MannitolQualityChecker

Mannitol

antivirals API biologics dissolution essential medicines global market heavy metals impurities

Mannitol Quality Checker — Sugar Alcohol (Ph. Eur., USP)

ℹ️ The utility checks assay, sorbitol/glucose, water, dissolution profile.
ℹ️ Does not use machine learning — rule-based logic only.
⚠️ CRITICAL! Sorbitol ≤0.5%. Glucose ≤0.5%. Water ≤10000 ppm!

Usage:
MannitolQualityChecker.exe → demo mode
MannitolQualityChecker.exe input.csv output.json → evaluate data

Input format:
BatchNumber,Assay_Percent,Melting_Point_Min,Melting_Point_Max,Sorbitol_Percent,Glucose_Percent,Total_Impurities_Percent,Loss_On_Drying_Percent,Residual_Solvent_Ethanol_ppm,Residual_Solvent_Water_ppm,Heavy_Metals_ppm,Sulfated_Ash_Percent,Dissolution_30min_Percent,Dissolution_60min_Percent,Weight_Variation_RSD,Friability_Percent,Microbial_Count_TAMC,Microbial_Count_TYMC,EColi_Detected,Salmonella_Detected

Example:
MAN-SUB-2026-001,99.5,166,169,0.2,0.1,0.3,0.3,800,2000,5,0.05,0.0,0.0,0.0,0.0,20,5,0,0

