namo
NAMO (New Approach Methodology Ontology) is a comprehensive schema for representing diverse in vitro and in silico model systems used as alternatives to traditional animal testing. It supports organoids, organ-on-chip systems, 3D cell cultures, computational models, and other New Approach Methodologies (NAMs) used in toxicology, drug discovery, and biomedical research.
Schema Organization
The schema follows a hierarchical structure that mirrors how NAM research is organized and conducted:
The top-level entity is a Dataset, which serves as a container for related research activities. A dataset might represent all NAM models from a specific laboratory, regulatory study, or collaborative research program.
Each dataset contains one or more Studies, which are focused investigations using specific NAM approaches. For example, a study might investigate "Hepatotoxicity screening using liver organoids" or "Multi-organ drug ADMET assessment using microphysiological systems."
Within each study, you'll find:
Model Systems
The core of NAMO is the representation of different NAM model types:
-
Organoids: Self-organizing 3D tissue models derived from stem cells that recapitulate organ-specific architecture and function. Examples include brain organoids for neurotoxicity testing, intestinal organoids for drug absorption studies, and liver organoids for metabolism research.
-
Organ-on-Chip Systems: Microfluidic devices that simulate organ-level physiology with precise control over cellular microenvironment. These include lung-on-chip for inhalation toxicology, heart-on-chip for cardiotoxicity assessment, and multi-organ chips for systemic drug effects.
-
Tissue-on-Chip Systems: Microfluidic models focused on specific tissue functions such as blood-brain barrier chips, skin models for dermatological testing, and kidney proximal tubule chips for nephrotoxicity screening.
-
3D Cell Cultures: Three-dimensional cell culture systems including spheroids, scaffold-based cultures, and bioengineered tissues that provide more physiologically relevant environments than traditional 2D cultures.
-
2D Cell Cultures: Monolayer cell culture systems with specialized configurations, substrates, and culture conditions optimized for specific applications.
-
Co-Culture Systems: Multi-cell-type culture systems that model cellular interactions, tissue interfaces, and organ-level communication pathways.
Computational Models
NAMO supports various in silico approaches:
-
Machine Learning Models: AI/ML systems for toxicity prediction, including deep learning models for chemical structure-activity relationships, neural networks for dose-response modeling, and ensemble methods for multi-endpoint prediction.
-
QSAR Models: Quantitative Structure-Activity Relationship models that predict biological activity from molecular structure, including traditional statistical approaches and modern machine learning implementations.
-
PBPK Models: Physiologically-based pharmacokinetic models that simulate drug absorption, distribution, metabolism, and excretion using mathematical representations of biological processes.
-
Digital Twins: Integrated computational models that combine multiple data sources and modeling approaches to create personalized, real-time simulations of biological systems.
-
Metabolic Models: Systems biology models of cellular metabolism, including flux balance analysis, kinetic modeling, and constraint-based approaches for understanding metabolic perturbations.
Technical Specifications
Microfluidic Design
For chip-based systems, detailed microfluidic design specifications capture device architecture, including channel configurations, flow control methods, sensor integration, and material properties essential for reproducibility and standardization.
Validation and Concordance
NAMO emphasizes validation through structured concordance analysis:
- Molecular Similarity: Gene expression profiles, protein markers, and metabolomic signatures compared to reference biological systems
- Functional Parity: Physiological responses, barrier functions, and cellular behaviors that match in vivo counterparts
- Reproducibility: Inter-laboratory consistency, batch-to-batch variation, and quality control metrics
Performance Metrics
Quantitative assessment through standardized functional assays that measure model performance, sensitivity, specificity, and predictive accuracy against known outcomes and regulatory endpoints.
