ABSTRACT Amivantamab, a bispecific antibody targeting epidermal growth factor and mesenchymal‐epithelial transition receptors, was initially approved under accelerated approval as a monotherapy for second‐line treatment of non‐small cell lung cancer (NSCLC) with exon 20 insertion mutations. Subsequently, amivantamab in combination with carboplatin‐pemetrexed demonstrated prolonged progression‐free survival compared to chemotherapy alone in the first‐line treatment of NSCLC with exon 20 insertion mutations and the second‐line treatment of NSCLC with exon 19 deletion or exon 21 L858R substitution mutations. To enable the combination with chemotherapy, the amivantamab regimen was changed from every 2 weeks (Q2W) to every 3 weeks (Q3W); both are weight‐tiered with a cutoff at 80 kg. Here we present the population pharmacokinetics (PK) and exposure‐response (E‐R) analysis supporting this dose regimen change. The population PK analysis demonstrated that the Q3W regimen achieved comparable trough concentrations as the approved Q2W regimen as well as between the two weight tiers. After accounting for confounding covariates, the E‐R relationship for PFS was flat in both indications. The safety profile of the Q3W regimen was generally manageable, despite trends of a positive E‐R relationship for adverse effects related to the mechanism of action. Besides weight, dose adjustment for other covariates was not warranted. These analyses supported the registration of the weight‐tiered Q3W regimen for amivantamab in combination with carboplatin‐pemetrexed in the new indications. This work demonstrates how the use of fit‐for‐purpose pharmacometrics analyses can support dose regimen changes without extensive dose selection clinical studies.

Teclistamab is a B cell maturation antigen × CD3 bispecific antibody approved for relapsed/refractory multiple myeloma. Two step-up doses (SUDs) are used to mitigate the risk of cytokine release syndrome (CRS). For patients who experience dose delays, it is uncertain what length of delay necessitates repeat SUDs. We used modeling simulations and retrospective analysis of the phase 1/2 MajesTEC-1 study to optimize recommendations for repeat SUDs after teclistamab dose delay. Population pharmacokinetic modeling was used to simulate teclistamab serum concentrations after dose delays to assess the duration required to achieve levels comparable to estimated trough concentrations (Ctrough) following SUDs. Quantitative systems pharmacology modeling was used to simulate cytokine dynamics. Modeling-informed time windows were applied to a retrospective analysis of CRS data from MajesTEC-1 recommended phase 2 dose cohorts to further evaluate CRS incidence with prolonged dose delays (> 28 days). Median teclistamab serum concentrations were estimated to drop to levels comparable to the simulated SUD 2 median Ctrough after 62 days and SUD 1 median Ctrough after 111 days. Simulated cytokine peaks at treatment restart during weekly or biweekly dosing at these intervals were lower than those following the initial SUD. Retrospective analysis of clinical data revealed a low incidence of CRS (grade 1–2; 2/61 [3.3

7524 Background: Talquetamab (Tal, anti-GPRC5D) and Teclistamab (Tec, anti-BCMA) are first-in-class bispecific antibodies approved as monotherapies for triple-class exposed relapsed/refractory multiple myeloma (RRMM). Extramedullary disease (EMD) is an aggressive MM subtype with poor outcomes and high unmet need. RedirecTT-1 (NCT04586426) is a Phase 1b/2 dose escalation/expansion study evaluating Tal + Tec in RRMM patients (pts) including EMD. We present data supporting selection of the recommended Phase 2 regimen (RP2R) for treatment of EMD pts, based on efficacy, safety, and exposure-response (E-R) analyses from Phase 1. Phase 2 allowed switching to a Q4W regimen after cycle 6 or cycle 4 if the response was ≥VGPR. Methods: Phase 1 evaluated 6 dose regimens of Tal (0.2–0.4 mg/kg QW, 0.8 mg/kg Q2W, 0.8 mg/kg Q4W) + Tec (0.75-1.5 mg/kg QW, 1.5-3 mg/kg Q2W, 3 mg/kg Q4W). Responses were investigator-assessed per IMWG criteria. CRS and ICANS were graded by ASTCT criteria; all other adverse events were graded by CTCAE v5.0. Model-based E-R analyses for efficacy were conducted with reported efficacy endpoints (ORR, ≥VGPR, ≥CR). First cycle PK metrics (C avgC1 , C troughC1 ) were used due to time-varying clearance of Tal and Tec. Results: At the clinical cutoff for this analysis (18 March 2025), Phase 1 enrolled 114 pts (38 EMD) with a median follow-up of 31.6 months. EMD pts treated with QW regimens of Tal 0.2-0.4 mg/kg + Tec 0.75-1.5 mg/kg (n=13), which comprised of multiple dose levels (1-9 pts per cohort), achieved an ORR of 33-100% (≥CR, 0-22.2%). EMD pts treated with the Q2W regimen using Tal 0.8 mg/kg and Tec 1.5 mg/kg (n=4) achieved an ORR of 50% (≥CR, 25%), while EMD pts treated with the Q2W regimen including Tal 0.8 mg/kg + Tec 3.0 mg/kg (RP2R, n=18) demonstrated high and deep response rates (ORR, 61.1%, ≥CR, 44.4%) with a manageable safety profile. EMD pts treated with the Q4W regimen of Tal 0.8 mg/kg + Tec 3.0 mg/kg (n=3) achieved an ORR of 100%, where 2 achieved ≥VGPR, but none achieved ≥CR. The RP2R generally provided higher and deeper responses in EMD pts compared to non-RP2R regimens. The efficacy E-R analysis for EMD pts showed a positive E-R relationship between exposure (C avgC1 and C troughC1 ) and ≥CR. Pts with exposures above the median for both Tal and Tec showed higher CR rates. At RP2R, C avgC1 and C trC1 exceeded median exposures across all Phase 1 dose regimens for both antibodies. The overall safety profile of Tal + Tec at the RP2R was manageable and consistent with each agent as monotherapy, while enabling deeper and more durable responses than observed across non-RP2R regimens. Conclusions: The totality of efficacy, safety and E-R analyses support advancement of a Tal + Tec regimen for further clinical development in RRMM pts with EMD who have received a PI, an IMiD, and an anti-CD38 mAb, and offers flexibility of switching to Q4W for responders. Clinical trial information: NCT04586426 .

