Evidence map›Paper›PMID 34410557›Full record

ArticleAAPS PharmSciTech2021

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

Elise Burmeister Getz, Kevin J Carroll, J David Christopher, Beth Morgan, Scott Haughie, Alessandro Cavecchi, Christopher Wiggenhorn, Hayden Beresford, Helen Strickland, Svetlana Lyapustina

Abstract read
In one paragraph

Article in AAPS PharmSciTech, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. A new method for investigating bioequivalence of inhaled formulations: A pilot study on salbutamol.Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Elise Burmeister GetzClinical Pharmacology, Sandoz Inc., 5959 Horton Street, Emeryville, California, 94608, USA. Elise.Burmeister-Getz@novartis.com.ORCID http://orcid.org/0000-0003-2716-2088
Kevin J CarrollKJC Statistics Limited, Cheshire, UK.
J David ChristopherMerck & Co., Inc., West Point, Pennsylvania, USA.
Beth MorganInhaled Product Development, AstraZeneca, Durham, North Carolina, USA.
Scott HaughieBiometrics-Global Clinical Operations, Viatris/Mylan Pharma UK Ltd., Sandwich, Kent, UK.
Alessandro CavecchiCMC-Quality Control & Product Development, Chiesi Farmaceutici S.p.A., Parma, Italy.
Christopher WiggenhornResearch & Development, Kindeva Drug Delivery, St Paul, Minnesota, USA.
Hayden BeresfordFormulation Development, Kindeva Drug Delivery, Loughborough, UK.
Helen StricklandManufacturing Science & Engineering, GlaxoSmithKline, Zebulon, North Carolina, USA.
Svetlana LyapustinaPharmaceutical Consortia Management Team, Faegre Drinker Biddle & Reath LLP, Washington, DC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Models, StatisticalPharmaceutical PreparationsTherapeutic EquivalencyHumansReproducibility of ResultsPharmaceutical Preparationsbatch-to-batch variabilitybioequivalencemultiple-batchpharmacokinetictype I error

Identifiers

PMID34410557
PMCPMC8376725

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.