PAVA: physiological and anatomical visual analytics for mapping of tissue-specific concentration and time-course data

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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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The authors gratefully acknowledge Rachael Brady (Duke University Visual Technology Group) for providing the opportunity to present to the academic visualization community and receive insightful feedback (see and and Dr. Shane Peterson and Dr. Elin Ulrich (US-EPA) for thorough criticism and suggestions towards the manuscript.

Author information

Correspondence to Michael-Rock Goldsmith.

Additional information


This manuscript was approved by the U.S. EPA’s National Exposure Research Laboratory for publication. However, the contents do not necessarily reflect the views and policies of the EPA and mention of trade names or commercial products does not constitute endorsement or recommendation for use. Each of the authors declares no competing interests pertaining to the present work.

Electronic supplementary material

Supporting Information. Information regarding PAVA v1.0 development and the server-side PAVA v1.0 application installation files can be obtained on the HEASD product/tools website in the “Models” section at or under the PAVA designated page ( In addition, there is product development and user forum with dialog on PAVA on the US-Environmental Protection Agency’s Environmental Science Connector ( Interested users may join to familiarize, comment, and learn about the PAVA development cycle and provide input for desired features in future releases by contacting the authors. Included in the supporting information are (i) a screen-capture video with dialog demonstrating how a PAVA animation may be generated (ii) animated gif rendering of Fig. 1 ethanol model and (iii) Fig. 4c—Male–Female differential cancer mortality time-course data animation. Below is the link to the electronic supplementary material.

Supplementary material 1 (WMV 1797 kb)

Supplementary material 1 (WMV 1797 kb)

Supplementary material 1 (GIF 487 kb)

Supplementary material 1 (GIF 395 kb)

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Goldsmith, M., Transue, T.R., Chang, D.T. et al. PAVA: physiological and anatomical visual analytics for mapping of tissue-specific concentration and time-course data. J Pharmacokinet Pharmacodyn 37, 277–287 (2010).

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  • Physiologically-annotated data
  • Dosimetry
  • Visualization
  • Visual analytics
  • Anatomical
  • Physiological
  • Server-side application
  • Model animation
  • Concentration time-course
  • Disease progression timelines
  • Model rendering
  • PBPK
  • PBTK