LossOnDryingQualityChecker
Loss On Drying
LabEx laboratory QC CSV→JSON URS & FS utilities / cleanroom
Open selectionLoss On Drying Quality Checker — Control of Loss on Drying (LOD) ℹ️ Utility checks compliance of loss on drying with pharmacopoeial requirements (Ph. Eur. 2.2.32 / USP <731>): • Measured LOD must be ≤ specified upper limit. • Accounts for method parameters: temperature and drying time. ⚠️ CRITICAL: Exceeding LOD limit indicates excessive moisture or residual solvents! This can affect powder flowability, stability, and compressibility. Usage: LossOnDryingQualityChecker.exe → demo mode (console output) LossOnDryingQualityChecker.exe input.csv output.json → evaluate your data Input format: BatchNumber,LODPercent,UpperLimitPercent,TemperatureC,DurationHours Example: LOD-API-2026-001,0.35,0.50,105.0,3.0 — WHY IS THIS NEEDED? Loss on Drying (LOD) is a standard test for determining volatile content (water, solvents). • Important for quality control of APIs and excipients (especially hygroscopic ones). • Excess moisture can cause API hydrolysis or powder caking. • Method is gravimetric and requires precise weighing before and after drying. • Automation eliminates manual comparison errors with limits. ⚠️ CRITICAL: • Drying temperature must strictly follow the method (risk of decomposition if overheated). • Drying time must be sufficient to reach constant mass. • For thermally unstable substances, use Karl Fischer (KF) titration for water determination. • LOD determines the sum of all volatiles, not just water. Key features: • Rapid specification compliance check. • Support for moisture analyzers and drying ovens. • Generation of PASS/FAIL status for LIMS. Critical parameters: • LOD: <= Upper Limit (e.g., 0.5%) 💡 Usage tips: 1. Use pre-dried and cooled crucibles/dishes. 2. Spread sample in a thin layer for uniform drying. 3. Cool sample in a desiccator before final weighing. 4. Regularly calibrate balances and check oven temperature. 5. If LOD is critical, consider using a more specific method (KF). ⚠️ Note: LOD does not distinguish between water and organic solvents. If water content specifically is important, use Karl Fischer titration.
input.csv
BatchNumber,LOD_Percent,UpperLimit_Percent,Temperature_C,Duration_Hours LOD-API-2026-001,0.35,0.50,105.0,3.0 LOD-EXC-2026-001,4.80,5.00,105.0,4.0 LOD-FAIL-2026-001,1.20,0.50,105.0,3.0
URS & FS — Loss On Drying
This document describes the user requirements and functional specification for LossOnDryingQualityChecker. The utility is intended for QC laboratory use as a rule-based check of data prepared from an instrument, LIMS, ELN, MES or an approved input.csv.
URS — User Requirements Specification
| ID | Requirement | Criticality | Acceptance criterion |
|---|---|---|---|
| URS-001 | The utility shall accept input.csv with approved columns: BatchNumber, LOD_Percent, UpperLimit_Percent, Temperature_C, Duration_Hours. | High | The CSV file is processed without manual header editing. |
| URS-002 | The utility shall perform deterministic evaluation for “Loss On Drying” without machine learning. | High | The same input data produce the same JSON result. |
| URS-003 | The utility shall validate mandatory fields, numeric formats, flags, ranges and domain plausibility. | High | Schema and conversion errors are explicitly reported. |
| URS-004 | The utility shall generate output.json with PASS / WARNING / FAIL statuses, source values, warnings and failures. | High | The JSON result is suitable for review, deviation investigation and integration. |
| URS-005 | The documentation shall support IQ/OQ/PQ or CSV/CSA verification. | Medium | URS/FS, CSV/JSON contract and test scenarios are supplied with the utility. |
input.csv contract
| # | Field | Sample | Purpose |
|---|---|---|---|
| 1 | BatchNumber | LOD-API-2026-001 | Input parameter for deterministic QC evaluation. |
| 2 | LOD_Percent | 0.35 | Input parameter for deterministic QC evaluation. |
| 3 | UpperLimit_Percent | 0.50 | Input parameter for deterministic QC evaluation. |
| 4 | Temperature_C | 105.0 | Input parameter for deterministic QC evaluation. |
| 5 | Duration_Hours | 3.0 | Input parameter for deterministic QC evaluation. |
FS — Functional Specification
| ID | Function | Implementation |
|---|---|---|
| FS-001 | CSV import | Read input.csv; validate header, column count and encoding. |
| FS-002 | Schema validation | Check required fields and permitted input values. |
| FS-003 | Rule engine | Apply domain rules, limits and system suitability/specification checks described in the source utility description. |
| FS-004 | Status aggregation | Produce final status: FAIL for critical failure, WARNING for non-critical deviation, PASS for conformance. |
| FS-005 | JSON export | Write machine-readable output.json for LIMS/ELN/MES and QA/QC review. |
OQ/PQ scenarios
- OQ-001: a valid sample row shall be processed without schema error.
- OQ-002: a missing mandatory column shall produce a schema error.
- OQ-003: a non-numeric value in a numeric field shall produce a conversion error.
- OQ-004: a critical parameter outside the limit shall produce
FAILor a critical finding. - PQ-001: user real batches shall be checked with retention of
input.csv,output.json, utility version and checksum.
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