Set Automated Pass/Fail Criteria for Assays and Unknowns to Match Your SOP

QC Acceptance in STATLIA MATRIX provides the first comprehensive method for automated Pass / Fail determinations for assays and unknowns based on your SOP.

The Automated QC Acceptance is Flexible and Comprehensive

STATLIA MATRIX allows you to set comprehensive yet flexible metrics for the Pass/Fail acceptance criteria of each assay and each individual unknown result according to your SOP.

You can include or exclude metrics for the precision, response and data reduction of your baselines, standard and controls for the Pass/Fail acceptance criteria of your assay.  The data reduction metrics are specific for quantitation, potency, or immunogenicity tests.

The precision and data reduction metrics of each unknown are matched to the Pass/Fail acceptance criteria you set for your unknowns. The data reduction metrics are specific for quantitation, potency, or immunogenicity tests.

The assay and unknown Pass/Fail determinations are based on reference statistics from your pooled assays or tolerance ranges set by your laboratory.

Setting Your QC Acceptance Criteria is as Easy as 1-2-3

1. Select the desired Metrics from the Standard Metrics, Control Metrics, and Unknown Metrics tabs.
2. Select the desired Weight for each Metric, to be used to compute the final Pass/Fail Score (a 0 Weight excludes that Metric).
3. Select the Acceptance Limit for each Metric. A Prob> is a statistical comparison to your pooled assays. A Low Tol / High Tol is a tolerance range established by your laboratory.

Select Your QC Acceptance Criteria

The final scores are the weighted sum of the metric groups that were included in the Standard Metrics and Control Metrics (Assay Score) and Unknown Metrics (Uk Score) screens. You can set a Pass/Fail score for the assays and each unknown that is appropriate for each test. The scores can be:

  • The weighted harmonic mean of the individual statistical probabilities (QC Probabilities).
  • The sum of all failed metrics times their respective weights (QC Points).
  • None (no Pass/Fail score).

Unknown results can be suppressed and not stored in the database or listed in any reports or LIM Results if the assay fails or if the individual unknown fails.

Separate Unknown Pass/Fail Metrics For Each Testing Technology

The final Uk Score is the combined weighted sum of the selected precision and data reduction metrics for that unknown.  The data reduction metric options for the unknowns are specific for each testing technology.

Quantitation

  • Concentration Range or Concentration Error

Potency (Residual Parallelism or Confidence Interval Parallelism)

  • Unknown Dilution Curve Fit
  • Parallelism
  • Relative Potency or Relative Potency Confidence Limit Ratio

Immunogenicity (Tier 1 or Tier 2)

  • Cut Point Ratio (Tier 1) or %Inhibition (Tier 2)

Immunogenicity (Tier 3)

  • Unknown Dilution Curve Fit
  • Cut Point Ratio Titer or Estimated Dose

Track The Performance Of Each Assay Metric Group

Each Assay Metric Group Score is the combined weighted sum of the metrics of that group expressed as QC Points (shown here) or QC Probabilities as specified by you in your acceptance criteria for this test.

Individual failed metrics are listed in the assay report along with their acceptance ranges (optional).

Seeing the precision, response, and data reduction scores of the baselines, standard, and controls as individual groups gives you a detailed insight into the performance of that assay that is unavailable in any other program.

Assay Acceptance…at a Glance

The final Pass/Fail and Assay Score plus the individual scores of each QC metric group plus the informative QC graphs are displayed at the beginning of each assay report for quick review.   This allows you to assess everything you need to know about that assay…at a glance.

Sample Replicate Outliers Automatically Masked

  • Outliers are identified automatically and can be masked from all computations.
  • Individual precision outliers from a dilution (minimum 3 replicates) are identified using the Grubb’s test.
  • Individual residual outliers off a dilution curve are identified using a residual probability test.
  • Outlier thresholds for all outliers identified by the software can be set by your laboratory.