Evidence map›Paper›PMID 36271265›Full record

ArticleThe AAPS journal2022

A Novel Bootstrapping Test for Analytical Biosimilarity.

Thomas Zahel

Open access · hybridAbstract read
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 49% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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

1 author at 1 institution in 1 country.

Thomas ZahelKörber Pharma Austria GmbH, Mariahilferstraße 88A, 1070, Vienna, Austria. Thomas.zahel@koerber.com.
EVER Neuro Pharma (Austria) · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Showing analytical similarity is key to license biosimilar products with reduced or circumvented clinical effort. Statistical procedures to assess analytical similarity of quality attributes at drug product level have been highly debated by academia, industry, and regulatory agencies. In the past, a tiered approach was recommended by regulators, consisting of equivalence tests and quality range tests. However, this approach has recently been withdrawn by FDA. New guidelines of FDA and EMA favour the usage of quality range tests. Moreover, it has recently been shown that simple range tests, such as the 3SD test, are flawed, since they do not control the agency risk of falsely declaring a non-biosimilar product as being biosimilar (Type I error). This has also been highlighted by regulators recently. In this contribution, we developed a novel bootstrapping test for assessing analytical similarity that overcomes current flaws of equivalence and range tests. The developed test shows the desired properties, that is, (i) similarity conditions can be easily defined, (ii) differences of mean and the variance between the biosimilar and the innovator can be studied simultaneously, and (iii) the Type I error of the test can be controlled at a low level, e.g. 5%, evenly along the entire similarity condition. Moreover, the test shows up to 10% higher mean power values in the similarity region compared to existing range tests that aim to control the Type I error. Hence, this test is superior to existing quality range tests and is perceived compliant with current regulatory requirements.

Indexed as

Biosimilar PharmaceuticalsResearch DesignUnited StatesUnited States Food and Drug AdministrationBiosimilar Pharmaceuticalsanalytical similaritybiosimilarbiosimilaritybootstrappingequivalence testsrange test

Identifiers

PMID36271265
OpenAlexW4307030493

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.