Accelerating robust plausible virtual patient cohort generation by substituting ODE simulations with parameter space mapping.

The generation of plausible virtual patients (VPs) is an important step in most quantitative systems pharmacology (QSP) workflows, which requires time-intensive solving of ordinary differential equations (ODEs). However, non-physiological profiles of outputs of interest (OoI) are frequently produced, and additional acceptance/rejection steps are needed for comparing and removing VPs with predicted values outside a pre-defined range. Here, a new approach is developed to accelerate the acceptance/rejection steps by leveraging patterns of parameter associations with OoI. In most models, some parameters are monotonic with respect to OoI, such that an increase in a parameter value always induces an increase or decrease in the OoI. This monotonic property can be used to replace some ODE-solving steps with appropriate monotonic parameter value comparisons to extrapolate the rejection or interpolate the acceptance of some VPs (after simulation) to others. Two algorithms were built that directly extract plausible VPs from a pre-defined initial cohort. These algorithms were first tested using a simple tumor growth inhibition model. Analyzing 200,000 VPs took 50 s with a reference method and 3 to 41 s (depending on the initial set-up) with the first algorithm. The method was then applied to an apoptosis QSP model, in which the clinical phenotypes (i.e., treatment sensitive or resistant) of 200,000 VPs were fully characterized for four different drug regimens in 12 min as compared to over 80 min with the reference approach. Extraction of each phenotype can also be performed individually in 34 s to 8 min, demonstrating the time benefit and flexibility of this approach.

Quantitative systems pharmacology modeling of tumor heterogeneity in response to BH3-mimetics using virtual tumors calibrated with cell viability assays.

Both primary and acquired resistance mechanisms that involve intra-tumoral cell heterogeneity limit the use of BH3-mimetics to trigger tumor cell apoptosis. This article proposes a new quantitative systems pharmacology (QSP)-based methodology in which cell viability assays are used to calibrate virtual tumors (VTs) made of virtual cells whose fate is determined by simulations from an apoptosis QSP model. VTs representing SU-DHL-4 and KARPAS-422 cell lines were calibrated using in vitro data involving venetoclax (anti-BCL2), A-1155463 (anti-BCLXL), and/or A-1210477 (anti-MCL1). The calibrated VTs provide insights into the combination of several BH3-mimetics, such as the distinction between cells eliminated by at least one of the drugs (monotherapies) from the cells eliminated by a pharmacological combination only. Calibrated VTs can also be used as initial conditions in an agent-based model (ABM) framework, and a minimal ABM was developed to bridge in vitro SU-DHL-4 cell viability results to tumor growth inhibition experiments in mice.

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

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.

Clinical Pharmacology and Determinants of Response to UCART19, an Allogeneic Anti-CD19 CAR-T Cell Product, in Adult B-cell Acute Lymphoblastic Leukemia.

Background: UCART19 is an "off-the-shelf" genome-edited anti-CD19 chimeric antigen receptor (CAR)-T cell product, manufactured from unrelated healthy donor cells. Methods: UCART19 was administered to 25 adult patients with relapsed or refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL) in the CALM trial. All patients underwent lymphodepletion with fludarabine and cyclophosphamide ± alemtuzumab and received one of three ascending doses of UCART19. Given the allogeneic nature of UCART19, we analyzed the impact of lymphodepletion, HLA disparities, and host immune system reconstitution on its kinetics, along with other factors known to affect autologous CAR-T cell clinical pharmacology. Results: Responder patients (12/25) had higher UCART19 expansion (C max) and exposure (AUCTlast) than nonresponders (13/25), as measured by transgene levels in peripheral blood. The persistence of CAR+ T cells did not exceed 28 days in 10/25 patients and lasted beyond 42 days in 4/25. No significant correlation was found between UCART19 kinetics and administered cell dose, patient and product characteristics or HLA disparities. However, the number of prior lines of therapy and absence of alemtuzumab negatively impacted UCART19 expansion and persistence. Alemtuzumab exposure positively affected IL7 and UCART19 kinetics, while negatively correlating with host T lymphocyte AUC0-28. Conclusions: UCART19 expansion is a driver of response in adult patients with R/R B-ALL. These results shed light on the factors associated with UCART19 kinetics, which remain highly affected by the impact of alemtuzumab on IL7 and host-versus-graft rejection. Significance: First description of the clinical pharmacology of a genome-edited allogeneic anti-CD19 CAR-T cell product showing the crucial role of an alemtuzumab-based regimen in sustaining UCART19 expansion and persistence through increased IL7 availability and decreased host T lymphocyte population.