ValidateLabs™ Validation Processor

Show export diagnostics (model vs imported concentration)

Tab	Description
Start Page	Overview of the Validation Processor and example datasets.
Criteria & Definitions	Pick a validation guideline and set acceptance limits (bias, precision, carryover, etc.).
File Importer	Import and standardise raw validation data files.
File Formatter	Map custom column names to the app format (when Other is selected).
Calibration Review	Review calibration curves, residuals, and model fit; exclude calibrator levels.
Detection & Quantitation Limits	Regression equations, limit of detection (LOD) and lower limit of quantitation (LLOQ), by the method the selected guidance defines.
Carryover	Assess analyte carryover from high-concentration samples into subsequent blanks.
QC Analysis	Evaluate bias and precision (within-run and between-run) from QC samples.
Dilution Integrity	Assess bias and precision when samples above the upper limit are diluted into range.
Ion Ratio & RT	Peak identity: qualifier ion ratios and relative retention time.
Stability	Assess analyte stability (e.g. autosampler, storage) as % change from baseline.
Matrix Effects	Inspect ionisation suppression/enhancement.
Interference	Assess IS, matrix, and common-analyte interferences.
Validation Report	Configure and export the validation report.
Sample Processing	The per-injection record: every processed injection with its nominal, response, model and back-calculated concentration. Also the report's raw-data appendix.
Start Page	Overview of the verification workflow and the example data set.
Verification Import	Load the verification files; each experiment is detected and pooled into one table.
Method Comparison	Compare the new method against the established one on paired patient samples (CLSI EP09).
Precision	Repeatability and within-laboratory imprecision, against the manufacturer claim (CLSI EP15).
Trueness & Bias	Measured mean against the assigned value of a reference material.
EQA	Performance against the peer group across external quality assessment rounds.
ROC / Method Evaluation	Sensitivity, specificity and AUC when the result is used to classify an outcome.
Verification Report	Configure and export the verification report, as Word or HTML.
Definitions	Glossary of validation terms used in this app.
Settings	User interface options, session save/load, and autosave.
Settings	User interface options, session save/load, and autosave.

Method verification

This application is currently still under development ( 1.5.0 (b32113c) ). Contact us on dwl8@leicester.ac.uk for feedback and more information on the application and all related queries.

Please do not upload sensitive information such as internal sample references or any patient identifiable data.

Introduction

Verification is the experimental confirmation that a measuring system meets its specified requirements. Establishing a method's performance is the manufacturer's responsibility; your laboratory's job is to confirm those claims locally - on your instrument, with your staff, on your samples - before the method goes into service.

The approach follows the Association for Laboratory Medicine guidance on measurement verification, with the statistics drawn from CLSI EP09 (comparison of procedures) and CLSI EP15 (imprecision and trueness). Five experiments are supported: comparison against the established procedure, imprecision, trueness against a reference material, performance against an EQA peer group, and - beyond the analytical core - diagnostic performance by ROC analysis.

Run only the experiments you actually performed: each tab is independent, and the report contains just the sections you have data for. When you are finished, export a Word report for the record or an interactive HTML one for review.

Confirming analytical performance does not by itself establish that a method is fit for the clinical purpose intended for it. These procedures cannot be used to verify ordinal (semi-quantitative) or dichotomous results.

How it works

Import once, then visit whichever analysis tabs apply. Every tab reads its own slice of the imported data.

Import data

One file per experiment. Each file's experiment is detected from its columns and pooled automatically.

Verification Import

Compare methods

Passing-Bablok and Deming regression, Bland-Altman, and bias at your medical decision levels.

Method Comparison

Check precision & trueness

Imprecision against the manufacturer claim; bias against an assigned reference value.

Precision / Trueness & Bias

Review EQA & ROC

Peer-group performance, and sensitivity/specificity where the result classifies an outcome.

EQA / ROC

Export report

A populated verification report, as Word or interactive HTML.

