Method_Validation_Data_Packager

Method Validation Data Packager

Lumex QC URS & FS input.csv output.json rule-based LIMS-ready method validation
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Utility description: Method Validation Data Packager

Method Validation Data Packager — Assessment of Analytical Method Validation Parameters

ℹ️  Utility checks key validation parameters according to ICH Q2(R1) and USP <1225>:
   • Linearity: R² ≥ 0.999
   • Accuracy: Recovery 98.0–102.0%, RSD ≤ 2.0%
   • Precision: Repeatability RSD ≤ 2.0%
   • Limit of Detection/Quantitation (LOD/LOQ): Reported
   • Robustness: Variation ≤ 5.0%

⚠️  CRITICAL: Non-compliance with linearity or accuracy criteria renders the method unsuitable!
   These parameters are the basis for registering a pharmacopoeial method.

Usage:
 Method_Validation_Data_Packager.exe                            → demo mode (console output)
 Method_Validation_Data_Packager.exe input.csv output.json      → evaluate your data

Input format:
BatchNumber,LinearityR2,YIntercept,Slope,MeanRecoveryPercent,RecoveryRSD,PrecisionRSD,LOD,LOQ,RobustnessVariationPercent

Example:
 VAL-METHOD-2026-001,0.9998,0.5,12000.0,99.5,0.8,0.9,0.05,0.15,1.2

— WHY IS THIS NEEDED?
Analytical method validation is a mandatory GMP and regulatory requirement (FDA, EMA).
• Confirms that the method is suitable for its intended use (QC, identification, impurities).
• ICH Q2(R1) defines standard parameters: Specificity, Linearity, Accuracy, Precision, Range, LOD, LOQ, Robustness.
• The utility automates the calculation and verification of key metrics, reducing the risk of human error in report preparation.
• Allows rapid assessment of method suitability before starting serial analysis.

⚠️  CRITICAL:
• R² ≥ 0.999 is required for quantitative determination of active substance and impurities.
• Recovery 98-102% demonstrates absence of systematic error (bias).
• Precision RSD ≤ 2.0% ensures reproducibility of results between analyses.
• Robustness shows method resistance to small changes in parameters (pH, temperature, mobile phase composition).

Key features:
• Aggregation of data for all key ICH Q2 parameters.
• Automatic check of acceptance criteria.
• Generation of structured JSON for archiving in LIMS.

Critical parameters:
• Linearity R²: >= 0.999
• Accuracy Recovery: 98.0-102.0%
• Precision RSD: <= 2.0%
• Robustness Variation: <= 5.0%

💡 Usage tips:
1. Use data from at least 5 concentrations for linearity assessment.
2. For accuracy, perform analysis at 3 concentration levels (80%, 100%, 120%) with 3 replicates each.
3. Evaluate precision using 6 replicates of one concentration (100%).
4. Calculate LOD/LOQ by signal-to-noise (3:1 and 10:1) or by standard deviation of response and slope.
5. Store raw chromatogram/spectrum data along with this report for auditing.

⚠️ Note: This utility does not replace full statistical analysis (e.g., ANOVA for intermediate precision), but serves as a rapid screening tool before final validation report formatting.

input.csv

BatchNumber,R2,YIntercept,Slope,MeanRecovery%,RecRSD%,PrecRSD%,LOD,LOQ,RobustnessVar%
VAL-METHOD-2026-001,0.9998,0.5,12000.0,99.5,0.8,0.9,0.05,0.15,1.2
VAL-METHOD-2026-002,0.9995,0.2,11500.0,100.1,1.1,1.2,0.06,0.18,1.5
VAL-FAIL-2026-003,0.9950,1.5,10000.0,95.0,3.5,3.0,0.10,0.30,8.0

Utility description

Method Validation Data Packager — Assessment of Analytical Method Validation Parameters

ℹ️  Utility checks key validation parameters according to ICH Q2(R1) and USP <1225>:
   • Linearity: R² ≥ 0.999
   • Accuracy: Recovery 98.0–102.0%, RSD ≤ 2.0%
   • Precision: Repeatability RSD ≤ 2.0%
   • Limit of Detection/Quantitation (LOD/LOQ): Reported
   • Robustness: Variation ≤ 5.0%

⚠️  CRITICAL: Non-compliance with linearity or accuracy criteria renders the method unsuitable!
   These parameters are the basis for registering a pharmacopoeial method.

