147: A Clinical Quantitative Systems Pharmacology Framework Describing Loncastuximab Tesirine Distribution & to Explore Patient Outcomes from the Lotis-2 Clinical Trial in Patients With B-Cell Lymphomas

Statement of Purpose: B-lymphocyte antigen CD19 has been clinically validated as a therapeutic target for the treatment of B-cell malignancies. Various CD19-targeted therapies include chimeric antigen receptor T-cell (CAR-T) therapy, monoclonal antibodies, antibody-drug conjugates (ADCs), and bispecific agents. Loncastuximab tesirine (Lonca) is an ADC comprising an anti-CD19 antibody conjugated to a pyrrolobenzodiazepine dimer cytotoxin. Lonca targets CD19 cell-surface antigens in most malignant B-cells and is indicated for treatment of relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) after ≥2 systemic treatments. A novel quantitative systems pharmacology (QSP) framework was developed describing Lonca distribution and effect on lymphomas [1]. The construct integrated multiple literature-based modeling elements and in-house preclinical and clinical data and was exercised in relevant DLBCL virtual populations to predict clinical responses to Lonca, identify influential model parameters, and test patient-specific hypotheses (hypoalbuminemia, and double hit and triple hit lymphoma).

Description of Methods & Materials: The QSP model combines a literature-based whole-body PBPK model [2] describing ADC biodistribution with nodal [3] and extranodal [4] lumped models of tumor dynamics. Literature and in-house data informed processes of receptor-mediated endocytosis, internalization, degradation, diffusion, and elimination of Lonca. Preclinical CD19 expression (IHC, flow) and in-vitro data supported binding, dissociation, internalization, biophysical/PK properties and IC50 effect values. A virtual population was generated from patients enrolled in the LOTIS-2 clinical trial (NCT03589469). The model was used to predict individual clinical observations (Figure 1) for model parameters and covariates impacting response (Figure 2), including: – Initial tumor size/location – Body weight – Hypoalbuminemia (as neonatal Fc receptor expression) – Growth and Lonca-induced death rates of tumor cells – Lonca internalization rate into cells – Payload diffusion rate out of cells – Fraction and surface density (molecules/cell) of CD19+ cells from pretreatment tumor biopsies – Double hit (DH)/triple hit (TH) lymphoma disease phenotypes.

Data & Results: A key finding resulted from evaluation of CD19 expression level and surface density thresholds needed for clinical response. 567 simulations were performed by scanning CD19 expression levels, tumoral CD19 antigen surface density, tumor mass, and tumor location using regular phase II dosing (150 µg/kg Q3W, followed by 75 µg/kg), (Figure 2). Analyses illustrated that 1) CD19 expression level (fraction of CD19+ cells in tumor assessed by IHC) alone is a poor predictor of response to Lonca; 2) CD19 surface density in addition to expression level improves response prediction; and 3) patients respond to Lonca with tumor cell surface densities as low as 1000 molecules/cell, below the recent threshold identified for CAR-T cell therapies [5]. Predicted influence of covariates on LOTIS-2 patient-level outcomes indicated that DH/TH lymphomas are more aggressive with 2-3 times higher growth rates than less aggressive phenotypes, and patients with hypoalbuminemia have reduced plasma exposure, which was well described through systemic reduction in FcRn expression levels.

Interpretation, Conclusion or Significance: A novel QSP framework integrating PBPK modeling with tumor dynamics was developed using literature and in-house data. Through a virtual population, development decisions such as indication, clinical population selection, influence of clinical study covariates, disease phenotypes, and CD19 expression levels on clinical responses in patients treated with Lonca can be effectively evaluated.

References: [1] Caimi et al., Blood 140.Supplement 1, 2022 [2] Jones et al., CPT: Pharmacometrics & Systems Pharmacology, 2019 [3] L. Kähäri et al. J. Clin. Invest., 2019 [4] Lindauer et al., CPT Pharmacometrics Syst Pharmacol., 2017 [5] Spiegel et al., Nat. Med. 27, 2021.

Disclosures:

Funding: ADC Therapeutics SA Utsey: employee of Metrum Research Group. Jordie: employee of Metrum Research Group. Knab: employee of Metrum Research Group. Wilkins: employee of Metrum Research Group. Nickaeen: employee of Metrum Research Group. Pantano: employed and a current equity holder at ADC Therapeutics SA, a publicly traded company. Zammarchi: employed and a current equity holder at ADC Therapeutics SA, a publicly traded company. Wang: employed and a current equity holder at ADC Therapeutics SA, a publicly traded company. Havenith: employed and a current equity holder at ADC Therapeutics SA, a publicly traded company. Cucchi: employed and a current equity holder at ADC Therapeutics SA, a publicly traded company. Boni: employee and a current equity holder at ADC Therapeutics America Inc, a publicly traded company.