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Tsur2019 - Response of patients with melanoma to immune checkpoint blockade Lab

About lab

This is a simple mathematical population model for pembrolizumab-treated advanced melanoma patients, used to predict the response of melanoma patients to immune checkpoint inhibitors. It can be used to explore immune response dynamics and compare pathway-level behavior across conditions.

Runtime

Duration10
Comms Step1

Runs

Total0
Completed0
Failed0

Metadata

Packagetsur2019-response-of-patients-with-melanoma-to-immune-checkpoint
Created2026-05-15
Updated2026-05-15
immunologysbmlbiomodels_ebifaithfulcuratedvisualisation

Manifest

{
  "io": {
    "inputs": [
      {
        "name": "initial_unresolved_prediction_observable_1",
        "label": "Initial Unresolved Prediction Observable 1",
        "units": "native source value",
        "default": 14119.9020779221,
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.initial_unresolved_prediction_observable_1",
        "description": "Initial Unresolved Prediction Observable 1. Sets the initial value of bundled SBML species `A`."
      },
      {
        "name": "initial_unresolved_prediction_observable_2",
        "label": "Initial Unresolved Prediction Observable 2",
        "units": "native source value",
        "default": 66094173.0355407,
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.initial_unresolved_prediction_observable_2",
        "description": "Initial Unresolved Prediction Observable 2. Sets the initial value of bundled SBML species `T`."
      },
      {
        "name": "initial_unresolved_prediction_observable_3",
        "label": "Initial Unresolved Prediction Observable 3",
        "units": "native source value",
        "default": 1000000,
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.initial_unresolved_prediction_observable_3",
        "description": "Initial Unresolved Prediction Observable 3. Sets the initial value of bundled SBML species `M`."
      }
    ],
    "outputs": [
      {
        "name": "unresolved_prediction_observable_1",
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.unresolved_prediction_observable_1"
      },
      {
        "name": "unresolved_prediction_observable_2",
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.unresolved_prediction_observable_2"
      },
      {
        "name": "unresolved_prediction_observable_3",
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.unresolved_prediction_observable_3"
      },
      {
        "name": "state",
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.state"
      },
      {
        "name": "summary",
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.summary"
      },
      {
        "name": "species_labels",
        "maps_to": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.species_labels"
      }
    ]
  },
  "title": "Tsur2019 - Response of patients with melanoma to immune checkpoint blockade Lab",
  "models": [
    {
      "path": "owned/models/immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model",
      "alias": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model",
      "provenance": {
        "owned_path": "owned/models/immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model"
      }
    },
    {
      "path": "owned/models/visualisation",
      "alias": "visualisation",
      "provenance": {
        "owned_path": "owned/models/visualisation"
      }
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model_state"
      ],
      "from": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.state"
    },
    {
      "to": [
        "visualisation.immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model_summary"
      ],
      "from": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.summary"
    },
    {
      "to": [
        "visualisation.immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model_species_labels"
      ],
      "from": "immunology_sbml_tsur2019_response_of_patients_with_melanoma_to_i_biomd0000000838_model.species_labels"
    }
  ],
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 1
  },
  "description": "This is a simple mathematical population model for pembrolizumab-treated advanced melanoma patients, used to predict the response of melanoma patients to immune checkpoint inhibitors. It can be used to explore immune response dynamics and compare pathway-level behavior across conditions.",
  "schema_version": "2.0"
}

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