Evidence map›Paper›PMID 38267593›Full record

ArticleThe AAPS journal2024

Development of Quantitative Comparative Approaches to Support Complex Generic Drug Development.

Yuqing Gong, Francis-Xavier Barretto, Yi Tsong, Youssef Mousa, Ke Ren, Darby Kozak, Meiyu Shen, Meng Hu, Liang Zhao

Abstract read
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In one paragraph

Article in The AAPS journal, 2024. 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. Review
  2. 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

9 authors.

Yuqing GongDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA.
Francis-Xavier BarrettoSwati Spentose Pvt. Ltd, Mumbai, India.
Yi TsongDivision of Biometrics VI, Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Youssef MousaDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA.
Ke RenDivision of Bioequivalence III, Office of Bioequivalence, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Darby KozakDivision of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Meiyu ShenDivision of Biometrics VI, Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Meng HuDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA. Meng.Hu@fda.hhs.gov.
Liang ZhaoDivision of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland, 20993, USA.

Funding

Center for Research on Complex GenericsU18FD007054 · FDA · UNIVERSITY OF MARYLAND BALTIMORE · PI JAMES E POLLI, Anna Schwendeman · 2020 to 2026
$6.8M
FDA HHS U18 FD007054
6 · The paper itself

Abstract

On October 27-28, 2022, the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG) hosted a virtual public workshop titled "Best Practices for Utilizing Modeling Approaches to Support Generic Product Development." This report summarizes the presentations and panel discussions for a session titled "Development of Quantitative Comparative Approaches to Support Complex Generic Drug Development." This session featured speakers and panelists from both the generic industry and the FDA who described applications of advanced quantitative approaches for generic drug development and regulatory assessment within three main topics of interest: (1) API sameness assessment for complex generics, (2) particle size distribution assessment, and (3) dissolution profile similarity comparison. The key takeaways were that the analysis of complex data poses significant challenges to the application of conventional statistical bioequivalence methods, and there are various opportunities for using data analytics approaches for developing and applying suitable equivalence assessment method.

Indexed as

Drug DevelopmentDrugs, GenericResearch DesignTherapeutic EquivalencyUnited StatesUnited States Food and Drug AdministrationDrugs, GenericAPI samenessbioequivalencecomplex generic drugdissolution profile similarityparticle size distribution

Identifiers

PMID38267593

What OpenQuestion holds

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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.