Antibodies are essential reagents that support all levels of scientific research. Used in a multitude of applications to identify, quantify, and isolate specific target biomolecules, they have recently become the focus of intense scrutiny for their contribution to the ongoing reproducibility crisis.
As awareness grows that poorly characterized antibodies are one of the reasons that many experimental results cannot be replicated, researchers expect increasingly rigorous in-house validation from antibody manufacturers.
At Cell Signaling Technology, we understand that there is no single assay that can determine the validity of an antibody. Confirming that an immuno-reagent is sufficiently specific and sensitive depends on the application and protocol being used, the type and quality of sample being analyzed, and the inherent biophysical properties of the antibody itself. To ensure our antibodies will work in your experiment, we adhere to the Hallmarks of Antibody Validation™, six complementary strategies that can be used to determine the functionality, specificity, and sensitivity of an antibody in any given assay. CST adapted the work by Uhlen, et. al., [“A Proposal for Validation of Antibodies.” Nature Methods (2016)] to build the Hallmarks of Antibody Validation, based on our decades of experience as an antibody manufacturer and our dedication to reproducible science. These include:
- Binary strategy
- Ranged strategy
- Orthogonal strategy
- Multiple antibody strategy
- Heterologous strategy
- Complementary strategies
We guarantee our antibodies by carefully tailoring the combination of validation strategies applied to each product. This means customizing our validation process according to the biological role of the target, while considering the sensitivity requirements of the downstream assay, the availability of appropriate testing models, and the relevance of each method to target investigation.
The aim of this series is to provide an overview of the Hallmarks of Antibody Validation, describing how our approach is part of a realizable solution to achieve experimental reproducibility.