Use Cases
NAMO supports diverse applications across multiple domains:
Regulatory Toxicology
- Chemical Safety Assessment: Systematic evaluation of chemical toxicity using integrated NAM approaches, supporting regulatory submissions to EPA, FDA, and ECHA
- Cosmetics Testing: Non-animal approaches for skin sensitization, eye irritation, and systemic toxicity assessment as required by regulations worldwide
- Pesticide Evaluation: Environmental and human health risk assessment using NAMs for neurotoxicity, endocrine disruption, and developmental toxicity endpoints
Pharmaceutical Development
- Drug Discovery: Early-stage compound screening using organ-specific models to identify promising candidates and eliminate toxic compounds
- ADMET Profiling: Absorption, Distribution, Metabolism, Excretion, and Toxicity assessment using integrated organ-on-chip platforms and computational models
- Precision Medicine: Patient-derived organoids and digital twins for personalized drug selection and dosing strategies
Academic Research
- Disease Modeling: Patient-specific organoids for studying rare diseases, cancer biology, and genetic disorders in controlled laboratory environments
- Mechanistic Studies: Investigation of toxicity pathways, cellular responses, and molecular mechanisms using well-characterized NAM systems
- Method Development: Innovation in NAM technologies, validation approaches, and standardization protocols
Key Features
- Multi-Modal Integration: Support for combining multiple NAM approaches in integrated testing strategies (ITS) and adverse outcome pathways (AOPs)
- Standardization Focus: Emphasis on reproducibility, quality control, and inter-laboratory harmonization essential for regulatory acceptance
- Literature Integration: Comprehensive reference system linking models to peer-reviewed publications, regulatory guidance, and validation studies
- Ontology Alignment: Integration with established ontologies including UBERON (anatomy), CL (cell types), CHEBI (chemicals), and OBI (biomedical investigations)
For detailed curation guidelines, see: - How to Curate Organoid Papers - How to Curate Organ-on-Chip Papers
Community and Standards
NAMO is developed in collaboration with the NAM research community, regulatory agencies, and standards organizations including OECD, ICCVAM, and ESTIV. It supports the 3Rs principles (Replacement, Reduction, Refinement) and contributes to the transition toward animal-free testing methodologies in safety assessment and biomedical research.
URI: https://w3id.org/monarch-initiative/namo
Name: namo
Classes
| Class | Description |
|---|---|
| CellRatio | Ratio specification for different cell types in co-culture systems |
| CellTypeProportion | Quantitative comparison of cell type proportions between systems |
| ChannelDimensions | Dimensions of a microfluidic channel according to ISO 10991:2023 definitions ... |
| ConcordanceResult | |
| CrossValidation | Cross-validation strategy and results for ML models |
| Dataset | |
| DoseResponseSimilarity | Comparison of dose-response relationships between model and biological system... |
| DrugProperties | Physicochemical and pharmacological properties of a drug in PBPK models |
| EnrichmentStatistics | Statistical measures for pathway enrichment analysis |
| ModelPerformance | Statistical performance metrics for computational models |
| ModelsRelationship | |
| NamedThing | A generic grouping for any identifiable entity |
| BiologicalSystem | |
| CellTypeCoverage | Assessment of cell type representation and cellular diversity between systems |
| FunctionalAssay | A functional assay used to assess biological capabilities |
| FunctionalParity | Evaluation of functional capabilities and physiological responses between sys... |
| Gene | A gene entity with identifiers and expression information |
| MechanicalStimulation | Specification of mechanical forces applied to the model system |
| MicrofluidicDesign | Detailed specification of a microfluidic device design including its architec... |
| ModelSystem | |
| AnimalModel | |
| NAMModel | A New Approach Methodology (NAM) model, which is a type of model system that ... |
| CellularSystem | Cell-based model systems that use living cells to model biological processes |
| CoCulture | Co-culture systems combining multiple cell types to mimic microenvironments ... |
| ThreeDCellCulture | Three-dimensional cell culture systems including spheroids and organoids |
| Organoid | A 3D cell culture system that self-organizes to recapitulate key structural a... |
| TwoDCellCulture | Conventional monolayer cell cultures grown on flat surfaces |
| CellLineModel | A model system based on immortalized cell lines that can be maintained in cul... |
| InSilicoModel | Computational models that simulate biological processes without physical biol... |
| DigitalTwin | Computational replicas of biological systems for real-time prediction and per... |
| MetabolicModel | A model that simulates the metabolic processes of an organism or system |
| MLModel | Machine Learning and AI-based models for prediction, mechanism inference, and... |
| PBPKModel | Physiologically Based Pharmacokinetic models that simulate drug absorption, ... |
| QSARModel | Quantitative Structure-Activity Relationship models that predict chemical/bi... |
