnings between innovator and generic drug developers

“…13 Lastly, and distinctive from the FDA workshop reports, are two model-based BE (MBBE) applications: an intricate and comprehensive application of PBPK modeling to ivermectin to identify factors that affect plasma exposure that may be relevant to the design of complex formulations for mass-drug administration, 14 and an evaluation of the model-based two one-sided test for a single sample PK BE study with a performance comparison to noncompartmental analysis. 15 Under the GDUFA III (2023 to 2027), utilizing QMM for complex generics to establish BE in place of clinical end point BE studies has the potential to lower development costs and accelerate access to generic drugs. A recent rise in MIE alternative BE approaches in pre-ANDA and ANDA interactions between the generic drug industry and the FDA is signaling an industry shift from MIE development to implementation; Yoon et al 5 provided a forward-looking perspective on how QMM will be pivotal to drive innovation for complex generics during this transition.…”

“…Oral generic products, which represent a large proportion of generics, but are not routinely labeled as complex, have been identified as having lingering knowledge gaps in PBPK model development, use, and validation for absorption models and food effect assessment 12 and as an alternative BE approach and tool for risk assessment and biowaiver 13 . Lastly, and distinctive from the FDA workshop reports, are two model‐based BE (MBBE) applications: an intricate and comprehensive application of PBPK modeling to ivermectin to identify factors that affect plasma exposure that may be relevant to the design of complex formulations for mass‐drug administration, 14 and an evaluation of the model‐based two one‐sided test for a single sample PK BE study with a performance comparison to noncompartmental analysis 15 …”

Model‐based bioequivalence approach for sparse pharmacokinetic bioequivalence studies: Model selection or model averaging?

“…6 MB-TOST even outperformed the non-parametric bootstrap NCA-based approach recommended by FDA for PK BE studies on ophthalmic drug products using a parallel design with only one PK sample taken per patient if the underlying PK structural model can be correctly specified. 7 However, due to under-estimation of the asymptotic standard errors (SE) on sparse data, MB-TOST showed inflated type I error rates. 6 Thus, we proposed alternative methods for SE calculation at finite distance.…”