Mechanistic Modeling of the Interplay Between Host Immune System, IL-7 and UCART19 Allogeneic CAR-T Cells in Adult B-cell Acute Lymphoblastic Leukemia

Abstract

Chimeric antigen receptor (CAR)-T cell therapies have shown tremendous results against various hematologic cancers. Prior to cell infusion, a host preconditioning regimen is required to achieve lymphodepletion and improve CAR-T cell pharmacokinetic exposure, leading to greater chances of therapeutic success. To better understand and quantify the impact of the preconditioning regimen, we built a population-based mechanistic pharmacokinetic-pharmacodynamic model describing the complex interplay between lymphodepletion, host immune system, homeostatic cytokines, and pharmacokinetics of UCART19, an allogeneic product developed against CD19⁺ B cells. Data were collected from a phase I clinical trial in adult relapsed/refractory B-cell acute lymphoblastic leukemia and revealed three different UCART19 temporal patterns: (i) expansion and persistence, (ii) transient expansion with subsequent rapid decline, and (iii) absence of observed expansion. On the basis of translational assumptions, the final model was able to capture this variability through the incorporation of IL-7 kinetics, which are thought to be increased owing to lymphodepletion, and through an elimination of UCART19 by host T cells, which is specific to the allogeneic context. Simulations from the final model recapitulated UCART19 expansion rates in the clinical trial, confirmed the need for alemtuzumab to observe UCART19 expansion (along with fludarabine cyclophosphamide), quantified the importance of allogeneic elimination, and suggested a high impact of multipotent memory T-cell subpopulations on UCART19 expansion and persistence. In addition to supporting the role of host cytokines and lymphocytes in CAR-T cell therapy, such a model could help optimizing the preconditioning regimens in future clinical trials.

Significance: A mathematical mechanistic pharmacokinetic/pharmacodynamic model supports and captures quantitatively the beneficial impact of lymphodepleting patients before the infusion of an allogeneic CAR-T cell product. Mediation through IL-7 increase and host T lymphocytes decrease is underlined, and the model can be further used to optimize CAR-T cell therapies lymphodepletion regimen.

FIGURE 1

Main features of the model. A, CAR-T cell phases: UCART19 first distributes from blood to tissue before expansion. Afterward, some sets undergo a fast allogeneic elimination, while others experience contraction and persistence. B, IL-7 and host T early AUC (from day 0 to day 11 after UCART19 infusion, day 11 being the median of UCART19 Tmax—measured by flow cytometry) versus expansion status, using the Wilcoxon test. High IL-7 and low host T exposures are related to higher expansions. C, One individual host NK-cell profile illustrating the theoretical decomposition of host lymphocytes (NK and host T cells work the same way): red curve represents a HemTox_like model, able to capture both initial and final observations. However, it does not capture an additional peak of lymphocyte observed around UCART19’s Tmax. An additional expansion of lymphocytes was thus added in the model (dotted curve). Host T/NK are thus the sum of these two systems. D, Illustrative example of a UCART19 truncated profile in blood.

FIGURE 2

Schematics of the final mechanistic pharmacokinetic/pharmacodynamic model. A, General overview of the final model. Lymphodepleting agents eliminate host NK and host T cells. Host T-cell depletion allow UCART19 cells to expand both by directly decreasing host T-cell cytotoxicity and by increasing IL-7 concentrations. B, Detailed model schematic: Top left: Pharmacokinetics of alemtuzumab, fludarabine, and cyclophosphamide compartments. Left: host lymphocytes, divided into T and NK cells. Lymphocytes recovers with the basal system (HemTox like model), FC acts only in tissue compartments, and alemtuzumab acts both in tissue and blood compartments. An expanding lymphocyte compartment was added to capture peaks. Bottom right: timeline of expanding lymphocytes (hostX means hostT or hostNK). Above: IL-7 was modeled with a simple indirect response model with an increased production rate in case of host T lymphodepletion. Middle right: UCART19 system and each subpopulation (T_SCM, T_CM, and T_EM cells) exist in blood and tissue. Model follows a progressive differentiation model (). UCART19 expansion is increased by IL-7, whereas host T cells act on each UCART19 compartment. Top right: timeline of UCART19 kinetics (allogeneic elimination, expansion, and elimination in blood—for two sets only—and switch from a contraction to persistence phase).

FIGURE 3

Observations used to support model building: alemtuzumab, IL-7 concentrations, total lymphocytes, host NK, host T, and UCART19 data.

FIGURE 4

Sample of individual predictions. Each bloc represents a pattern of sets: sets with persistence (A), with expansion followed by fast elimination (B), with no expansion (C). Inside each block, each row represents an observation type. Dots represents observations while full line represent modeled profiles and horizontal dashed black line represent LOQ values.

FIGURE 5

A, Impact of IL-7 on UCART19 profile. Simulation of a typical profile with lowest, intermediate, and highest values for IL7effMax: IL-7 increases the magnitude of the expansion. B, Impact of Allogeneic elimination on UCART19 profiles. In blue, the absence of allogeneic elimination leads to profiles with persistence. In green the allogeneic elimination is lower than UCART19 expansion and a transient peak is observed. In red, a high allogeneic elimination leads to the absence of observable expansion. C, For each set, contribution of IL-7, intrinsic proliferation capacity and allogeneic elimination on UCART19 Cmax. Y axe represent the number of C_max log₁₀ increase (from individual profile) in case of maximal IL-7 effect (red), maximal intrinsic proliferation capacity (green) or absence of allogeneic elimination (blue). D, Memory subpopulation in tissue for a profile with persistence. In blue T_SCM expand faster than the other but is also transformed into T_CM (T_SCM has the highest total disappearance rate). After the expansion, T_CM disappears faster than T_EM due to a high transformation into T_EM. This transformation is then reduced, and T_CM ultimately controls the persistence phase.

FIGURE 6

Fraction of UCART19 expansion from model simulation. For each simulation (n = 2,000), number of expansions was computed and reported into histograms. Observation was highlighted in red, and CI90 reported with dotted lines. Top, All sets gathered. Bottom, Sets grouped by alemtuzumab doses (0 mg, 40 mg, or higher).