Verification Report

What your files need to contain

Each experiment is a separate file - CSV, tab- or semicolon-separated text, or an Excel workbook. You do not tell the app which is which: the columns are read and the experiment identified, then everything is pooled into one table tagged by experiment and source file. Headers may carry units or extra words, and additional columns are ignored.

Method comparison - one row per patient sample, with the comparative and test result (replicate columns are accepted).
Precision - one row per replicate, with the day or series it belongs to. One file per concentration, named distinctly (the file name becomes the level label unless the file carries a level column).
Trueness - repeated results for a reference material. The assigned value is entered in the app, not in the file.
EQA - your results per sample, plus the scheme's peer mean, SD and n. The two are merged automatically.
ROC - a result and a binary outcome per subject, and optionally a list of candidate thresholds. One file per method, named distinctly.

For the exact column names accepted for each, open the Help menu and read the Verification Import page.

Please contact our team on dwl8@leicester.ac.uk about any questions and/or issues with this software.

Example data

A worked example built from the published ACB verification data set, covering all five experiments.

Load it from the Verification Import tab: the worked session arrives with the manufacturer claims, assigned target and decision levels already filled in, so every tab and the report are populated at once. The files themselves are downloadable here if you would rather see the input format first.

Download the example files (.zip)

Welcome to the Validation Processor

This application is currently still under development ( 1.5.0 (b32113c) ). Contact us on dwl8@leicester.ac.uk for feedback and more information on the application and all related queries.

The Validation Processor is intended for assay validation purposes only. Please do not upload sensitive information such as internal sample references or any patient identifiable data.

Introduction

The Validation Processor helps you turn raw bioanalytical and clinical assay data into a complete, accreditation-ready validation report — without spreadsheets or manual calculation.

Mass-spectrometry validation data exported from common software (e.g. TargetLynx ^™ , LabSolutions ^™ , Skyline ^™ ) is imported, compiled and analysed experiment by experiment — calibration and model fit, limit of quantitation, bias and precision, carryover, dilution integrity, stability, matrix effects and interference.

You choose the validation guideline you are working to and the app applies that guideline’s acceptance criteria and expected experiments for you. Supported guidelines currently include ANSI/ASB 036 (forensic toxicology), ICH M10 , the FDA Bioanalytical Method Validation guidance, and CLSI C62 (clinical LC-MS/MS). Every limit and definition remains fully editable to match your own SOP.

When you are finished, a Word validation report is populated automatically with your results, pass/fail outcomes and the methods actually applied. For step-by-step help on any tab, open the Help menu (top right of the screen).

How it works

The validation workflow runs left to right. Each step is a tab in the sidebar; work through them in order.

Set criteria

Pick your validation guideline and confirm the acceptance limits and experiments.

Criteria & Definitions

Import data

Upload one file per batch. Sample types are auto-detected; adjust if needed.

File Importer

Choose models

Set the calibration model for every compound, from Calibration Review.

Calibration Review

Review experiments

Check each experiment tab — QC, carryover, stability, matrix effects, interference.

Analysis tabs

Export report

Generate the populated Word validation report.

Validation Report

Tutorial

Using the application

Start in the Criteria & Definitions tab: choose your validation guideline and the app fills in that guideline’s acceptance limits and shows only the experiments it expects. Use the Experiments performed selector to auto-detect the experiments from your data, follow the guideline, or choose them manually. Every limit stays editable.

Next, open the File Importer tab and upload your validation data as separate batch files. The Validation Processor natively reads several common export formats. For other formats, select Other in the drop-down to open the File Formatter tab, where you can map the columns so the data is readable, then return to the File Importer to view the compiled data.

Once the data has been successfully imported, each validation batch file is processed and compiled into a single table within the File Importer Tab, where the filename of each batch is used as the 'Batch' column tag. This table is used for all other downstream processing. The software will automatically search for key terms in the 'Name' column in order to identify the Sample Type (e.g., 'Calibrator'). It is possible to define the Sample Type based on other naming conventions using the 'Edit sample types' option, either by using the drop-down selection table or by importing a 'Sample Type Key' .csv file.

