Antibody validation remains a critical yet nuanced step in ensuring experimental reproducibility. While vendors provide extensive validation data, that information is inherently limited by tested applications, protocols, and sample types. Researchers must therefore balance reliance on vendor data with thoughtful in-house validation tailored to their specific use cases.
In this Ask the Expert article, we talked to Katherine Crosby, Sr. Director, Antibody Applications & Validation at Cell Signaling Technology, about how validation data is generated, what strategies vendors use to confirm specificity, and how lot-to-lot variability is managed. We also examine when to engage technical support and how strong vendor–customer collaboration can help resolve performance issues and strengthen confidence in antibody-based experiments.
Biocompare: From a vendor perspective, what are the key strengths and limitations of the validation data you provide, and how do you recommend customers decide when that data is sufficient versus when they should still perform in‑house validation?
Katherine: “Antibody performance depends upon the protocol being utilized and can be further influenced by the types of samples being tested. A vendor cannot possibly test all applications that a researcher may use, or all permutations of a given protocol. Additionally, it is impossible for a vendor to test every possible sample type a researcher may be using. A vendor should provide sufficient data to demonstrate the specificity of an antibody in a given application, and provide the specific details of the protocol that was used. A researcher who plans to use the antibody in one or more of the same applications with a reasonably similar protocol and similar sample type should feel confident that the antibody will perform similarly in his or her hands. If, on the other hand, the researcher plans to use the antibody in an application for which the vendor has not demonstrated specificity, or use a protocol that varies considerably from the vendor's recommendation, or use a sample type for which the vendor does not provide data, it would be wise for the researcher to confirm that the antibody's performance is suitable under those specific conditions.”
Biocompare: What internal validation strategies do you prioritize to build confidence in your antibodies, and how do you communicate those details to customers?
Katherine: “We carefully test antibodies in commonly used applications, like western blot, IHC, immunocytochemistry, and flow cytometry, for example. Each application team independently assesses antibody performance and determines the antibody's specificity in that application by leveraging multiple strategies. Binary models, including knockout, for example, are widely leveraged across applications, while IHC investigates performance in multiple normal and diseased tissue models. Additional options that can be incorporated into the validation work include protein overexpression, siRNA, and treatments to induce protein modulation, such as changes in expression levels, activation state, and/or localization. Leveraging a second antibody directed against a distinct region on the target protein can also be a powerful tool. We will display the validation data for each application for which an antibody is recommended on the web, though it is often the case that supplemental data exists.”
Biocompare: How do you handle variability across batches or lots, and what guidance or documentation do you provide to help customers interpret changes in antibody performance or design experiments that remain robust despite minor lot‑to‑lot differences?
Katherine: “Recombinant monoclonal antibodies are highly consistent from batch to batch, posing virtually no risk to a researcher. Polyclonal antibodies, on the other hand, are far more likely to differ between batches. We compare each new lot of antibody to the previous lot to ensure that performance does not vary. If we were to observe a performance difference in a given application, we would remove that application from the antibody upon release of the new lot.
Biocompare: When should a customer reach out to technical support?
Katherine: “If a researcher is using an antibody in an approved application and following the recommended protocol, but not obtaining expected results, technical support should be consulted. If the application is not approved or the protocol varies considerably from what is recommended, connecting with technical support can be quite useful as well. There may be some antibody-specific nuances that can be shared, or possibly the sharing of positive controls that can help to determine if a protocol or sample type difference is contributing to the performance difference. If a researcher is obtaining results that call into question an antibody's specificity, technical support should be contacted so it can be determined if further internal testing is needed.”