Biomedical Engineering Reference
In-Depth Information
validation, which could be labor intensive and time consuming, the assay should be
evaluated and qualified. This includes the assessment of assay robustness, the impact
of flow cytometer setup and standardization on data quality; sample stability in the
context of sample matrix, sample collection, and shipment logistics; and assay
quality controls.
On the basis of the intended use of data and regulatory compliance, it is
recommended to develop an assay validation plan identifying the required resources
(time, budget, and full-time employees), to develop validation parameters (stability,
precision, sensitivity, specificity, accuracy, limits of quantity, reference range, and
acceptability criteria, if required and applicable), and to appropriately document
the validation approaches and results. To ensure high data quality and minimize
instrument-to-instrument and analyst-to-analyst variability, instrument performance
and analyst performance should be compared and qualified prior to the stage of
sample analysis. During the stage of sample analysis, both the assay performance and
the instrument performance require close monitoring using predetermined accept-
ability criteria. It is only after orchestration of all parameters of assay development,
validation, and performance that the flow cytometry laboratory can present a
legitimate immunological story to support the development and commercialization
process as applied to experimental therapeutic agents.
REFERENCES
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