Recent media coverage describing the manipulation of validation data images used to promote commercial antibodies has brought critical issues of data integrity and reagent validation to the forefront.1,2 While scrutiny of product images and of the practices used to generate them is a vital component of improving research reproducibility, broad claims implying that inappropriate image manipulation is a universal practice among antibody suppliers misrepresent the market and add confusion rather than reducing it.
Significant differences exist in how suppliers operate, specifically regarding where the products they sell are actually developed, manufactured, and validated. The practice of sourcing, relabeling, and reselling antibodies is widespread across the industry. But it is by no means universal.3
How a supplier operates, and which operations and practices it prioritizes, can directly impact the integrity of its data. Unfortunately, some suppliers seem to prioritize having as broad an antibody catalog as possible, while minimizing the investment required to properly validate outsourced (or even in-house) antibodies. It is apparent that in the rush to expand catalogs, corners are being cut. This understandably erodes trust in suppliers that engage in data manipulation, but also casts a negative impression on the antibody market as a whole, with potentially serious implications for researchers who have published studies using these antibodies.
As scientists who perform research ourselves and collaborate with scientists around the world, we think all suppliers should be expected to provide:
- Rigorous In-House Testing: When licensing hybridomas or sourcing an antibody from a third party, which could be another company, a contract lab, or an academic lab, suppliers should conduct their own in-house, application-specific testing using qualified materials to ensure performance.
- Zero Data Reuse: Suppliers should not repost product data generated by third parties without disclosing the source. The images, graphs, and application data shown on product pages should reflect representative, real performance—not just cherry-picked results.
- Appropriate image editing practices: While the judicious use of image editing tools to improve presentation clarity is valid, there must be no manipulation to hide poor results. Product images should be prepared WITHOUT image cloning, paintbrush operations, duplication or masking of bands, or any other selective image operations that change the meaning of the underlying data and misrepresent the performance of an antibody.
Data integrity is not just a commercial policy for us; it is a fundamental pledge.
Scientists should be able to trust the tools they use to advance discovery. When you view product data on our website, you can be assured that the information provided is honest, accurate, and reproducible in your own lab.
Science depends on trust, and we remain dedicated to earning yours every day.
Roberto Polakiewicz, PhD
Chief Scientific Officer, Cell Signaling Technology
References
- Garisto D. More than 18,000 questionable images found in antibody catalogues of 15 companies. Nature. Published online August 25, 2026. doi:10.1038/d41586-026-02635-w
- Richardson R, David S. Problematic images in vendor antibody verification data (version 260825). Zenodo. Published online August 25, 2026. doi:10.5281/zenodo.22090940
- The antibody supply chain: why we have 13,500 antibodies, not >100,000. Cell Signaling Technology Blog. Published September 2026. Accessed September 10, 2026. https://blog.cellsignal.com/antibody-supply-chain
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