OncologyImmuno-oncologyImmunology & inflammationRespiratory disease QSP

Neoadjuvant nivolumab tumor–immune dynamics

Reference paper ↗

A reduced QSP model connecting nivolumab exposure and PD-1 checkpoint inhibition to effector and regulatory T-cell dynamics, tumor-cell burden, and tumor regression.

Therapeutic
Nivolumab
Modality
Monoclonal antibody
Target
PD-1 / PDCD1
Disease
Resectable non-small cell lung cancer
Model type
QSP

Complete model workspace

Checking workspace access…

Parameters
17
States
7
Equations
7
Derived outputs
12

Explore this model

Choose a starting point to view its result. Adjust key model inputs when you want to explore a different outcome.

Starting configuration

Regimen-averaged neoadjuvant nivolumab input

Regimen-averaged neoadjuvant nivolumab input

Explore how a regimen-averaged nivolumab input rate changes PD-1 blockade, effector and regulatory T-cell balance, and tumor regression. The packaged equations use a continuous average input parameter; discrete infusion events are not executed by this reduced model.

Starting result

This result reflects the starting settings. Run your changes to update it.

Result preview could not load

The generated result could not be loaded. The inputs remain available below.

Starting configuration

Time: 0–40 day; step 1

InputDefaultAvailable range
Nivolumab elimination rate0.062 1/day0.031–0.093 1/day
Nivolumab input rate17.14 mg/day8.571–25.71 mg/day
Checkpoint relaxation2 day1–3 day
Effector T-cell activation0.018 1/day0.009–0.027 1/day
Regulatory T-cell relaxation35 day17.5–52.5 day

Expected readouts

PD 1 blockade · Effector t (cell) · Regulatory t (cell) · Tumor-cell count (cell) · Tumor diameter relative to baseline

Adjustable model parameters

This public explorer exposes 5 curated parameters. Sign in to edit all 17 declared model parameters.

More key parameters (1)

How the model represents the biology

A reduced QSP model connecting nivolumab exposure and PD-1 checkpoint inhibition to effector and regulatory T-cell dynamics, tumor-cell burden, and tumor regression.

How does averaged nivolumab exposure alter the reduced checkpoint, T-cell, and tumor-response system?A continuous regimen-averaged nivolumab input creates central exposure. Exposure lowers a lumped checkpoint-complex proxy and increases effector T-cell activation. Effector and regulatory T-cell pools jointly govern immune killing, which reduces tumor-cell burden and drives relaxed tumor diameter and regression readouts.BIOLOGY OVERVIEWHow does averaged nivolumab exposure alter the reduced checkpoint, T-cell, andtumor-response system?Averaged nivolumabinputContinuous regimen-equivalentrateCentral nivolumabexposureReduced systemic PK stateCheckpoint-complexproxyLumped PD-1/PD-L1/PD-L2 signalEffector andregulatory T cellsReduced immune-cell poolsT-cell-mediatedkillingTeff drive opposed by TregTumor-cell burdenGrowth opposed by immune lossDiameter andregressionRelaxed response readoutsPRIMARY READOUTSCentral nivolumabCentral nivolumabTumor cellsTumor cellsTumor diameterTumor diameterTumor regressionTumor regression

Solid arrows show modeled movement or change; two-headed arrows show reversible exchange; dashed arrows show modulation without material transfer.

Model scope: Explicit nivolumab–PD-1 binding kinetics, receptor occupancy, free checkpoint species, discrete infusions, antigen-presenting-cell biology, lymph-node trafficking, and the source paper's full systems-modeling environment system are not represented.

Modeled relationships (7)
  • Averaged nivolumab input → Central nivolumab exposure: average input (flow)
  • Central nivolumab exposure → Checkpoint-complex proxy: saturable blockade (modulation)
  • Central nivolumab exposure → Effector and regulatory T cells: raises Teff activation (modulation)
  • Checkpoint-complex proxy → T-cell-mediated killing: suppresses killing (modulation)
  • Effector and regulatory T cells → T-cell-mediated killing: Teff drive / Treg restraint (modulation)
  • T-cell-mediated killing → Tumor-cell burden: immune-mediated tumor-cell loss (loss)
  • Tumor-cell burden → Diameter and regression: cube-root response (production)

Modeled relationships: Averaged nivolumab input to Central nivolumab exposure: average input (flow); Central nivolumab exposure to Checkpoint-complex proxy: saturable blockade (modulation); Central nivolumab exposure to Effector and regulatory T cells: raises Teff activation (modulation); Checkpoint-complex proxy to T-cell-mediated killing: suppresses killing (modulation); Effector and regulatory T cells to T-cell-mediated killing: Teff drive / Treg restraint (modulation); T-cell-mediated killing to Tumor-cell burden: immune-mediated tumor-cell loss (loss); Tumor-cell burden to Diameter and regression: cube-root response (production).

Primary readouts: Central nivolumab; Tumor cells; Tumor diameter; Tumor regression.

Found a scientific issue? Email helpdesk@unibiointelligence.com with model ID jafarnejad_2019_nivolumab_neoadjuvant_pd1_nsclc_qsp.

Research use only — not for patient-specific prediction or dosing advice.

Ubi Biologics