Purpose

Define user requirements for a standalone FUZKK utility that accepts laboratory CSV data, evaluates the records using limits embedded in code, and produces LabWare-compatible JSON.

Scope

The utility is intended for preliminary QC/QA review, integration testing, LIMS/LabWare flow and evidence-trail preparation. Final release decisions remain under the laboratory's validated procedure and responsible personnel.

Users

QC analyst, QA reviewer, CSV/validation engineer, LIMS/LabWare integration engineer, responsible laboratory specialist.

User requirements

1. The utility shall run without arguments and print its self-description, a built-in input.csv example from GetDemoData(), and demo evaluation for the embedded records.
2. The utility shall run with two arguments: input.csv output.json.
3. The utility shall not read input.csv and shall not write output.json when started without arguments.
4. CSV numeric values shall be parsed using CultureInfo.InvariantCulture.
5. Output shall be generated as LabWare-compatible JSON with Header, Samples, Results, Status, StatusCode, ErrorMessage, Description and DescriptionEN.
6. For PASS records, ErrorMessage shall be an empty string.
7. Embedded limits shall follow this priority: Ph. Eur. → British Pharmacopoeia / UK implementation → EAEU / regional requirements → EMA/ICH/EU guidance → USP fallback.
8. If an exact monograph is not known, strict standard API limits are used where applicable: assay 98–102%, total impurities ≤1.0%, individual impurity ≤0.5%.
9. For biologics and mAb-like products, aggregation, sterility and endotoxin checks shall be included where relevant to the utility purpose.
10. If a parameter may arrive in different units, the unit shall be represented as a separate input field or explicitly reflected in the input.csv field name.

Input CSV

BatchNumber,ProductName,dsRNA_Concentration_ng_ml,Total_mRNA_Concentration_ng_ml,StandardCurve_R2,LOD_ng_ml,LOQ_ng_ml,CV_Percent
MRNA-DS-2026-001,SARS-CoV-2 Spike mRNA,150.0,10000.0,0.998,10.0,30.0,6.5
MRNA-DS-2026-002,Flu HA mRNA,50.0,8000.0,0.995,10.0,30.0,8.0
MRNA-DS-2026-003,Therapeutic Enzyme mRNA,500.0,5000.0,0.992,10.0,30.0,12.0

input.csv fields

Utility description

mRNA Residual dsRNA Quantifier — Quantitative analysis of residual double-stranded RNA

mRNA Residual dsRNA Quantifier — Quantitative analysis of residual double-stranded RNA

ℹ️ Utility controls levels of immunogenic dsRNA impurities:
• % dsRNA of total RNA mass (≤3.0%)
• Absolute dsRNA concentration
• Calibration curve quality (R²)
• Method variability (CV)

⚠️ CRITICAL: dsRNA activates RIG-I/MDA5 receptors!
This leads to inflammation and suppression of target protein translation.

Usage:
mRNAResidualdsRNAQuantifier.exe → demo mode (console output)
mRNAResidualdsRNAQuantifier.exe input.csv output.json → evaluate your data

Input format:
BatchNumber,ProductName,dsRNA_Concentration_ng_ml,Total_mRNA_Concentration_ng_ml,StandardCurve_R2,LOD_ng_ml,LOQ_ng_ml,CV_Percent

Example:
MRNA-DS-2026-001,SARS-CoV-2 Spike mRNA,150.0,10000.0,0.998,10.0,30.0,6.5

— WHY IS THIS NEEDED?
dsRNA control is critical for mRNA drug safety (Moderna, BioNTech, CureVac):
• Double-stranded RNA (dsRNA) is formed as a byproduct during enzymatic synthesis (IVT)
• dsRNA is a potent trigger of innate immune response (via RIG-I, MDA5, PKR pathways)
• Immune activation leads to interferon production, blocking mRNA translation and causing patient inflammation
• Regulators require strict control and minimization of this impurity type

⚠️ CRITICAL:
• dsRNA level ≤3.0% (often targeting <1% or even <0.1%) of total RNA mass
• Absolute concentration must be below established safety threshold
• Method must have low limit of detection (LOD) and quantification (LOQ)
• High calibration quality (R² ≥0.99) is mandatory for accuracy
• Low variability (CV ≤15%) ensures reproducibility

