ArticleNaunyn-Schmiedeberg's archives of pharmacology2016
Longitudinal trends and subgroup analysis in publication patterns for preclinical data of newly approved drugs.
Article in Naunyn-Schmiedeberg's archives of pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 5 citations in OpenAlex.
- Navigating the Critical Translational Questions for Implementing FLASH in the Clinic.Seminars in radiation oncology · 2024Review
- A year in pharmacology: new drugs approved by the US Food and Drug Administration in 2021.Naunyn-Schmiedeberg's archives of pharmacology · 2022Review
- Preclinical research strategies for newly approved drugs as reflected in early publication patterns.Naunyn-Schmiedeberg's archives of pharmacology · 2016Article
- Opportunities and Challenges for Drug Development: Public-Private Partnerships, Adaptive Designs and Big Data.Frontiers in pharmacology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Having observed a large variation in the number and type of original preclinical publications for newly registered drugs, we have explored whether longitudinal trends and/or factors specific for certain drugs or their manufacturers may explain such variation. Our analysis is based on 1954 articles related to 170 newly approved drugs. The number of preclinical publications per compound declined from a median of 10.5 in 1991 to 3 in 2011. A similar trend was observed for the number of in vivo studies in general, but not in the subset of in vivo studies in animal models of disease. The percentage of compounds with studies using isolated human cells or cell lines almost doubled over time from 37 to 72%. Number of publications did not exhibit major differences between compounds intended for human versus veterinary use, therapeutic areas, small molecules versus biologicals, or innovator versus follow-up compounds; however, some companies may publish fewer studies per compound than others. However, there were qualitative differences in the types of models being used depending on the therapeutic area; specifically, compounds for use in oncology very often used isolated cells and cell lines, often from human origin. We conclude that the large variation in number and type of reported preclinical data is not easily explained. We propose that pharmaceutical companies should consistently provide a comprehensive documentation of the preclinical data they generate as part of their development programs in the public domain to enable a better understanding of the drugs they intend to market.
Indexed as
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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.