Performance of Multiple-Batch Approaches to Pharmacokinetic Bioequivalence Testing for Orally Inhaled Drug Products with Batch-to-Batch Variability

Abstract

Batch-to-batch pharmacokinetic (PK) variability of orally inhaled drug products has been documented and can render single-batch PK bioequivalence (BE) studies unreliable; results from one batch may not be consistent with a repeated study using a different batch, yet the goal of PK BE is to deliver a product comparison that is interpretable beyond the specific batches used in the study. We characterized four multiple-batch PK BE approaches to improve outcome reliability without increasing the number of clinical study participants. Three approaches include multiple batches directly in the PK BE study with batch identity either excluded from the statistical model (“Superbatch”) or included as a fixed or random effect (“Fixed Batch Effect,” “Random Batch Effect”). A fourth approach uses a bio-predictive in vitro test to screen candidate batches, bringing the median batch of each product into the PK BE study (“Targeted Batch”). Three of these approaches (Fixed Batch Effect, Superbatch, Targeted Batch) continue the single-batch PK BE convention in which uncertainty in the Test/Reference ratio estimate due to batch sampling is omitted from the Test/Reference confidence interval. All three of these approaches provided higher power to correctly identify true bioequivalence than the standard single-batch approach with no increase in clinical burden. False equivalence (type I) error was inflated above the expected 5% level, but multiple batches controlled type I error better than a single batch. The Random Batch Effect approach restored 5% type I error, but had low power for small (e.g., <8) batch sample sizes using standard [0.8000, 1.2500] bioequivalence limits.

Sensitivity Analysis and Uncertainty Quantification of Nanoparticle Deposition from Tongue Morphological Variations

“…First, only one original mouth-throat model was used to generate variants of the tongue and glottis. A large cohort of patient-specific, mouth-throat models can further verify or amend our understanding of the geometrical effect of orally inhaled medication dosimetry as well as the confidence level regarding the intersubject variability in device or medication bioequivalence (BE) [ 42 , 43 , 44 , 45 , 46 ]. Second, tidal breathing specific to the device and patient should be used to more accurately simulate the drug disposition distributions, even though steady flows have been shown to generate deposition distributions similar to those under corresponding tidal breathing conditions [ 47 , 48 , 49 ].…”

A new method for investigating bioequivalence of inhaled formulations: A pilot study on salbutamol

“…Visits were arranged considering a washout period of 7–10 days. To avoid batch variations of MDIs ( 31 , 32 ), the same two inhalers used in APSD analysis were administered to the volunteers. Immediately before each experiment, the inhaler was shaken for 15 s. In order to achieve drug concentrations well within the quantification range of the analytical technique, two actuations, 1 minute apart, were done by subjects.…”