Usage:
 Method_Validation_Data_Packager.exe                            → demo mode (console output)
 Method_Validation_Data_Packager.exe input.csv output.json      → evaluate your data

Input format:
BatchNumber,LinearityR2,YIntercept,Slope,MeanRecoveryPercent,RecoveryRSD,PrecisionRSD,LOD,LOQ,RobustnessVariationPercent

Example:
 VAL-METHOD-2026-001,0.9998,0.5,12000.0,99.5,0.8,0.9,0.05,0.15,1.2

— WHY IS THIS NEEDED?
Analytical method validation is a mandatory GMP and regulatory requirement (FDA, EMA).
• Confirms that the method is suitable for its intended use (QC, identification, impurities).
• ICH Q2(R1) defines standard parameters: Specificity, Linearity, Accuracy, Precision, Range, LOD, LOQ, Robustness.
• The utility automates the calculation and verification of key metrics, reducing the risk of human error in report preparation.
• Allows rapid assessment of method suitability before starting serial analysis.

⚠️  CRITICAL:
• R² ≥ 0.999 is required for quantitative determination of active substance and impurities.
• Recovery 98-102% demonstrates absence of systematic error (bias).
• Precision RSD ≤ 2.0% ensures reproducibility of results between analyses.
• Robustness shows method resistance to small changes in parameters (pH, temperature, mobile phase composition).

Key features:
• Aggregation of data for all key ICH Q2 parameters.
• Automatic check of acceptance criteria.
• Generation of structured JSON for archiving in LIMS.

Critical parameters:
• Linearity R²: >= 0.999
• Accuracy Recovery: 98.0-102.0%
• Precision RSD: <= 2.0%
• Robustness Variation: <= 5.0%

💡 Usage tips:
1. Use data from at least 5 concentrations for linearity assessment.
2. For accuracy, perform analysis at 3 concentration levels (80%, 100%, 120%) with 3 replicates each.
3. Evaluate precision using 6 replicates of one concentration (100%).
4. Calculate LOD/LOQ by signal-to-noise (3:1 and 10:1) or by standard deviation of response and slope.
5. Store raw chromatogram/spectrum data along with this report for auditing.

⚠️ Note: This utility does not replace full statistical analysis (e.g., ANOVA for intermediate precision), but serves as a rapid screening tool before final validation report formatting.

URS & FS — User Requirements and Functional Specification

This document describes the controlled interface, user requirements and functional behaviour of Method_Validation_Data_Packager. The utility is intended for automated verification of laboratory, pharmacopoeial, analytical or manufacturing QC parameters using input.csv and producing a structured output.json result.

Domain limits and critical parameters

Before production use, all limits must be verified against the approved specification, registration dossier, pharmacopoeial monograph, validated method and local SOPs.
  • • Confirms that the method is suitable for its intended use (QC, identification, impurities).
  • • ICH Q2(R1) defines standard parameters: Specificity, Linearity, Accuracy, Precision, Range, LOD, LOQ, Robustness.
  • • The utility automates the calculation and verification of key metrics, reducing the risk of human error in report preparation.
  • • Allows rapid assessment of method suitability before starting serial analysis.
  • • R² ≥ 0.999 is required for quantitative determination of active substance and impurities.
  • • Recovery 98-102% demonstrates absence of systematic error (bias).
  • • Precision RSD ≤ 2.0% ensures reproducibility of results between analyses.
  • • Robustness shows method resistance to small changes in parameters (pH, temperature, mobile phase composition).
  • • Aggregation of data for all key ICH Q2 parameters.
  • • Automatic check of acceptance criteria.
  • • Generation of structured JSON for archiving in LIMS.
  • • Linearity R²: >= 0.999
  • • Accuracy Recovery: 98.0-102.0%
  • • Precision RSD: <= 2.0%
  • • Robustness Variation: <= 5.0%
  • • Linearity: R² ≥ 0.999

URS — User Requirements Specification

IDRequirementCriticalityAcceptance criterion
URS-001The utility shall accept an input.csv file with exact headers defined in the data contract.HighThe file is processed without manual header editing.
URS-002The utility shall perform deterministic evaluation for Method Validation Data Packager using input values, approved limits and domain rules.HighEach row receives a PASS / WARNING / FAIL status.
URS-003The utility shall validate mandatory fields, data types, numeric ranges, units and domain plausibility.HighSchema, format and conversion errors are explicitly reported.
URS-004The utility shall identify critical deviations for parameters stated in the method description and specification.HighA critical deviation causes FAIL or a dedicated critical finding.
URS-005The utility shall generate output.json with machine-readable results, source values, warnings and failures.HighJSON is suitable for LIMS/ELN/MES integration, QA/QC review and archival.
URS-006The result shall not depend on machine learning or undocumented heuristics.MediumAll decisions are based on explicit rules, thresholds and input values.
URS-007The system shall preserve traceability between batch/sample, input data, applied rules and final status.HighThe output contains the batch/sample identifier and checked parameters.
URS-008The documentation shall support IQ/OQ/PQ preparation and inspection discussion.MediumURS, FS, CSV/JSON contract and test scenarios are supplied with the utility.
URS-009The utility shall support batch processing of multiple input.csv rows.MediumEach row is evaluated independently; errors in one row do not mask errors in others.
URS-010The utility shall support a simple operating model: demo mode and execution with input/output files.MediumThe CLI scenario is reproducible in test and production environments.

