ArticleJournal of pharmacokinetics and pharmacodynamics2010
PAVA: physiological and anatomical visual analytics for mapping of tissue-specific concentration and time-course data.
Article in Journal of pharmacokinetics and pharmacodynamics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 11 citations in OpenAlex.
- Obstetric anaesthesia practice: Dashboard as a dynamic audit tool.Indian journal of anaesthesia · 2018Review
- A review of analytics and clinical informatics in health care.Journal of medical systems · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We describe the development and implementation of a Physiological and Anatomical Visual Analytics tool (PAVA), a web browser-based application, used to visualize experimental/simulated chemical time-course data (dosimetry), epidemiological data and Physiologically-Annotated Data (PAD). Using continuous color mapping scheme both spatial (organ shape and location) and temporal (time-course/kinetics) data was cast onto an abstract, layered, 2D visual representation of the human anatomy and physiology. This approach is aligned with the compartment-level of detail afforded by Physiologically-Based Pharmacokinetic (PBPK) modeling of chemical disposition. In this tutorial we provide several illustrative examples of how PAVA may be applied: (1) visualization of multiple organ/tissue simulated dosimetry of a previously published oral exposure route ethanol PBPK model, (2) visualization of PAD such as organ-specific disease time-lines or (3) tissue-specific mRNA expression-level profiles (e.g. phase I/II metabolic enzymes and nuclear receptors) to draw much needed molecular biological conclusions at organ-level resolution conducive to model development. Furthermore, discussion is raised on how graphical representations of PBPK models, and the use of PAVA more generally to visualize PAD, can be of benefit. We believe this novel platform-independent tool for visualizing PAD on physiologically-relevant representations of human anatomy will become a valuable visual analytic addition to the tool-kits of modern exposure scientists, computational biologists, toxicologists, biochemists, molecular biologists, epidemiologists and pathologists alike in visually translating, representing and mining complex PAD relationships required to understand systems biology or manage chemical risk.
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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.