GraphPad Prism Software
Past New Requirement Updated
- Agency
-
National Institutes of Health
Department of Health and Human Services
- Solicitation expected
- Estimated value
- $25,000 to $250,000
- Set-aside
- Total Small Business
Forecast facts
- Anticipated award
- NAICS code
- 541519 Other Computer Related Services
- Points of contact
-
- Adam Burkholder adam.burkholder@nih.gov
- Kimesha Leake kimesha.leake@nih.gov
Forecast details come from HHS's procurement forecast. Agencies' dates and values are estimates.
About this forecast
The National Institutes of Health's NIEHS Office of Scientific Computing plans to procure renewal of GraphPad Prism visualization software as a new requirement set aside for total small business, with an estimated solicitation release date of 2026-08-01 and an estimated award date of 2026-09-01. The software lets NIEHS intramural researchers analyze data and generate publication-quality plots and figures, and it has been used broadly across the Institute for many years. Transitioning to another tool would severely disrupt ongoing experimental work and manuscript authoring, because producing comparable statistical analyses and figures would require staff to learn R or Python and complex add-on packages.
The estimated award value range is $25,000 to $250,000 under NAICS 541519, Other Computer Related Services. Points of contact are Kimesha Leake, Contracting Officer, at kimesha.leake@nih.gov, and Adam Burkholder, at adam.burkholder@nih.gov.
Forecast text
The NIEHS Office of Scientific Computing requires renewal of licenses for GraphPad Prism Visualization Software. This tool is utilized directly by intramural researchers at NIEHS to analyze their data and generate publication-quality plots and figures. GraphPad Prism has been in use at NIEHS for many years and is utilized broadly throughout the Institute. NIEHS research staff rely on GraphPad as a user-friendly analysis and visualization environment. Transition to another tool will severely disrupt ongoing experimental work and authoring of manuscripts - in many cases the learning curve to produce similar quality statistical analyses and figures will be extremely high, requiring staff to become familiar with scripting languages such as R or Python and additionally learn to apply highly complex add-on packages within these environments.
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