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,ADCName,AverageDAR,DAR_Heterogeneity_Index,Percent_DAR0,Percent_DAR2,Percent_DAR4,Percent_DAR6,Percent_DAR8Plus,HydrophobicityScore
ADC-DAR-2026-001,Trastuzumab-Deruxtecan,7.7,1.2,1.5,5.0,15.0,30.0,8.5,3.8
ADC-DAR-2026-002,Sacituzumab-Govitecan,7.6,1.3,2.0,6.0,14.0,28.0,9.0,3.5
ADC-DAR-2026-003,Polatuzumab-Vedotin,3.5,0.8,1.0,10.0,40.0,35.0,2.0,2.1

input.csv fields

Utility description

ADC Drug-Antibody Ratio Analyzer — ADC DAR Analyzer

ADC Drug-Antibody Ratio Analyzer — ADC DAR Analyzer

ℹ️ Utility analyzes toxin loading profile on antibody:
• Average DAR (target ±0.5)
• Heterogeneity index (≤1.5)
• Unconjugated antibody DAR0 (≤5%)
• High load DAR8+ (≤10%)
• Hydrophobicity score

⚠️ CRITICAL: Wide DAR distribution reduces therapy reproducibility!
DAR0 reduces efficacy, DAR8+ increases toxicity.

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

Input format:
BatchNumber,ADCName,AverageDAR,DAR_Heterogeneity_Index,Percent_DAR0,Percent_DAR2,Percent_DAR4,Percent_DAR6,Percent_DAR8Plus,HydrophobicityScore

Example:
ADC-DAR-2026-001,Trastuzumab-Deruxtecan,7.7,1.2,1.5,5.0,15.0,30.0,8.5,3.8

— WHY IS THIS NEEDED?
DAR (Drug-Antibody Ratio) is a key quality parameter for ADCs (Hengrui, BeiGene, Hansoh):
• Determines balance between efficacy (more toxin) and safety/stability (less toxin)
• DAR heterogeneity (0-8 distribution) affects pharmacokinetics and clearance
• High DAR (>8) often leads to rapid elimination due to aggregation and liver uptake
• Low DAR (<2) does not provide therapeutic effect

⚠️ CRITICAL:
• Average DAR must match platform specification (e.g., 3.5 for MMAE, 7.7 for DXd)
• Heterogeneity index ≤1.5 — ensures batch reproducibility
• DAR0 (unconjugated antibody) ≤5% — otherwise drug competes with active forms for target
• DAR8+ (overloaded forms) ≤10% — main source of aggregates and toxicity
• Hydrophobicity directly correlates with DAR: higher DAR means higher hydrophobicity and clearance risk

Key features:
• Analysis of DAR distribution by individual forms (0, 2, 4, 6, 8+)
• Assessment of conjugation process heterogeneity
• Control of distribution "tails" (DAR0 and DAR8+)
• Correlation with hydrophobicity

Critical parameters:
• Average DAR: Target ±0.5
• Heterogeneity index: ≤1.5
• DAR0: ≤5.0%
• DAR8+: ≤10.0%

💡 Usage tips:
1. Use HIC-HPLC or MS for accurate separation of forms by DAR
2. For enzymatic conjugation (e.g., Transglutaminase), distribution is narrower than for chemical (maleimide)
3. Control DAR0 at purification stage (flow-through mode)
4. High heterogeneity index may indicate issues with conjugation reaction or purification
5. Compare DAR profiles of different batches to ensure process consistency (PPQ)

⚠️ Note: Unlike small molecules, ADCs are a mixture of molecules with different toxin counts. Managing this distribution (DAR profile) is the main technological challenge in ADC development. Chinese companies are actively moving to site-specific conjugation technologies to narrow DAR distribution.

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,ADCName,AverageDAR,DAR_Heterogeneity_Index,Percent_DAR0,Percent_DAR2,Percent_DAR4,Percent_DAR6,Percent_DAR8Plus,HydrophobicityScore
ADC-DAR-2026-001,Trastuzumab-Deruxtecan,7.7,1.2,1.5,5.0,15.0,30.0,8.5,3.8
ADC-DAR-2026-002,Sacituzumab-Govitecan,7.6,1.3,2.0,6.0,14.0,28.0,9.0,3.5
ADC-DAR-2026-003,Polatuzumab-Vedotin,3.5,0.8,1.0,10.0,40.0,35.0,2.0,2.1

Output JSON

{
  "Header": {
    "UtilityName": "ADC_DrugAntibodyRatio_Analyzer",
    "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
        }
      ]
    }
  ]
}