LevonorgestrelQualityChecker

1. Scope

The Levonorgestrel Quality Checker utility is used for Levonorgestrel. The actual input.csv is the source of truth for the input structure; control criteria are defined by the executable and the domain description.

The utility does not use machine learning; decisions are produced by deterministic rules.

Categories: Contraceptives

Tags: assay, contraceptives, fixed-dose combinations, heavy metals, hormones, impurities, residual solvents, solid dosage

2. Execution modes

LevonorgestrelQualityChecker.exe                            → demo mode (console output)
LevonorgestrelQualityChecker.exe input.csv output.json      → evaluate your data

3. Key controlled areas

• assay / content
• purity and impurities
• residual solvents
• heavy metals / elemental impurities
• pH and physicochemical parameters

5. URS — user requirements

6. input.csv data contract

The source of truth for the input schema is the actual input.csv header. Column names are technical identifiers and are not translated.

CSV example

BatchNumber,AssayPercent,SpecificRotation,MeltingPoint,UV240_280Ratio,Impurity3Keto,ImpurityEpimer,TotalImpurities,LossOnDrying,HeavyMetals,ResidualSolvents,EthanolPPM,AcetonePPM,ClarityNTU,ColorAPHA
LNG-SUB-2026-001,99.5,27.0,207.5,2.0,0.2,0.1,0.4,0.3,5,1500,800,500,2,30

7. FS — functional specification

8. output.json contract

The output file must be suitable for automated processing, audit review and correlation with the source input.csv row.

{
  "utility": "LevonorgestrelQualityChecker",
  "api": "Levonorgestrel",
  "batchNumber": "LNG-SUB-2026-001",
  "overallStatus": "PASS|WARNING|FAIL",
  "checkedAtUtc": "2026-05-18T00:00:00Z",
  "checks": [
    {
      "parameter": "BatchNumber",
      "value": "LNG-SUB-2026-001",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "AssayPercent",
      "value": "99.5",
      "unit": "%",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "SpecificRotation",
      "value": "27.0",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "MeltingPoint",
      "value": "207.5",
      "unit": "°C",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "UV240_280Ratio",
      "value": "2.0",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Impurity3Keto",
      "value": "0.2",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "ImpurityEpimer",
      "value": "0.1",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "TotalImpurities",
      "value": "0.4",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    }
  ],
  "criticalFindings": [],
  "sourceFile": "input.csv"
}

9. OQ/PQ test scenarios

10. QA/QC, CSV and change control

• Before production use, the client records executable version, checksum, specification/monograph version, test CSV, expected JSON and IQ/OQ results.
• Column names must not be changed without updating the validator and test scenarios.
• The source CSV, output.json and utility version should be stored together as an evidence package.
• Any change in control rules must go through change control and repeated OQ scenario verification.