Navigate through the tabs to explore and analyse the imported data. Of note, the Calibration Review tab allows the user to set the response function used for every compound. By default, models are constrained to linear. The models selected here are used throughout the software to calculate concentration. Other user input variables are pulled through the application and are used for defining the Validation Report . This can be exported and reviewed for accreditation purposes.

Prerequisites for the data

Validation experiment raw data files must first be analysed in an appropriate processor (e.g., Skyline ^™ ) to check the integrity of the data (e.g., chromatogram integration). Data should then be exported into files containing the following (or equivalent naming conventions):

Compound name
Sample name
Concentration
Peak area
Internal standard peak area
Response

These files can then be imported into the Validation Processor and analysed accordingly. For each batch, create a separate file with a unique name (e.g., Batch 1). Readable import files include: .csv, .txt, and .xlsx.

Below are some examples of validation data the user can upload into the Validation Processor for testing and exploring the application.

Please contact our team on dwl8@leicester.ac.uk about any questions and/or issues with this software.

Experimental design plan

Not sure how many samples, levels and batches you need? Download a design plan for your chosen guideline — an overview of every experiment with the recommended concentration levels, replicates, batches/runs and independent matrix sources, plus an approximate total sample count.

Select your guideline in the Criteria & Definitions tab first; the plan is generated for whichever guideline is currently selected. Values are a drafted starting point — always confirm against the guideline itself.

Download experimental design plan (.csv)

Example datasets

Download example dataset 1 (TargetLynx) Download example dataset 2 (TargetLynx) Download example dataset 3 (Skyline)

Name of the validated method/procedure

Instrument reference

Define the measurement unit

Validation guidance document

Auto-detect from imported data

As required by the guideline

Choose manually

Select experiments performed

Bias and precision

Carryover

Dilution integrity

Sample stability

Ionisation suppression/enhancement

Interferences

Ion ratio and retention time

Recovery

Reinjection reproducibility

Recovery and Reinjection reproducibility have no tab and no calculation - the app does not quantify them. Ticking one adds a section to the report recording that the guideline expects it and that its results are documented separately.

Which experiments were performed. This shows/hides the matching analysis tabs and the report checklist. Calibration and the limit of quantitation are always included. Auto-detect infers the set from the sample types found in your imported data; "As required by the guideline" uses the selected guideline's expected experiments; "Choose manually" lets you tick them yourself.

Within-run precision (%):

Between-run precision (%):

Precision limit (%):

IS interference fold-change:

Common analyte % of LOQ:

Compiled Data Import Table

Sample Type Selection Table

Model performance, all compounds

R-squared for every candidate model. The model in the last column is the one used to calculate concentrations throughout the app.

Calibrator exclusions

Calibration Acceptance

Acceptance summary

Calibrator accuracy detail

Every calibration standard, its back-calculated concentration and its deviation from nominal. Tolerance is wider at the LLOQ level.

Linearity assessment

First-, second- and third-order fits to each calibration run, the slope's p-value and residual normality (Shapiro-Wilk), shown at each analyte's weakest run - or at the run named below as the linearity study. A significant quadratic or cubic term flags curvature; residual normality is reported and does not decide the verdict. Set a deviation-from-linearity tolerance on the Validation Report tab to judge the deviation as well.

Report linearity at

Regression record

The first-, second- and third-order least-squares fits of the run above, reported the way MedCalc reports them: R-squared, adjusted R-squared and the residual standard deviation; each coefficient with its standard error, 95% confidence interval, t and P (and, for the polynomials, the partial and semipartial correlations and the variance inflation factor); the analysis of variance; and Shapiro-Wilk on the residuals. The third-order fit enters x, x^2 and x^3 together, as MedCalc's multiple regression does.

