ReviewTherapeutic innovation & regulatory science2025
Focusing on First Cycle Approval in ANDA Submission: Understanding Common Deficiencies & Case Study Insights.
Review in Therapeutic innovation & regulatory science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
The trial behind it
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveAchieving first-cycle approval in Abbreviated New Drug Applications (ANDAs) is a critical goal in the generic drug industry, as it enables faster market entry. This study covers common areas of deficiency within ANDA submissions that often lead to delays and multiple review cycles. This review also delves into FDA initiatives aimed at improving first-cycle approval rates and case study analysis that assess deficiencies impact on approval timelines.
methodA literature-based analysis was conducted, reviewed industry reports, regulatory guidelines, and published articles available on various databases to identify trends in ANDA deficiencies.
resultIdentifies key areas where applicants frequently fall short, such as incomplete data submissions, inadequate manufacturing, labelling and DMF requirements, and insufficient bioequivalence studies.
conclusionOverall, it provides valuable insights and practical guidance for generic drug developers to refine their submissions, aiming for higher first-cycle approval success in alignment with FDA standards.
Indexed as
Identifiers
39922964What OpenQuestion holds
Registered trials
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.