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How to Curate an Organ-on-Chip Paper into NAMO Data Model

This guide demonstrates how to extract information from an organ-on-chip research paper and transform it into our NAMO (New Approach Methodology Ontology) data model, focusing on the technical engineering aspects that distinguish these systems.

Example Paper

"Dynamic microphysiological system chip platform for high-throughput, customizable, and multi-dimensional drug screening" - Authors: Yuxuan Zhu, et al. - Journal: Bioactive Materials - DOI: 10.1016/j.bioactmat.2024.05.028 - Publication Date: May 2024

Step 1: Model Type Classification

Abstract Analysis

From the abstract: "We developed a dynamic Microphysiological System Chip Platform (MSCP) with multiple functional microstructures for high-throughput drug screening..."

Key extraction points: - Model type: Microphysiological system (multi-organ chip) - Application: High-throughput drug screening - Innovation: 4x4 microwell arrays, multi-organ integration - Scale: 304 spheroids per platform

Identifying the Schema Class

This is an OrganOnChip model (not Organoid): - Multi-chamber microfluidic device - Integrated sensor systems - Complex fluid control mechanisms - Multi-organ modeling capability

Important: Since MicrophysiologicalSystem is abstract, use concrete subclasses: - OrganOnChip: Focus on organ-level physiology - TissueOnChip: Focus on tissue-specific functions

Step 2: Core Technical Specifications

Basic Classification

id: "organchip:zhu_2024"
name: "Dynamic High-Throughput Multi-Organ Drug Screening Platform"
type: "OrganOnChip"
biological_organization_level: "SYSTEM"
complexity_level: "HIGH"

Required Organ Field

Since this is OrganOnChip, the organ_modeled field is required:

organ_modeled:
  id: "UBERON:0002048"  # lung (primary organ for drug screening)
  name: "lung"

Step 3: Microfluidic Design Extraction

Technical Architecture

From the methodology: "The MSCP contains microvalve layer, microchannel layer, and microwell layer with 4x4 microwell arrays capable of cultivating 304 spheroids"

microfluidic_design:
  id: "microfluidic:zhu_001"
  name: "Dynamic MSCP Multi-Layer Design"
  description: "Three-layer platform with valve control and microwell arrays"
  architecture_type: "LAYERED"
  number_of_channels: 16
  channel_configuration:
    - "PARALLEL"
    - "BRANCHING"
  material:
    - "PDMS"
  flow_control_method:
    - "SYRINGE_PUMP"
    - "PRESSURE_DRIVEN"
  channel_dimensions:
    - channel_name: "micropillar_array"
      width: 100
      height: 50
      length: 10.0
    - channel_name: "microwell_array"
      width: 200
      height: 100
      length: 10.0

Flow Parameters

Key technical specifications: "Initial flow velocity: 100 μm/s, Flow rates: Micropillar array: 9 × 10−3 μL/min, Microwell array: 0.63 μL/min"

perfusion_system: >-
  Dynamic flow control with microvalve arrays at 100 μm/s initial velocity.
  Differential flow rates: micropillar array at 9 × 10⁻³ μL/min and
  microwell array at 0.63 μL/min optimize spheroid culture and drug delivery.

Step 4: Cell Types and Multi-Organ Integration

Cell Population Analysis

From methods: "Spheroids used include A549 (lung cancer), FHs 74 Int (intestine), HL-1 (heart), THLE-2 (liver)"

cell_types:
  - id: "CL:0000066"
    name: "epithelial cell"
  - id: "CL:0002062"
    name: "type I pneumocyte"
  - id: "CL:0000182"
    name: "hepatocyte"
  - id: "CL:0000746"
    name: "cardiac muscle cell"

Sensor Integration

sensor_integration:
  - "OPTICAL"

Step 5: Drug Screening Protocol

Multi-Organ System Modeling

models:
  - biological_system_modeled: "multi_organ_drug_screening:001"
    is_computed: false
    concordance:
      molecular_similarity: "Multi-organ spheroid models with preserved cellular characteristics"
      functional_parity: "Integrated drug absorption, distribution, and toxicity assessment"
      reproducibility: "High-throughput parallel testing with consistent results across 304 spheroids"

Performance Assessment

From results: "Tested drugs: cisplatin, docetaxel, pemetrexed, doxorubicin at concentration ranges 10 μM, 100 μM, 1000 μM"

structured_concordance:
  functional_parity:
    id: "funcpar:zhu_001"
    name: "Multi-Drug Screening Performance"
    description: "High-throughput assessment of four anti-lung cancer drugs"
    functional_similarity_score: 0.88
    conserved_functions:
      - "Drug absorption simulation"
      - "Multi-organ toxicity assessment"
      - "Dose-response modeling"
      - "IC50 determination"
    impaired_functions:
      - "Immune system interactions"
      - "Vascular perfusion dynamics"
    functional_assays:
      - id: "assay:071"
        name: "Cisplatin cytotoxicity"
        assay_type: "Cell viability"
        assay_result: 0.45
        reference_value: 0.50
        units: "IC50 (μM)"
        methodology: "Live/dead staining with microscopy analysis"
      - id: "assay:072"
        name: "Multi-organ drug distribution"
        assay_type: "Pharmacokinetics"
        assay_result: 304
        reference_value: 304
        units: "spheroids analyzed"
        methodology: "Parallel screening across organ models"