Analyte

Model summary

Coefficients

Analysis of variance

Show each calibrator's residual from the straight line

Limits of detection and quantitation

LLOQ replicate study

Laboratory's own S/N minimum at the lower limit (blank = guidance)

Laboratory's own CV limit, % (blank = guidance)

Show every LLOQ injection

Signal-to-noise at the lower limit

Calibration model equations

The fitted response function per compound, and the regression LOD where the selected guidance defines one.

Blank-signal limits

Derived from the blank response you selected on the left: LOD at mean blank + 3.3 SD and LOQ at mean blank + 10 SD. These are shown because you chose the blank-signal definition - where that differs from the limit the selected guidance defines, the guidance figure above is the one the report uses.

Carryover Table

Relative carryover and allowable concentration ratio

Bias by compound and QC level

Every compound and level against the acceptance band. Bars beyond the dashed lines are outside the bias limit set in Criteria.

Dilution Integrity Table

Stability exclusions

Matrix Effects Table

Internal Standard Interference Table

Matrix Interference Table

Common analyte Interference Table (%Area of LOQ)

Pooled verification data

Comparison by analyte

Imprecision by analysis of variance (CLSI EP15)

Manufacturer claims (per level, optional)

Results

Trueness / bias vs assigned target

Assigned targets (per material)

Results

External quality assessment (peer-group bias)

Summary by analyte

Per-sample z scores

Diagnostic performance (ROC)

Summary

ROC curve

Sensitivity / specificity by threshold

Verification summary

Ion ratio and relative retention time

The imported data carries no reference-ion ratio or %Dev RRT columns. These come from exports that record them - a Shimadzu Insight export does.

Summary by compound

Closest reference ion, per injection

Each point is one injection, plotted against the reference ion that came closest to its set ratio - the one the verdict rests on. Points beyond the dashed lines failed on every reference ion.

Detail

Summary Table

Report settings

Report header (appears in Word document)

Title

Reference

Version

Active date

Owner

Author

Specimen requirements (optional)

Laboratory/Department (optional)

Report date override (optional)

Custom introduction (optional)

Validation plan (optional)

System parameters - LC and MS conditions (optional)

LOD formula description (optional)

Materials table (optional)

Conclusion/remarks (optional)

Settings

Help

Method verification

Introduction

How it works

What your files need to contain

Example data

Welcome to the Validation Processor

Introduction

How it works

Tutorial

Using the application

Prerequisites for the data

Experimental design plan

Example datasets

Criteria & Definitions

Please enter your validation specifications

Experiments performed

Acceptance criteria

Calibration / linearity

Carryover

Bias and precision

Dilution integrity

Stability

Matrix effects

Interferences

Define export type

Load validation batch files

Values from the export

Define response type

Edit sample information

Transform data

Compiled Data Import Table

Sample Type Selection Table

Define calibration settings

Model performance, all compounds

Calibrator exclusions

Calibration Acceptance

Acceptance summary

Calibrator accuracy detail

Linearity assessment

Regression record

Model summary

Coefficients

Analysis of variance

Define limit of detection settings

Limits of detection and quantitation

LLOQ replicate study

Signal-to-noise at the lower limit

Calibration model equations

Blank-signal limits

Define carryover limits

Carryover Table

Relative carryover and allowable concentration ratio

Define bias and precision settings

Bias by compound and QC level

Define dilution integrity settings

Dilution Integrity Table

Define stability settings

Stability exclusions

Define matrix effect limits

Matrix Effects Table

Define IS interference settings

Define matrix interference settings

Define common analyte interference settings

Internal Standard Interference Table

Matrix Interference Table

Common analyte Interference Table (%Area of LOQ)

Data

Exclusions

Pooled verification data

Settings

Laboratory's own criteria

Comparison by analyte

Data

Imprecision by analysis of variance (CLSI EP15)

Manufacturer claims (per level, optional)

Results

Data

Settings