— WHY IS THIS NEEDED?
Mannitol — sugar alcohol used as a tablet excipient, injectable solvent, and osmotic diuretic:
• Synthesis Impurities: Main impurities are sorbitol (isomer) and glucose (reduction product of mannose). Control of these is critical to ensure substance purity.
• Moisture: Mannitol is hygroscopic. Water control is important for stability and technological properties (powder flow). Limits can be higher than for other substances (up to 1%).
• Synthesis often involves ethanol and water. Limits for residual solvents are strict.
• Dissolution profile is important for ensuring rapid bioavailability.
⚠️ CRITICAL:
• Assay: 98–102%
• Melting Point: 165–170°C (with decomposition)
• Sorbitol: ≤ 0.5%
• Glucose: ≤ 0.5%
• Total Impurities: ≤ 1.0%
• Water: ≤ 1.0% (or 10000 ppm)
• Ethanol: ≤ 5000 ppm
• Heavy Metals: ≤ 10 ppm
• Dissolution: ≥ 80% in 30 min, ≥ 85% in 60 min
• Microbiology: standard limits
⚠️ Note: Utility adapted for dissolution profile check. If dissolution data absent (0), check skipped (for substance). For finished forms, deviation from dissolution profile is critical defect. Sorbitol and glucose control is a safety priority due to their potential impact on osmolarity and drug stability.
```

input.csv

BatchNumber,Assay_Percent,Melting_Point_Min,Melting_Point_Max,Sorbitol_Percent,Glucose_Percent,Total_Impurities_Percent,Loss_On_Drying_Percent,Residual_Solvent_Ethanol_ppm,Residual_Solvent_Water_ppm,Heavy_Metals_ppm,Sulfated_Ash_Percent,Dissolution_30min_Percent,Dissolution_60min_Percent,Weight_Variation_RSD,Friability_Percent,Microbial_Count_TAMC,Microbial_Count_TYMC,EColi_Detected,Salmonella_Detected
MAN-SUB-2026-001,99.5,166,169,0.2,0.1,0.3,0.3,800,2000,5,0.05,0.0,0.0,0.0,0.0,20,5,0,0

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.

Utility: MannitolQualityCheckerAPI / object: MannitolCategory: Global API expansion

1. Scope

The Mannitol Quality Checker utility is used for Mannitol. 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: Global API expansion

Tags: antivirals, API, biologics, dissolution, essential medicines, global market, heavy metals, impurities, medical gases, microbiology, oncology, residual solvents

2. Execution modes

MannitolQualityChecker.exe                            → demo mode
MannitolQualityChecker.exe input.csv output.json      → evaluate data

3. Key controlled areas

assay / content
dissolution / disintegration
residual solvents
microbiology and pathogens
heavy metals / elemental impurities
pH and physicochemical parameters

4. Domain limits and critical parameters

⚠️ CRITICAL! Sorbitol ≤0.5%. Glucose ≤0.5%. Water ≤10000 ppm!
⚠️ CRITICAL:
Assay: 98–102%
Melting Point: 165–170°C (with decomposition)
Sorbitol: ≤ 0.5%
Glucose: ≤ 0.5%
Total Impurities: ≤ 1.0%
Water: ≤ 1.0% (or 10000 ppm)
Ethanol: ≤ 5000 ppm
Heavy Metals: ≤ 10 ppm
Dissolution: ≥ 80% in 30 min, ≥ 85% in 60 min
Microbiology: standard limits
⚠️ Note: Utility adapted for dissolution profile check. If dissolution data absent (0), check skipped (for substance). For finished forms, deviation from dissolution profile is critical defect. Sorbitol and glucose control is a safety priority due to their potential impact on osmolarity and drug stability.

Limits stated in the description must be verified against the current approved specification, pharmacopoeial monograph and registration dossier before production use.

5. URS — user requirements

ID	Requirement	Criticality	Acceptance criterion
URS-001	The system shall accept an `input.csv` file for Mannitol 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: assay / content, dissolution / disintegration, residual solvents, microbiology and pathogens, 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	`BatchNumber`	identifier	as specified	Batch Number	`MAN-SUB-2026-001`	mandatory field; used for batch/lot traceability
2	`Assay_Percent`	decimal	%	Assay %	`99.5`	numeric value; compared with assay/purity limit from specification or method
3	`Melting_Point_Min`	decimal	°C	Melting Point Min	`166`	mandatory numeric value; rule comparison is performed by the utility
4	`Melting_Point_Max`	decimal	°C	Melting Point Max	`169`	mandatory numeric value; rule comparison is performed by the utility
5	`Sorbitol_Percent`	decimal	%	Sorbitol %	`0.2`	mandatory numeric value; rule comparison is performed by the utility
6	`Glucose_Percent`	decimal	%	Glucose %	`0.1`	mandatory numeric value; rule comparison is performed by the utility
7	`Total_Impurities_Percent`	decimal	%	Total Impurities %	`0.3`	mandatory numeric value; rule comparison is performed by the utility
8	`Loss_On_Drying_Percent`	decimal	%	Loss On Drying %	`0.3`	mandatory numeric value; rule comparison is performed by the utility
9	`Residual_Solvent_Ethanol_ppm`	decimal	ppm	Residual Solvent Ethanol ppm	`800`	numeric value; checked as residual solvent against the applicable limit
10	`Residual_Solvent_Water_ppm`	decimal	ppm	Residual Solvent Water ppm	`2000`	numeric value; checked as residual solvent against the applicable limit
11	`Heavy_Metals_ppm`	decimal	ppm	Heavy Metals ppm	`5`	numeric value; checked as elemental/metal impurity
12	`Sulfated_Ash_Percent`	decimal	%	Sulfated Ash %	`0.05`	mandatory numeric value; rule comparison is performed by the utility
13	`Dissolution_30min_Percent`	decimal	%	Dissolution 30min %	`0.0`	numeric value; dissolution/disintegration profile checked according to method
14	`Dissolution_60min_Percent`	decimal	%	Dissolution 60min %	`0.0`	numeric value; dissolution/disintegration profile checked according to method
15	`Weight_Variation_RSD`	decimal	as specified	Weight Variation RSD	`0.0`	mandatory numeric value; rule comparison is performed by the utility
16	`Friability_Percent`	decimal	%	Friability %	`0.0`	mandatory numeric value; rule comparison is performed by the utility
17	`Microbial_Count_TAMC`	decimal	as specified	Microbial Count TAMC	`20`	numeric value; compared with microbiological limits
18	`Microbial_Count_TYMC`	decimal	as specified	Microbial Count TYMC	`5`	numeric value; compared with microbiological limits
19	`EColi_Detected`	boolean / flag	0/1	EColi Detected	`0`	valid flag required; prohibited organisms and growth are normally expected as 0 / absent
20	`Salmonella_Detected`	boolean / flag	0/1	Salmonella Detected	`0`	valid flag required; prohibited organisms and growth are normally expected as 0 / absent

CSV example

BatchNumber,Assay_Percent,Melting_Point_Min,Melting_Point_Max,Sorbitol_Percent,Glucose_Percent,Total_Impurities_Percent,Loss_On_Drying_Percent,Residual_Solvent_Ethanol_ppm,Residual_Solvent_Water_ppm,Heavy_Metals_ppm,Sulfated_Ash_Percent,Dissolution_30min_Percent,Dissolution_60min_Percent,Weight_Variation_RSD,Friability_Percent,Microbial_Count_TAMC,Microbial_Count_TYMC,EColi_Detected,Salmonella_Detected
MAN-SUB-2026-001,99.5,166,169,0.2,0.1,0.3,0.3,800,2000,5,0.05,0.0,0.0,0.0,0.0,20,5,0,0

7. FS — functional specification

ID	Function	Implementation description
FS-001	CLI entry point	The executable `MannitolQualityChecker.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 Mannitol, 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": "MannitolQualityChecker",
  "api": "Mannitol",
  "batchNumber": "MAN-SUB-2026-001",
  "overallStatus": "PASS|WARNING|FAIL",
  "checkedAtUtc": "2026-05-18T00:00:00Z",
  "checks": [
    {
      "parameter": "BatchNumber",
      "value": "MAN-SUB-2026-001",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Assay_Percent",
      "value": "99.5",
      "unit": "%",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Melting_Point_Min",
      "value": "166",
      "unit": "°C",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Melting_Point_Max",
      "value": "169",
      "unit": "°C",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Sorbitol_Percent",
      "value": "0.2",
      "unit": "%",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Glucose_Percent",
      "value": "0.1",
      "unit": "%",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Total_Impurities_Percent",
      "value": "0.3",
      "unit": "%",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "Loss_On_Drying_Percent",
      "value": "0.3",
      "unit": "%",
      "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.
TC-005	Positive pathogen/microbiological flag or microbiological limit excursion	Critical FAIL is produced with the offending parameter.
TC-006	Insufficient dissolution or excessive disintegration time	FAIL/WARNING is produced according to method criticality.
TC-007	Residual solvent above applicable limit	FAIL is produced with solvent name and measured value.

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.

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