| MicrophysiologicalSystem | Organ-/tissue-on-chip systems that integrate microfluidics, biomaterials, and... |
| OrganOnChip | A model system that simulates the physiological functions of an organ using a... |
| TissueOnChip | Tissue-level microphysiological systems that model specific tissue functions ... |
| MolecularSimilarity | Detailed assessment of molecular-level concordance between model and biologic... |
| Pathway | A biological pathway with activity and enrichment information |
| PathwayConcordance | Assessment of biological pathway conservation and activity between model and ... |
| PBPKCompartment | A physiological compartment in a PBPK model |
| PhenotypeOverlap | Comparison of phenotypic manifestations between model and biological systems |
| Reproducibility | Assessment of experimental reproducibility and consistency of the model syste... |
| Study | A study is a structured investigation or analysis, often involving the collec... |
| Term | A term is a concept or entity that can be defined and used in a specific cont... |
| QualityControlMetric | A quality control measure and its associated value |
| Reference | A literature reference with identifier and title for citing published work |
| StatisticalSignificance | Statistical measures of significance for molecular comparisons |
| StructuredConcordanceResult | Detailed structured assessment of concordance between model and biological sy... |
Slots
| Slot | Description |
|---|---|
| accuracy | Overall accuracy of the model (0 |
| active_pathways | List of biological pathways that are active in both systems |
| activity_endpoint | Biological activity or property being predicted |
| activity_score | Quantitative measure of pathway activity |
| adjusted_p_value | Multiple testing corrected p-value |
| age | The age of the animal used in the model system |
| architecture_type | The overall architecture type of the microfluidic device |
| assay_result | Quantitative result of the assay |
| assay_type | Type of functional assay (e |
| auc | Area under the ROC curve |
| authentication_method | Method used for cell line authentication (e |
| authors | Authors of the publication |
| barrier_functions | Tissue barrier functions modeled (epithelial, endothelial, etc |
| batch_to_batch_variation | Measure of variation between different experimental batches |
| biological_context | tissue/region (anatomy), cell types, sex/age equivalents, mechanics (e |
| biological_organization_level | The level of biological organization represented by the model |
| biological_proportion | Proportion of this cell type in the biological system |
| biological_specific_phenotypes | List of phenotypes present only in the biological system |
| biological_system_modeled | |
| blood_flow | Blood flow to the compartment (L/h) |
| cell_ratios | Ratios of different cell types in the co-culture |
| cell_source | Source of cells (e |
| cell_type | The cell type for which the ratio is specified |
| cell_type_coverage | |
| cell_type_proportions | Quantitative comparison of cell type proportions |
| cell_types | Cell types present in the cellular system |
| channel_configuration | Configuration of channels (e |
| channel_dimensions | Dimensions of the channels in the device |
| channel_name | Name or identifier of the channel (e |
| clearance | Total body clearance (L/h) |
| coculture_configuration | Configuration of co-culture (direct contact, transwell, conditioned media) |
| coefficient_of_variation | Coefficient of variation across experimental replicates |
| compartment_type | Type of physiological compartment |
| compartments | Physiological compartments included in the model |
| complexity_level | Level of biological complexity represented (subcellular, cellular, tissue, or... |
| compound_tested | Name of compound used in dose-response testing |
| computational_method | Primary computational method or algorithm used |
| concordance | Metrics used to assess the concordance between the model system and the biolo... |
| confidence_interval_lower | Lower bound of confidence interval |
| confidence_interval_upper | Upper bound of confidence interval |
| confluence_level | Typical confluence level maintained (0 |
| conserved_functions | List of biological functions conserved between model and biological system |
| conserved_genes | List of genes with conserved expression patterns between model and target |
| context_of_use | What decision will this inform? Care? Policy? Drug approval? |
| correlation_coefficient | Pearson correlation coefficient for expression profiles |
| coverage_percentage | Percentage of target cell types represented in the model system |
| cross_validation | Cross-validation strategy and results |
| culture_conditions | Standard culture conditions and media used |
| culture_system | Culture system used (e |
| cv_method | Type of cross-validation used |
| cv_score | Average cross-validation score |
| cv_std | Standard deviation of cross-validation scores |
| cyclic_stretch_percent | Percentage of cyclic stretch applied (if applicable) |
| data_source | Source of molecular data (e |
| description | A human-readable description for a thing |
| differentially_expressed_genes | List of genes that are differentially expressed in the model system |
