PreservativeEfficacyValidator

1. Scope

The Preservative Efficacy Validator utility is used for Preservative Efficacy Validator. 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: Pharmacopoeial methods, Sterile liquids

Tags: contrast media, dialysis, endotoxins, heavy metals, infusions, microbiology, particulate contamination, Ph. Eur., pharmacopoeia, residual solvents, sterile products, sterility, WFI

2. Execution modes

PreservativeEfficacyValidator.exe                            → демо-режим (вывод в консоль)
PreservativeEfficacyValidator.exe input.csv output.json      → оценка ваших данных

3. Key controlled areas

• residual solvents
• microbiology and pathogens
• 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

ProductName,BatchNumber,ProductType,LogReduction_Bacteria_7days,LogReduction_YeastMold_7days,LogReduction_Bacteria_28days
MultiDose_EyeDrops,B20250110,MultiDoseInjectable,3.0,2.0,2.0

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": "PreservativeEfficacyValidator",
  "api": "Preservative Efficacy Validator",
  "batchNumber": "B20250110",
  "overallStatus": "PASS|WARNING|FAIL",
  "checkedAtUtc": "2026-05-18T00:00:00Z",
  "checks": [
    {
      "parameter": "ProductName",
      "value": "MultiDose_EyeDrops",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "BatchNumber",
      "value": "B20250110",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "ProductType",
      "value": "MultiDoseInjectable",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "LogReduction_Bacteria_7days",
      "value": "3.0",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "LogReduction_YeastMold_7days",
      "value": "2.0",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "LogReduction_Bacteria_28days",
      "value": "2.0",
      "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.