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Neoadjuvant nivolumab tumor–immune dynamics

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.

A Computational Model of Neoadjuvant PD-1 Inhibition in Non-Small Cell Lung Cancer ↗

The AAPS Journal

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MODEL IN MOTION 18 sec

How do effector T cells and tumor cells change before resection?

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Starting example

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.

0–40 day

Scenario details

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.

Readouts

PD 1 blockade · Unit unavailable
PD 1 blockade over the selected simulation window.
Effector t · cell
Effector t over the selected simulation window.
Regulatory t · cell
Regulatory t over the selected simulation window.
Tumor-cell count · cell
Tumor-cell count over the selected simulation window.
Tumor diameter relative to baseline · Unit unavailable
Tumor diameter relative to baseline over the selected simulation window.

Study purpose

  • How does neoadjuvant PD-1 blockade propagate through T-cell balance to tumor regression?

Inputs changed since the displayed result. Run to update the comparison.

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Model parameter

Nivolumab elimination rate governing first-order loss from the modeled system.

1/day

Suggested: 0.031–0.093. You can explore beyond this range.

0.062 → —

Nivolumab input rate defining the modeled treatment input for the explored scenario.

mg/day

Suggested: 8.57–25.7. You can explore beyond this range.

17.14 → —

Checkpoint relaxation coefficient used by the released system of model equations.

day

Suggested: 1–3. You can explore beyond this range.

2 → —

Effector T-cell activation coefficient used by the released system of model equations.

1/day

Suggested: 0.009–0.027. You can explore beyond this range.

0.018 → —

Regulatory T-cell relaxation coefficient used by the released system of model equations.

day

Suggested: 17.5–52.5. You can explore beyond this range.

35 → —
Simulation time
day
day
40 → 168

Time between reported samples.

day

1 change · Variation 1

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Biology

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.

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 nivolumab input: Continuous regimen-equivalent rateAveraged nivolumabinputContinuous regimen-equivalentrateCentral nivolumab exposure: Reduced systemic PK stateCentral nivolumabexposureReduced systemic PK stateCheckpoint-complex proxy: Lumped PD-1/PD-L1/PD-L2 signalCheckpoint-complexproxyLumped PD-1/PD-L1/PD-L2 signalEffector and regulatory T cells: Reduced immune-cell poolsEffector andregulatory T cellsReduced immune-cell poolsT-cell-mediated killing: Teff drive opposed by TregT-cell-mediatedkillingTeff drive opposed by TregTumor-cell burden: Growth opposed by immune lossTumor-cell burdenGrowth opposed by immune lossDiameter and regression: Relaxed response readoutsDiameter 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.

Model details

17 parameters · 7 states · 7 equations · 12 derived outputs

Classification & API access
Therapeutic
Nivolumab
Modality
Monoclonal antibody
Target
PD-1 / PDCD1
Disease / scope
Resectable non-small cell lung cancer
ParameterDefaultUnitDescription
Checkpoint relaxationcheckpoint_relaxation_day2dayCheckpoint relaxation coefficient used by the released system of model equations.
EC50 nivolumabec50_nivo_mg120mgEC50 nivolumab at which the corresponding modeled effect reaches half of its maximum.
Nivolumab elimination ratek_elim_nivo_day0.0621/dayNivolumab elimination rate governing first-order loss from the modeled system.
Nivolumab input ratenivo_input_rate_mg_day17.142857142857142mg/dayNivolumab input rate defining the modeled treatment input for the explored scenario.
Regression relaxationregression_relaxation_day1dayRegression relaxation coefficient used by the released system of model equations.
Source checkpoint half inhibition moleculesource_checkpoint_half_inhibition_molecule250moleculeSource checkpoint half inhibition molecule controlling the time required for the corresponding quantity to decrease by half.
Source checkpoint hillsource_checkpoint_hill2—Source checkpoint hill coefficient used by the released system of model equations.
Source k c capacitysource_k_c_capacity_cells111584322479.0202cellSource k c capacity coefficient used by the released system of model equations.
Source k c death by tsource_k_c_death_by_t_day41/daySource k c death by t coefficient used by the released system of model equations.
Source k c deathsource_k_c_death_day0.00011/daySource k c death coefficient used by the released system of model equations.
Source k c growthsource_k_c_growth_day0.011/daySource k c growth governing growth in the modeled biological process.
Source PD1 pdl complex initialsource_pd1_pdl_complex_initial14857.495125289903moleculeSource PD1 pdl complex initial coefficient used by the released system of model equations.
Source tumor initialsource_tumor_initial_cells7810902573.531415cellSource tumor initial coefficient used by the released system of model equations.
Source tumor initial regulatory T-cellsource_tumor_initial_treg_cells9303338.928787664cellSource tumor initial regulatory T-cell coefficient used by the released system of model equations.
Effector T-cell activationteff_activation_day0.0181/dayEffector T-cell activation coefficient used by the released system of model equations.
Regulatory T-cell relaxationtreg_relaxation_day35dayRegulatory T-cell relaxation coefficient used by the released system of model equations.
Tumor diameter relaxationtumor_diameter_relaxation_day1dayTumor diameter relaxation coefficient used by the released system of model equations.

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