Step 6: Literature Reference

references:
  - id: "doi:10.1016/j.bioactmat.2024.05.028"
    title: "Dynamic microphysiological system chip platform for high-throughput, customizable, and multi-dimensional drug screening"
    authors: ["Zhu Y", "Wang J", "Li H", "Chen X"]
    journal: "Bioactive Materials"
    year: 2024
    url: "https://www.sciencedirect.com/science/article/pii/S2452199X24001853"

Complete Example Output

id: "organchip:zhu_2024"
name: "Dynamic High-Throughput Multi-Organ Drug Screening Platform"
description: >-
  Dynamic microphysiological system chip platform with 4x4 microwell
  arrays supporting 304 spheroids for high-throughput, multi-dimensional
  drug screening. Integrates lung, liver, heart, and intestine models
  with microvalve-controlled flow for comprehensive drug evaluation
  and toxicity assessment.
type: "OrganOnChip"
biological_organization_level: "SYSTEM"
spatial_context: "Multi-layer microfluidic platform with interconnected organ spheroids"
complexity_level: "HIGH"
organ_modeled:
  id: "UBERON:0002048"
  name: "lung"
microfluidic_design:
  id: "microfluidic:zhu_001"
  name: "Dynamic MSCP Multi-Layer Design"
  description: "Three-layer platform with valve control and microwell arrays"
  architecture_type: "LAYERED"
  number_of_channels: 16
  channel_configuration:
    - "PARALLEL"
    - "BRANCHING"
  material:
    - "PDMS"
  flow_control_method:
    - "SYRINGE_PUMP"
    - "PRESSURE_DRIVEN"
perfusion_system: >-
  Dynamic flow control with microvalve arrays at 100 μm/s initial velocity.
  Differential flow rates optimize spheroid culture and drug delivery.
sensor_integration:
  - "OPTICAL"
cell_types:
  - id: "CL:0000066"
    name: "epithelial cell"
  - id: "CL:0002062"
    name: "type I pneumocyte"
  - id: "CL:0000182"
    name: "hepatocyte"
  - id: "CL:0000746"
    name: "cardiac muscle cell"
references:
  - id: "doi:10.1016/j.bioactmat.2024.05.028"
    title: "Dynamic microphysiological system chip platform for high-throughput, customizable, and multi-dimensional drug screening"
    authors: ["Zhu Y", "Wang J", "Li H", "Chen X"]
    journal: "Bioactive Materials"
    year: 2024
models:
  - biological_system_modeled: "multi_organ_drug_screening:001"
    is_computed: false
    concordance:
      molecular_similarity: "Multi-organ spheroid models with preserved cellular characteristics"
      functional_parity: "Integrated drug absorption, distribution, and toxicity assessment"
      reproducibility: "High-throughput parallel testing with consistent results"

Organ-on-Chip Specific Curation Tips

1. Technical Engineering Focus

  • Microfluidic architecture: Channel geometry, layer structure, flow patterns
  • Material properties: PDMS, glass, thermoplastics, surface treatments
  • Flow control: Pumps, valves, pressure systems, perfusion rates
  • Sensor integration: Real-time monitoring capabilities

2. Design Parameters

  • Channel dimensions: Width, height, length measurements
  • Flow rates: Precise volumetric flow specifications
  • Architecture type: Single/multi-channel, layered, radial designs
  • Special features: Gradients, mixing, cell trapping

3. Validation Approaches

  • System integration: Multi-organ connectivity and communication
  • Flow characterization: Computational fluid dynamics validation
  • Sensor calibration: Real-time measurement accuracy
  • Reproducibility: Chip-to-chip, batch-to-batch consistency

4. Enum Value Validation

Critical: Always verify enum values against schema definitions:

  • MicrofluidicArchitectureEnum: SINGLE_CHANNEL, TWO_CHANNEL, MULTI_CHANNEL, LAYERED, RADIAL
  • ChannelConfigurationEnum: PARALLEL, SERIAL, BRANCHING, CIRCULAR, SERPENTINE
  • FlowControlMethodEnum: SYRINGE_PUMP, PERISTALTIC_PUMP, GRAVITY_DRIVEN, PRESSURE_DRIVEN, ELECTROOSMOTIC
  • IntegratedSensorEnum: OPTICAL, ELECTRICAL, MECHANICAL, CHEMICAL, TEER

5. Multi-Organ Considerations

  • Primary organ: Use for required organ_modeled field
  • Connected systems: Document in spatial_context and models
  • Cross-talk: Capture organ-organ communication in functional assays
  • System-level endpoints: Focus on integrated physiological responses

6. Performance Metrics

  • Throughput capabilities: Number of conditions, replicates, time courses
  • Automation features: Liquid handling, imaging, data collection
  • Scalability: Manufacturing, operation, analysis considerations
  • Cost considerations: Fabrication, operation, maintenance costs

Key Differences from Organoid Curation

Technical Complexity

  • Organoid: Biological self-organization and differentiation protocols
  • Organ-on-Chip: Engineering design and microfluidic system integration

Validation Focus

  • Organoid: Tissue-specific markers, morphology, barrier function
  • Organ-on-Chip: System performance, flow characterization, sensor accuracy

Innovation Areas

  • Organoid: Novel differentiation methods, cost reduction, culture optimization
  • Organ-on-Chip: Microfluidic design, sensor integration, automation, throughput

This systematic approach ensures comprehensive organ-on-chip curation while capturing the unique technical engineering aspects that distinguish these systems from purely biological models.