| differentiation_method | Method used to differentiate cells into organoid (e |
| divergent_pathways | List of pathways that show different activity patterns |
| dose_response_similarity | Comparison of dose-response relationships for therapeutic compounds |
| drug_properties | Physicochemical and pharmacological properties modeled |
| duration_minutes | Duration of mechanical stimulation in minutes |
| ec50_ratio | Ratio of EC50 values between model and biological system |
| elimination_pathways | Drug elimination and metabolism pathways included |
| endpoints | phenotypes, function (TEER/leak, beating rate), and multi-omics |
| enrichment_score | Statistical enrichment score for the pathway |
| enrichment_statistics | Statistical measures of pathway enrichment |
| ensembl_id | Ensembl gene identifier |
| entrez_id | NCBI Entrez gene identifier |
| environment | The environmental conditions under which the animal model is maintained |
| feature_types | Types of features used (molecular, phenotypic, imaging, etc |
| flow_control_method | Methods used to control fluid flow in the device |
| fold_change | Fold change in expression compared to control or reference |
| frequency_hz | Frequency of mechanical stimulation in Hertz |
| functional_assays | List of functional assays used to assess parity |
| functional_parity | |
| functional_similarity_score | Quantitative score (0 |
| gene_symbol | Standard gene symbol (e |
| genes_in_dataset | Number of genes from dataset found in pathway |
| genes_in_pathway | Number of genes in the pathway |
| height | Height of the channel in micrometers |
| id | A unique identifier for a thing |
| impaired_functions | List of functions that are impaired or absent in the model system |
| inter_laboratory_consistency | Measure of consistency across different laboratories |
| interaction_mechanisms | Mechanisms of cell-cell interaction (paracrine, direct contact, mechanical) |
| interface_type | Type of interface(s) present in the device |
| is_computed | Indicates whether the model is computed or derived from experimental data |
| journal | Journal or publication venue |
| length | Length of the channel in millimeters |
| logp | Lipophilicity (log P) |
| material | Materials used to construct the device |
| matrix_composition | Composition of extracellular matrix or scaffold material |
| max_response_ratio | Ratio of maximum responses between systems |
| mechanical_forces | Mechanical forces applied to the model system |
| membrane_pore_size | Pore size of the membrane in micrometers |
| membrane_thickness | Thickness of the membrane in micrometers |
| membrane_type | Type of membrane used in the device if applicable |
| methodology | Description of experimental methods used for molecular comparison |
| metric_name | Name of the quality control metric |
| metric_value | Value of the quality control metric |
| microfluidic_design | Detailed design specifications of the microfluidic device |
| missing_cell_types | List of cell types present in biological system but missing in model |
| ml_algorithm | Type of machine learning algorithm used |
| model_interpretability | Level of model interpretability (black box, interpretable, explainable) |
| model_performance | Statistical performance metrics of the model |
| model_proportion | Proportion of this cell type in the model system |
| model_specific_phenotypes | List of phenotypes present only in the model system |
| model_systems | |
| models | |
| molecular_descriptors | Types of molecular descriptors used (topological, electronic, etc |
| molecular_similarity | |
| molecular_weight | Molecular weight (g/mol) |
| n_folds | Number of folds in cross-validation |
| name | A human-readable name for a thing |
| number_of_channels | Total number of channels in the device |
| organ_modeled | The organ or tissue being modeled |
| p_value | Statistical p-value for differential expression |
| partition_coefficient | Tissue-to-plasma partition coefficient |
| pass_fail_status | Whether this metric passes quality control criteria |
| passage_protocol | Standard passaging protocol and frequency |
| passage_range | Recommended passage number range for experimental use |
| pathway_analysis_method | Method used for pathway analysis (e |
| pathway_concordance | |
| pathway_database | Source database (e |
| pathway_id | Database-specific pathway identifier |
| pathway_overlap_score | Quantitative score (0 |
| perfusion_system | Description of perfusion and flow systems |
| personalization_parameters | Parameters used for personalization (genetic, phenotypic, etc |
| perturbations | exposure/dose/time; diet/drugs/toxicants |
| phenotype_ontology | Ontology used for phenotype classification (e |
| phenotype_overlap | |
| phenotype_similarity_score | Quantitative score (0 |
| pka | Acid dissociation constant |
| plan_comparators | human data, gold-standard assays, or high-quality animal references |
| prediction_scope | Scope and limitations of model predictions |
| pressure_pascal | Pressure applied in Pascals |
| proportion_ratio | Ratio of model to biological proportions |
| protein_binding | Fraction bound to plasma proteins (0 |
| q_value | False discovery rate corrected p-value |
