ArticleDrug design, development and therapy2025
Bibliometrics Analysis and Knowledge Mapping of Fragment-Based Drug Design Research: Trends from 2015 to 2024.
Article in Drug design, development and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis of the landscape.Human vaccines & immunotherapeutics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study systematically analyzed available literature related to fragment-based drug design (FBDD) published between 2015 and 2024 using bibliometric methods to identify research trends, hotspots, and emerging frontiers. The findings provide valuable information and a comprehensive reference for future FBDD research and drug development. Methods: The relevant literature was comprehensively searched from the Web of Science Core Collection (WOSCC) database using the keywords "Fragment-based drug design" or "FBDD", covering articles published between January 1, 2015 and November 1, 2024. A total of 1,301 papers were included. Bibliometric analysis and knowledge mapping were conducted using the RStudio's bibliometrix-biblioshiny package, CiteSpace, and VOSviewer software, assessing multiple dimensions such as journal co-occurrence, keyword density, institutional collaboration, and citation patterns. Results: The research output in FBDD revealed fluctuating growth, with an average annual growth rate of 1.42%. The United States and China lead global research with 889 and 719 publications, respectively, contributing significantly to international collaboration (34.82%). Prominent research institutions included the Center National de la Recherche Scientifique (CNRS), the University of Cambridge, and the Chinese Academy of Sciences, demonstrating strong academic influence. Key contributors such as Abell, C. Blundell, TL, and Johnson, CN, were among the top ten high-impact authors, significantly shaping the FBDD landscape through highly cited publications. Influential journals included the Conclusion: FBDD remains a dynamic field with ongoing global academic attention. Future research directions are likely to emphasize innovations in computational simulation, targeted drug screening, and molecular docking techniques, facilitating the advancement and development of novel therapeutic agents.
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What 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.