input.csv contract

#FieldTypeSamplePurpose
1BatchNumberstringVAL-METHOD-2026-001Batch or lot identifier used for traceability, review and deviation investigation.
2R2decimal0.9998Coefficient of determination; key acceptance metric for method linearity.
3YInterceptdecimal0.5Platinum content; controlled residual catalyst / elemental impurity parameter.
4Slopedecimal12000.0Controlled input parameter used by deterministic QC rules and traceable result generation.
5MeanRecovery%decimal99.5Recovery; accuracy metric indicating absence of significant bias.
6RecRSD%decimal0.8Relative standard deviation; precision metric for the process or analytical method.
7PrecRSD%decimal0.9Relative standard deviation; precision metric for the process or analytical method.
8LODdecimal0.05Limit of Detection; method sensitivity reference parameter.
9LOQdecimal0.15Limit of Quantitation; method suitability parameter for quantitative analysis.
10RobustnessVar%decimal1.2Controlled input parameter used by deterministic QC rules and traceable result generation.
BatchNumber,R2,YIntercept,Slope,MeanRecovery%,RecRSD%,PrecRSD%,LOD,LOQ,RobustnessVar%
VAL-METHOD-2026-001,0.9998,0.5,12000.0,99.5,0.8,0.9,0.05,0.15,1.2
VAL-METHOD-2026-002,0.9995,0.2,11500.0,100.1,1.1,1.2,0.06,0.18,1.5
VAL-FAIL-2026-003,0.9950,1.5,10000.0,95.0,3.5,3.0,0.10,0.30,8.0

FS — Functional Specification

IDFunctionImplementation
FS-001CSV importRead input.csv in UTF-8/CSV-compatible format and validate the header and expected columns.
FS-002Schema validationCheck mandatory fields, column count, critical missing values and row structure.
FS-003Type conversionConvert numeric, flag and text values; invalid formats are recorded as row-level errors.
FS-004Domain rule engineApply domain rules for Method Validation Data Packager, including limits from the utility description and approved specification.
FS-005Status aggregationProduce final status: FAIL for critical failure, WARNING for non-critical deviation, PASS for conformance.
FS-006JSON exportWrite output.json with detailed checks, source values, warnings, failures and critical findings.
FS-007Audit supportKeep the result structure suitable for review, deviation investigation, calculation reproduction and IQ/OQ/PQ preparation.
FS-008Integration contractSupport the production scenario: LIMS/ELN/MES creates input.csv, the utility returns output.json, and the portal displays description and documentation.
FS-009Error handlingReport errors unambiguously and do not substitute missing values with calculated values unless the rule is explicitly defined.
FS-010Version control supportDocument the utility version, input contract, executable checksum and rule application date.

Example output.json

{
  "utilityId": "method-validation-data-packager",
  "utilityName": "Method_Validation_Data_Packager",
  "overallStatus": "PASS|WARNING|FAIL",
  "sourceFile": "input.csv",
  "checks": [
    {
      "parameter": "BatchNumber",
      "value": "VAL-METHOD-2026-001",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "R2",
      "value": "0.9998",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "YIntercept",
      "value": "0.5",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Slope",
      "value": "12000.0",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "MeanRecovery%",
      "value": "99.5",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "RecRSD%",
      "value": "0.8",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "PrecRSD%",
      "value": "0.9",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "LOD",
      "value": "0.05",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "LOQ",
      "value": "0.15",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "RobustnessVar%",
      "value": "1.2",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    }
  ],
  "criticalFindings": [],
  "warnings": [],
  "generatedFor": "QA/QC review and LIMS integration"
}

Traceability matrix

URSFSOQ/PQ coverage
URS-001, URS-003FS-001, FS-002, FS-003OQ-001/OQ-002/OQ-003
URS-002, URS-004FS-004, FS-005OQ-004/PQ-001
URS-005, URS-007FS-006, FS-007OQ-005/PQ-002
URS-008, URS-010FS-008, FS-010IQ-001/OQ-006

OQ/PQ test scenarios

IDScenarioExpected result
OQ-001Valid sample rowPASS or acceptable WARNING according to the rules.
OQ-002Mandatory column missingSchema error or FAIL.
OQ-003Non-numeric value in numeric fieldType-conversion error.
OQ-004Critical parameter outside limitFAIL and critical finding.
OQ-005Multiple rows with different statusesIndependent row-level evaluation.
PQ-001User real batch/sampleReviewed result with retained input/output files.

QA/QC and change control

  • Do not rename columns without updating the validator, documentation and test set.
  • Retain input.csv, output.json, executable version, documentation and checksum.
  • Before production use, perform IQ/OQ/PQ or equivalent CSV/CSA verification.
  • Critical limits must be verified against the approved specification, local SOPs and registration dossier.

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