• Data Validation

    Quality, rigor and transparency are very important values for Olink Proteomics. Consequently, all of our assays are rigorously quality controlled and our validation data is made freely available.

    See our FAQ on the quality controls included in each assay run.

    How we validate our panels

    The analytical performance of our panels is carefully validated for sensitivity, dynamic range, specificity, precision and scalability. You can see how we perform and report on this validation below.

    Measuring ranges

    Analytical measuring range is defined by the lower limit of quantification (LLOQ) and upper limit of quantification (ULOQ) and reported in pg/mL. The high dose hook effect (a state of antigen excess relative to the reagent antibodies resulting in falsely lower values) is also determined for each analyte. The figure below shows an example calibrator curve and corresponding analytical measurement data.

    Validation Fig 1

    Precision

    All assays are thoroughly validated for precision (repeatability and reproducibility). The figure below shows a representative example of a combined intra-assay and inter-assay variation validation study.

    Validation Fig 2

    Scalability: Multiplex level-independent performance

    Olink’s PEA technology is able to achieve a high level of multiplexing while maintaining exceptional data quality, since unlike in many other immunoassay formats, any antibody cross-reactivity that may occur during the multiplexed assay is excluded from the detection process. This is exemplified in the figure below, comparing dCq-values from single assays for Growth Hormone (GH) and Matrix Metalloproteinase (MMP-7) with the equivalent assays performed in a full 96-plex reaction. The square of the correlation coefficient (R2) value was generated by linear regression.

    Validation Fig 3

    Specificity

    Using Olink’s panels, each biomarker analyte is addressed by a matched pair of antibodies, coupled to unique, partially complementary oligonucleotides and measured by quantitative real-time PCR. This dual recognition, DNA-coupled method provides exceptional readout specificity. Validation of the readout specificity for all our panels is carried out using a simple, sequential approach in which pools of protein analytes are tested with all 92 antibody probe pairs in the panel. The design of this validation study is shown below.

    Validation Fig 4v2

    A) Test ”sample” created (pool of full-length recombinant antigens corresponding to 8 of the 92 proteins targeted by the specific panel). B) Test sample of 8 antigens analyzed using all 92 oligo-labeled antibody pairs (Olink probes) C) qPCR readout from all 92  probes detects only those 8 represented by the pooled recombinant antigens. The whole process is then repeated using additional pools of analytes.

     

    The figure below shows the aggregated results from such a study, clearly demonstrating that thanks to our Proximity Extension Assay technology, any antibody cross-reactivity that may occur in the high-multiplex reactions does not affect the specificity of the final readout. This is contrast to other conventional methods such as sandwich ELISA, where antibody cross-reactivity in multiplex assays contributes directly to the detection readout.

    Validation Fig 5

    Click image to enlarge

    Validation Data documents for current Olink panels

    The analytical performance of our panels has been carefully validated for sensitivity, dynamic range, specificity, precision and scalability, and the results are summarized in the Data Validation documents for each panel. To access these documents, please go to the Documents & Downloads page.

    Biomarker Validation Data web pages

    Detailed validation data and background information for all of the 92 biomarkers in each panel are available by clicking on the individual biomarkers in the summary tables that can be accessed via the links below:

    Cardiometabolic

    Cell Regulation

    CVD II

    CVD III

    Development

    Immune Response

    Immuno-Oncology

    Inflammation

    Metabolism

    Mouse Exploratory

    Neuro Exploratory

    Neurology

    Oncology II

    Oncology III

    Organ Damage