| quality_control_metrics | List of quality control measures and their values |
| r_squared | R-squared value for regression models |
| ratio | Proportion or ratio of this cell type (0 |
| ratio_type | Type of ratio specification (percentage, absolute, fold) |
| real_time_data_sources | Sources of real-time data for model updating |
| reference_value | Reference or control value for comparison |
| references | Literature references that describe, validate, or support this model |
| replicate_count | Number of experimental replicates used in assessment |
| represented_cell_types | List of cell types present in both model and biological system |
| reproducibility | |
| reproducibility_score | Quantitative score (0 |
| rmse | Root mean square error |
| sensitivity | Sensitivity/recall of the model (0 |
| sensor_integration | Sensors integrated for real-time monitoring |
| sensors_integrated | Sensors integrated into the device for monitoring |
| shared_phenotypes | List of phenotypes present in both model and biological system |
| shear_stress | Shear stress applied in dyn/cm² |
| similarity_score | Quantitative similarity score (0 |
| single_cell_method | Method used for single-cell analysis (e |
| size_range | Typical size range of 3D structures |
| software_platform | Software platform or programming language used |
| spatial_context | Description of spatial organization and context captured by the model |
| special_features | Additional special features of the device (e |
| species | The species of the animal used in the model system |
| species_modeled | Species for which the model is designed |
| specificity | Specificity of the model (0 |
| statistical_significance | Statistical measures of significance for the molecular similarity |
| statistical_test | Name of statistical test used |
| stimulation_type | Type of mechanical stimulation applied |
| strain | The specific strain of the animal used in the model system |
| structured_concordance | Detailed structured assessment of concordance between the model system and th... |
| studies | |
| substrate_type | Type of culture substrate (e |
| surface_treatment | Surface treatments or coatings applied to the device |
| three_d_architecture | Type of 3D architecture (spheroid, organoid, scaffold-based, etc |
| threshold | Acceptable threshold for this metric |
| tissue_architecture | Description of tissue-level architecture and organization |
| tissue_modeled | The specific tissue being modeled |
| title | Title of the referenced publication or dataset |
| training_data_size | Size of training dataset |
| training_dataset_size | Number of compounds in training dataset |
| twin_scope | Scope of digital twin (organ, patient, population) |
| type | |
| units | Units of measurement for the assay result |
| update_frequency | Frequency of model updates based on new data |
| url | URL to access the publication |
| validation_datasets | Datasets used for model training and validation |
| volume | Volume of the compartment (L) |
| width | Width of the channel in micrometers |
| year | Publication year |
Enumerations
| Enumeration | Description |
|---|---|
| AgeEnum | |
| BiologicalOrganizationLevelEnum | |
| CaseOrControlEnum | |
| CellTypeEnum | |
| ChannelConfigurationEnum | Channel configurations for microfluidic devices aligned with ISO 22916:2022 i... |
| CocultureConfigurationEnum | |
| ComplexityLevelEnum | |
| CrossValidationMethodEnum | |
| DeviceMaterialEnum | |
| DigitalTwinScopeEnum | |
| FeatureTypeEnum | |
| FlowControlMethodEnum | Flow control methods for microfluidic devices as defined in ISO 10991:2023 |
| IntegratedSensorEnum | |
| InterfaceTypeEnum | |
| InterpretabilityLevelEnum | |
| InvestigativeProtocolEnum | |
| MechanicalStimulationTypeEnum | |
| MembraneTypeEnum | |
| MicrofluidicArchitectureEnum | Architecture types for microfluidic devices as defined in ISO 10991:2023 |
| MLAlgorithmEnum | |
| OrganEnum | |
| PBPKCompartmentEnum | |
| PredictionOutcomeEnum | |
| PresenceEnum | |
| RatioTypeEnum | |
| RelativeTimeEnum | |
| SampleProcessingEnum | |
| SpeciesEnum | |
| StrainEnum | |
| StudyDesignEnum | |
| SurfaceCoatingEnum | |
| ThreeDArchitectureEnum |
Types
| Type | Description |
|---|---|
| Boolean | A binary (true or false) value |
| Curie | a compact URI |
| Date | a date (year, month and day) in an idealized calendar |
| DateOrDatetime | Either a date or a datetime |
| Datetime | The combination of a date and time |
| Decimal | A real number with arbitrary precision that conforms to the xsd:decimal speci... |
| Double | A real number that conforms to the xsd:double specification |
| Float | A real number that conforms to the xsd:float specification |
| Integer | An integer |
| Jsonpath | A string encoding a JSON Path |
| Jsonpointer | A string encoding a JSON Pointer |
| Ncname | Prefix part of CURIE |
| Nodeidentifier | A URI, CURIE or BNODE that represents a node in a model |
| Objectidentifier | A URI or CURIE that represents an object in the model |
| Sparqlpath | A string encoding a SPARQL Property Path |
| String | A character string |
| Time | A time object represents a (local) time of day, independent of any particular... |
| Uri | a complete URI |
| Uriorcurie | a URI or a CURIE |
Subsets
| Subset | Description |
|---|---|