Big Data: Challenges and opportunities for clinical pharmacology.

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

5 citing papers in PubMed.

1. The new big is small: Leveraging knowledge from small trials for rare disease drug development: Blarcamesine for Rett syndrome.British journal of clinical pharmacology · 2025
   Review
2. The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.Molecular biomedicine · 2025
   Review
3. Macrolide Treatment Failure due to Drug-Drug Interactions: Real-World Evidence to Evaluate a Pharmacological Hypothesis.Pharmaceutics · 2022
   Article
4. Big Data: Challenges and opportunities for clinical pharmacology.British journal of clinical pharmacology · 2016
   Article
5. Opportunities and Challenges for Drug Development: Public-Private Partnerships, Adaptive Designs and Big Data.Frontiers in pharmacology · 2016
   Review

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.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.

Indexed as