Key features:
• Calculation of dsRNA percentage relative to total mRNA
• Compliance check with strict regulatory limits
• Analytical method quality control (ELISA/J2 antibody or fluorescence)
• Immunogenicity risk assessment based on impurity level

Critical parameters:
• % dsRNA: ≤3.0% (target <1%)
• Calibration R²: ≥0.99
• CV: ≤15%
• Concentration: Above LOQ

💡 Usage tips:
1. Use specific antibodies (e.g., J2) or enzymes (RNase III) for detection
2. Thoroughly purify mRNA by LiCl precipitation or chromatography to reduce dsRNA
3. Perform analysis at different purification stages to monitor efficiency
4. Compare dsRNA levels with cell-based assay data (interferon correlation)
5. For therapeutic mRNA, requirements may be stricter than for vaccines

⚠️ Note: Unlike other impurities, dsRNA does not significantly change molecule mass but drastically changes its biological behavior. Even trace amounts can cause strong immune response. The utility helps ensure the product acts as a medicine, not an immunostimulant.

Traceability and limitations

• The URS is used as the source document for functional specification, CSV review and later validation work.
• This document does not replace an approved pharmacopoeial monograph, validated analytical method or internal product specification.
• For product-specific limits, the approved customer specification takes priority.

The functional specification describes the behaviour of the standalone FUZKK console utility, input-data format, evaluation algorithm and output JSON structure.

Functional flow

1. Main() checks the number of arguments.
2. If no arguments are provided: PrintHello() prints the description and built-in input.csv example, then RunDemoEvaluation() executes Evaluate() over GetDemoData() and prints demo JSON.
3. If two arguments are provided: RunWithFiles(input.csv, output.json) reads CSV, evaluates each record and writes LabWare-compatible JSON.
4. LoadData() uses CultureInfo.InvariantCulture and shall not be called in no-arguments mode.
5. Evaluate() returns a named tuple with BatchNumber, ProductName, Parameters, CriticalFailCount, WarningCount, Recommendation and RecommendationEN.
6. GetIssues() builds messages for ErrorMessage in WARNING/FAIL cases.

Evaluation rules

• PASS: CriticalFailCount = 0 and WarningCount = 0.
• WARNING: CriticalFailCount = 0 and WarningCount > 0.
• FAIL: CriticalFailCount > 0.
• ERROR: exception during reading or processing.
• ErrorMessage remains empty for PASS.
• Limits are embedded in Program.cs; no external limit configuration is required.

Input and fields

BatchNumber,ProductName,dsRNA_Concentration_ng_ml,Total_mRNA_Concentration_ng_ml,StandardCurve_R2,LOD_ng_ml,LOQ_ng_ml,CV_Percent
MRNA-DS-2026-001,SARS-CoV-2 Spike mRNA,150.0,10000.0,0.998,10.0,30.0,6.5
MRNA-DS-2026-002,Flu HA mRNA,50.0,8000.0,0.995,10.0,30.0,8.0
MRNA-DS-2026-003,Therapeutic Enzyme mRNA,500.0,5000.0,0.992,10.0,30.0,12.0

Output JSON

{
  "Header": {
    "UtilityName": "mRNA_Residual_dsRNA_Quantifier",
    "Version": "1.0.0",
    "Timestamp": "UTC",
    "InstrumentID": "FUZKK-QC-WORKSTATION",
    "OperatorID": "Admin"
  },
  "Samples": [
    {
      "SampleID": "from BatchNumber",
      "BatchNumber": "from CSV",
      "ProductName": "from CSV",
      "TestName": "utility-specific test",
      "AnalysisCode": "utility-specific code",
      "Status": "PASS | WARNING | FAIL | ERROR",
      "StatusCode": "1 | 2 | 0 | -1",
      "ErrorMessage": "",
      "Description": "Russian recommendation",
      "DescriptionEN": "English recommendation",
      "Results": [
        {
          "ParameterName": "parameter",
          "ResultValue": 0.0,
          "UnitOfMeasure": "unit",
          "SpecificationLimit": "limit",
          "IsWithinSpec": true
        }
      ]
    }
  ]
}