ArticleOncotarget2016
An appraisal of drug development timelines in the Era of precision oncology.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 34 citations in OpenAlex.
- Strategic Integration of Companion Diagnostics in Precision Oncology: Key Factors, Drug Development Timelines, and Regulatory Insights from U.S. FDA Approvals.Therapeutic innovation & regulatory science · 2026Article
- Inclusion of Older Adults in Early-Phase Cancer Clinical Trials: Safety, Efficacy and a Way Forward.Drugs & aging · 2025Review
- The role of clinical imaging in oncology drug development: progress and new challenges.The British journal of radiology · 2023Review
- Integrating Early-Stage Drug Development with Clinical Networks; Challenges and Opportunities: The City of Hope Developing Experience.Journal of clinical medicine · 2023Article
- Immuno-oncology trends: preclinical models, biomarkers, and clinical development.Journal for immunotherapy of cancer · 2022Review
- Feasibility of Randomized Controlled Trials for Cancer Drugs Approved by the Food and Drug Administration Based on Single-Arm Studies.JNCI cancer spectrum · 2021Article
- Proportion of Patients in Phase I Oncology Trials Receiving Treatments That Are Ultimately Approved.Journal of the National Cancer Institute · 2020Article
- Reimagining Global Oncology Clinical Trials for the Postpandemic Era: A Call to Arms.JCO global oncology · 2020Article
- Article
- Cell-free DNA in cancer: current insights.Cellular oncology (Dordrecht, Netherlands) · 2019Review
- Seamless Designs: Current Practice and Considerations for Early-Phase Drug Development in Oncology.Journal of the National Cancer Institute · 2019Review
- Lessons From the Development of the Immune Checkpoint Inhibitors in Oncology.Integrative cancer therapies · 2018Review
- Analysis of Drug Development Paradigms for Immune Checkpoint Inhibitors.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The effects of incorporating a biomarker-based (personalized or precision) selection strategy on drug development timelines for new oncology drugs merit investigation. Here we accessed documents from the Food and Drug Administration (FDA) database for anticancer agents approved between 09/1998 and 07/2014 to compare drugs developed with and without a personalized strategy. Sixty-three drugs were included (28 [44%] personalized and 35 [56%] non-personalized). No differences in access to FDA-expedited programs were observed between personalized and non-personalized drugs. A personalized approach for drug development was associated with faster clinical development (Investigational New Drug [IND] to New Drug Application [NDA] submission; median = 58.8 months [95% CI 53.8-81.8] vs. 93.5 months [95% CI 73.9-112.9], P =.001), but a similar approval time (NDA submission to approval; median=6.0 months [95% CI 5.5-8.4] vs. 6.1 months [95% CI 5.9-8.3], P = .756) compared to a non-personalized strategy. In the multivariate model, class of drug stratified by personalized status (targeted personalized vs. targeted non-personalized vs. cytotoxic) was the only independent factor associated with faster total time of clinical drug development (clinical plus approval phase, median = 64.6 vs 87.1 vs. 112.7 months [cytotoxic], P = .038). Response rates (RR) in early trials were positively correlated with RR in registration trials (r = 0.63, P = <.001), and inversely associated with total time of drug development (r = -0.29, P = .049). In conclusion, targeted agents were developed faster than cytotoxic agents. Shorter times to approval were associated, in multivariate analysis, with a biomarker-based clinical development strategy.
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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.