ViscosityAnalyzer
Viscosity Analyzer
Viscosity Analyzer — Анализ вязкости (Ph. Eur. 2.2.8–2.2.10, 2.2.49)
ℹ️ Утилита проверяет соответствие вязкости требованиям Европейской фармакопеи.
ℹ️ Не использует машинное обучение — только правила.
Использование:
ViscosityAnalyzer.exe → демо-режим (вывод в консоль)
ViscosityAnalyzer.exe input.csv output.json → оценка ваших данных
Формат input.csv:
ProductName,BatchNumber,ProductType,Viscosity_mPa_s
Пример:
Artificial_Tears,B20250110,Ophthalmic,15.0
ProductType: Ophthalmic, Injectable, OralSolution, Topical
— ЗАЧЕМ ЭТО НУЖНО?
Вязкость — критический параметр качества:
• Для глазных капель — влияет на удержание на роговице,
• Для инъекций — на проходимость через иглу,
• Для сиропов и гелей — на дозирование и стабильность.
Отклонение может указывать на ошибку в формуле или деградацию.
Соответствие Ph. Eur. 2.2.8–2.2.10 обязательно для выпуска.
input.csv
ProductName,BatchNumber,ProductType,Viscosity_mPa_s Artificial_Tears,B20250110,Ophthalmic,15.0
URS & FS — user requirements and functional specification
This document defines user requirements and functional specification for the quality-control utility. It supports deployment discussion, IQ/OQ preparation and QC workflow integration.
1. Scope
The Viscosity Analyzer utility is used for Viscosity Analyzer. 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
Tags: heavy metals, microbiology, particulate contamination, Ph. Eur., pharmacopoeia, residual solvents
2. Execution modes
ViscosityAnalyzer.exe → демо-режим (вывод в консоль) ViscosityAnalyzer.exe input.csv output.json → оценка ваших данных
3. Key controlled areas
- residual solvents
- heavy metals / elemental impurities
- pH and physicochemical parameters
4. Domain limits and critical parameters
The source description does not contain a separate critical-limit list; rules implemented in the executable and defined by the CSV schema apply.
5. URS — user requirements
| ID | Requirement | Criticality | Acceptance criterion |
|---|---|---|---|
| URS-001 | The system shall accept an input.csv file for Viscosity Analyzer with the exact columns listed in the “Input data contract” section. | High | A file with the correct header is processed without manual editing; missing mandatory columns produce FAIL/import error. |
| URS-002 | The system shall support execution without arguments in demo mode and execution with input.csv output.json for user data. | Medium | Both execution scenarios produce a predictable result or clear diagnostic error. |
| URS-003 | The system shall perform rule-based controls for: residual solvents, heavy metals / elemental impurities, pH and physicochemical parameters. | High | Each controlled parameter receives a status and message; the result does not depend on hidden Excel formulas or ML. |
| URS-004 | The system shall preserve traceability between batch/lot, source values, applied rules and final verdict. | High | Output includes batch identifier, source values, parameter statuses and critical findings. |
| URS-005 | The system shall generate machine-readable output.json for LIMS/ELN/MES, batch record and QA/QC review. | High | JSON contains overall status, check array, warnings, failures and source-file reference. |
| URS-006 | The system shall support use in the client validation package: URS/FS, IQ/OQ preparation, installation and operational scenario checks. | High | The document, test scenarios and reproducible CSV/JSON flow are suitable for audit and internal approval. |
| URS-007 | The system shall clearly separate technical data errors from specification nonconformities. | Medium | Schema/type errors are not mixed with pharmacopoeial deviations and are reported separately. |
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.
| # | Column | Type | Unit | Description | Sample | Control rule |
|---|---|---|---|---|---|---|
| 1 | ProductName | identifier | as specified | Product Name | Artificial_Tears | mandatory value; format and acceptability are checked by the utility |
| 2 | BatchNumber | identifier | as specified | Batch Number | B20250110 | mandatory field; used for batch/lot traceability |
| 3 | ProductType | text | as specified | Product Type | Ophthalmic | mandatory value; format and acceptability are checked by the utility |
| 4 | Viscosity_mPa_s | decimal | as specified | Viscosity m Pa s | 15.0 | mandatory numeric value; rule comparison is performed by the utility |
CSV example
ProductName,BatchNumber,ProductType,Viscosity_mPa_s Artificial_Tears,B20250110,Ophthalmic,15.0
7. FS — functional specification
| ID | Function | Implementation description |
|---|---|---|
| FS-001 | CLI entry point | The executable ViscosityAnalyzer.exe supports demo mode and input.csv output.json processing mode. |
| FS-002 | CSV parser | The import module reads CSV, validates header, column presence/order, value count and encoding. Decimal values are expected with a dot separator. |
| FS-003 | Field conversion | Each column is converted to the expected type: identifier, text, decimal number, date/time or boolean flag. |
| FS-004 | Domain rule engine | For Viscosity Analyzer, explicit rules are applied: range, minimum, maximum, absence of prohibited flag, data completeness or calculation-based check. |
| FS-005 | Criticality handling | Critical violations produce FAIL; non-critical deviations and incomplete data produce WARNING; full conformance produces PASS. |
| FS-006 | JSON writer | output.json stores overall status, per-parameter results, source values, warnings, failures and diagnostic messages. |
| FS-007 | Integration contract | The CSV → JSON format is stable for invocation from LIMS/ELN/MES, scheduled task or wrapper service. |
| FS-008 | Error handling | Schema error, missing file, non-numeric value or JSON write failure returns diagnosable error without silent PASS. |
8. output.json contract
The output file must be suitable for automated processing, audit review and correlation with the source input.csv row.
{
"utility": "ViscosityAnalyzer",
"api": "Viscosity Analyzer",
"batchNumber": "B20250110",
"overallStatus": "PASS|WARNING|FAIL",
"checkedAtUtc": "2026-05-18T00:00:00Z",
"checks": [
{
"parameter": "ProductName",
"value": "Artificial_Tears",
"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": "Ophthalmic",
"unit": "as specified",
"status": "PASS|WARNING|FAIL",
"message": "Rule-based check result"
},
{
"parameter": "Viscosity_mPa_s",
"value": "15.0",
"unit": "as specified",
"status": "PASS|WARNING|FAIL",
"message": "Rule-based check result"
}
],
"criticalFindings": [],
"sourceFile": "input.csv"
}9. OQ/PQ test scenarios
| ID | Scenario | Expected result |
|---|---|---|
| TC-001 | Valid CSV with expected header and sample row | All rows are processed; output contains PASS/WARNING/FAIL and parameter-level detail. |
| TC-002 | A mandatory input.csv column is missing | Import is rejected or the row receives FAIL with schema reference. |
| TC-003 | A numeric field contains text or a blank value | Type conversion error is recorded; the result is not hidden as PASS. |
| TC-004 | A parameter is outside specification or critical limit | Critical parameters produce FAIL; non-critical deviations produce WARNING according to the rule. |
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.