Antibodies are widely used in clinical tests, diagnostics, and life science research. Despite their widespread importance and significant investment in time and money, antibodies still lack standard guidelines for defining their validation before use.
As a result, most commercial antibodies are either inadequately validated or lack sufficient experimental data. Inadequacies in antibody validation have resulted in unrepeated results and, in some cases, project abandonment. As a result, large sums of money, valuable time, and effort are lost.
Antibody Validation
Antibody validation proves an antibody’s specificity and ability to distinguish between different antigens. It also entails demonstrating specificity in the application for which it is intended, as well as establishing affinity, which means determining the strength of the bond an antibody can form with an epitope. Finally, the process is defined as providing antibody reproducibility.
Many antibody manufacturers validate their products, while others do not validate them at all. These inconsistencies exist because no regulatory body is in charge, unlike the pharmaceutical industry. Fortunately, some basic rules and regulations for validating antibodies have emerged, and scientists, clinicians, and other interested parties should be aware of them, as outlined below.
Antibody Definition
The binding molecule, usually an antibody, must be easily identified. As a result, an antibody ID, clone number, commercial product number, or equivalent is suitable. The antibody structure is more appropriate, primarily defined by the amino acid sequence. Significantly, specifying the polyclonal or monoclonal antibody production cost and whether the binder is a monoclonal or polyclonal antibody is necessary. The lack of this information means that the work will be irreproducible.
Defining the Target
The ability of antibodies to selectively connect with another molecule known as an antigen is perhaps their most important feature (usually the analyte). The target antigen should be defined as precisely as possible. The immunogen structure, including the hapten orientation and linker, must be designated as the chemical formula when dealing with haptens. Failure to properly define the target means failing to determine whether the binder is sufficiently selective.
Binding Selectivity/Cross-Reactivity
Cross-Reactivity (CR) is a reasonably sophisticated property that is frequently misunderstood. Despite not fully comprehending his research paper, several researchers rely solely on Abraham GE’s definition. As a result, it’s widely assumed that monoclonal antibodies have fewer CRs than polyclonals. However, this isn’t always the case, so getting the CR data right is critical. This is because more CR data increases the likelihood of accurate usability evaluation in any given application.
Concentrations of Additives and Antibodies
Even with surface plasmon resonance, determining antibody concentration is difficult (SPR). As an alternative, many companies decide on a non-selective protein concentration method, such as UV at 280 nm, bicinchoninic acid, or the Bradford assay for amino acid analysis. Finally, it is possible to conclude that the antibody concentration indicated on any product label is only a rough estimate for assay optimization.
Documentation
The derived information for each feature listed above should be properly documented using a data sheet. Documents that are nearly empty and only contain the reagent’s name and order numbers should indicate that the antibodies involved have poor validation standards. These antibodies are frequently only useful in situations involving the task of screening a binder. However, you should avoid such antibodies if a dependable reagent is required.
Influence of Nontarget Substances/Matrix Effect
Abraham’s definition, as previously mentioned, is also helpful for matrix components such as humid acids, solvents, humic acids, salts, and other additives. The main distinction is the nonspecific mode of action and, as a result, the typically high concentrations that are applicable. Regrettably, this method has yet to gain widespread acceptance. It can, however, be useful when testing the robustness of an immunochemical reagent.
Stabilizing and Storing
Despite their benefits, antibodies are somewhat unstable reagents that require special handling. This is due to the high cost of the majority of antibody reagents. Antibodies can thus only be stored or stabilized using the appropriate protocols. When using an antibody for an extended period, it is beneficial to use validation of stability, but only under certain conditions. As a result, avoiding poor stability can save a lot of frustration and money.
Application Protocols
Application protocols are critical sources of information for understanding an antibody’s applicability under specific conditions. One of the essential pieces of data derived from application sheets is the possibility of using the antibody in the intended sample matrix, such as surface water, urine, or serum. This increases the likelihood of an immunoassay being successful. Furthermore, the number of accessible application protocols is evidence of the validity of the validation method.
User Feedback
User comments and ratings are another essential addition to application protocols. These users must have previously purchased and used the antibody in specific applications. The open and direct exchange of user experience and data is an excellent example of “Open Science,” a highly effective approach to accelerating and improving scientific progress.
Bottomline
You can use these ten basic rules to determine antibody validity in various situations. This makes the processes as simple as possible, especially for those who have never worked with antibodies. However, when assessing the level of validation of any commercial antibody, there are several references and supplementary resources to consult. If one or more of the five required rules are not met, using the respective binding agent or antibody for scientific work is not recommended without additional validation. The analytical methods discussed in this article are merely examples. As a result, validation is entirely dependent on the application.
