Overcoming common immunoassay challenges
Generating accurate and precise data on analytes in the complex matrices frequently encountered in biological R&D means overcoming many challenges. These can include interference that reduces robustness, selectivity and specificity, and the poor performance of cross-reacting antibody reagents.
Sources of interference vary depending on the nature of the assay, and interference should be determined early in method development by assessing a number of factors:
- Parallelism/linearity
- Recovery of spiked analyte
- Effects of blocking agents
- Changes in therapy and sampling techniques
- Trends and inconsistencies in study results
Assay interference can be avoided by careful choice of reagents, including dilution, or depletion steps in the protocol, or blocking with specific reagents. Drug-target studies can be complicated by drug-target complex dissociation, which can be reduced by optimizing reagent concentrations and incubation/assay times. The development of anti-drug antibody (ADA) assays should include evaluation of drug tolerance early in assay development and validation.
Minimize contact times to reduce matrix interference
Interference is often countered by dilution, but this lowers assay sensitivity. Alternatively, contact times can be reduced to favor specific high-affinity antibody-antigen interactions and minimize low affinity interference. This is possible in a flow-through device that shortens contact times between reagents, the sample and its matrix.
Avoid cross reactivity of antibody reagents
Cross-reactivity (antibody binding to different antigens in the matrix) is widespread and selecting antibodies based on high specificity/low cross-reactivity is critical in assay validation. For example, a monoclonal antibody should be chosen as the primary antibody (e.g. for capture) to establish high assay specificity, and a polyclonal antibody can be used as the detection reagent.
Miniaturize assays to save sample and reagent
Getting more data from precious samples and reagents is an increasing challenge. This can include microsampling in animal studies to meet the requirements of the 3R’s (Replace, Reduce, Refine), or the analysis of precious biotherapeutics used in cell and gene therapy. Reagent availability can also be an issue, for example when analyzing lead compounds in early drug development. Miniaturizing immunoassays to the nanoliter scale enables more data to be generated from smaller amounts of sample and reagents and even makes it possible to perform ‘one mouse, one PK’ studies that reduce animal use and biological variation in preclinical studies and maximize data quality.
Avoid sample dilution and repeats by staying in range
Extensive sample dilution to stay in range can limit sensitivity and result in errors that require laborious assay repeats. Analytical efficiency can be greatly improved with methods that have high precision and accuracy, and a broad analytical range.
Implement automation to save time
Productivity relies on the rapid development and validation of immunoassays. Automation is a great support for this, with many benefits:
- Minimal hands-on time
- Reduced risk for errors that require assay repeats
- Improved precision in liquid handling
- Support for Design of Experiments (DOE) to accelerate method development