Abstract Background The human body produces immunoglobulin antibodies as a response to various viruses, bacteria, and pathogens. Automated antibody assays, developed to detect immune response or infectious state, are typically qualitative or semi-quantitative where a positive or negative designation is reported out based on a comparison of signal intensity from the chemical reaction and a predetermined signal to cut-off ratio. In these assays the result is not suggestive of a concentration but rather the strength of the antibody antigen avidity. Use of daily QC, in conjunction with linearity materials, can be used to monitor the performance of these assays. Although the signal response may be linear, serological assays can show variability due to the assay’s antigen specificity to the antibodies present in the sample and the antibody heterogeneity within the samples. Understanding these variables is crucial in interpreting patient and control results, as well as developing controls and linearity material to meet the needs of regulatory requirements for clinical testing. Methods Evaluation of high and low titer patient samples was carried out across multiple platforms including the Roche cobas®, Abbott Alinity, Ortho Vitros, and Siemens Centaur, where applicable, for analyte recovery of aHBs IgG, Toxoplasma IgG and Rubella IgG. These patient samples were then used to evaluate the linear response across the analyzer measuring range using equal delta admixtures, as well as serial dilution studies. Results The serology assays tested here, for Rubella IgG, show a significant difference in recovery of approximately 50% when comparing a 60% diluted patient sample run across multiple platforms. Results vary at both the low and high end of the assays. The linearity of aHBs IgG assays and linear variability in the Rubella IgG and Toxoplasma IgG assays is demonstrated via equal delta analysis. These results demonstrate the incongruity in results within a patient sample, likely due to the heterogeneity of antibodies in the patient samples and the non-linear dilution effect this can cause. Conclusion Since serology assays are based on antigen antibody avidity, patient pools taken from recently infected patients, while ideal low positives, can be variable lot to lot and assay to assay as the antibodies are not matured and contain a mix of IgG and IgM, decreasing avidity. Lot to lot variability is decreased in third party controls and linearity materials such as VALIDATE by diluting high titer patient samples or by using recombinant antibodies. Laboratories must set their own acceptance criteria for daily QC and calibration verification linearity testing, keeping in mind inherent assay variability and variability in the controls themselves. It is important to keep in mind that in-kit controls and linearity materials are typically optimized for that specific lot of reagent and calibrators and that although they may be required as part of the manufacture’s IFUs, use of a third-party quality control and linearity material in conjunction with the in-kit controls can help to ensure laboratories are monitoring the assay for changes over time and allows for comparison against peer data when determining clinical significance of assay performance.