Based on the phase I/II MajesTEC-1 study, the B-cell maturation antigen (BCMA) and cluster of differentiation (CD)3 bispecific antibody, teclistamab, is approved for relapsed/refractory multiple myeloma (RRMM) at a dose of 1.5 mg/kg weekly (QW), with the option to switch to 1.5 mg/kg every other week (Q2W) in patients maintaining complete response (CR) or better for ≥ 6 months on the QW schedule. We report the pharmacokinetics (PK), pharmacodynamics, and anticancer activity of teclistamab 1.5 mg/kg Q2W, and the PK of teclistamab 3 mg/kg every 4 weeks (Q4W), on the basis of modeling and simulation results from MajesTEC-1. Teclistamab PK was assessed using a population PK approach. Exposure–response analysis was based on individual estimated teclistamab serum trough concentration (Ctrough). The impact of responders switching to Q2W teclistamab dosing on the formation of the key pharmacological species that drive the mechanism of action of teclistamab (i.e., the trimer formed by simultaneous engagement of teclistamab with BCMA on target multiple myeloma cells and CD3 on effector T cells) was estimated using a quantitative systems pharmacology (QSP) model. Additionally, steady-state teclistamab PK and trimer was simulated for the 1.5 mg/kg Q2W and Q4W (3 mg/kg or 1.5 mg/kg) doses. Median estimated teclistamab serum Ctrough was lower after the first and fourth Q2W doses (14.4 and 11.7 µg/mL, respectively) than after QW doses (20.4 µg/mL) but remained above the 90

Objectives: AMI was initially approved as a monotherapy for second-line treatment of NSCLC patients with EGFR exon 20 insertion (exon20ins) mutations whose disease has progressed on or after platinum-based chemotherapy based on CHRYSALIS study. The approved regimen is a weight-tiered Q2W IV regimen in a 28-day cycle with a cutoff of 80 kg [1]. PAPILLON is a Phase 3 study demonstrating a significant prolongation of progression free survival (PFS) of AMI in combination with CP (ACP) compared to CP alone for the first-line treatment of NSCLC patients with EGFR exon20ins mutations. To align with the regimen of chemotherapy and to ensure equivalent therapeutic exposure, AMI was adjusted to Q3W in a 21-day cycle at a slightly higher dose for each weight tier. Both Q2W and Q3W regimens applied QW loading doses in Cycle 1. Here we present the popPK and E-R analyses from PAPILLON study supporting the weight-tiered Q3W IV regimen.Methods: The previous popPK model supporting the Q2W monotherapy regimen was updated based on pooled PK data of monotherapy and combination with CP from CHRYSALIS and PAPILLON studies. PK simulation was conducted to compare Q2W and Q3W regimens and to support subgroup analysis of PK exposures.The E-R analysis for efficacy included PAPILLON participants who received ACP. The analysis focused on the primary endpoint PFS, using Kaplan-Meier plots and log-rank test. Impact of covariates were explored graphically and using Cox-PH modeling.Results: The updated popPK model was a 2-compartment model with parallel linear and Michaelis-Menten elimination. Baseline weight, age, albumin, and sex were identified as statistically significant PK covariates. Coadministration with CP had no impact on AMI PK. PK simulation demonstrated that AMI trough concentrations at the end of the QW loading phase and at steady state for the Q3W regimen were generally comparable to the approved Q2W regimen and between the two weight tiers. The 17% and 27% lower exposures in 60 to 70 kg and 70 to 80 kg subgroups were not clinically meaningful as these subgroups had similar PFS, supporting the 80 kg weight cutoff. AMI exposures were comparable across age and albumin subgroups.A weak trend of positive E-R relationship for trough concentration at the end of the QW loading doses and PFS was observed, however, was insignificant in multivariable Cox-PH modeling after accounting for brain metastases and sex. The insignificant (flat) E-R relationship for PFS suggested that the Q3W regimen provided adequate exposure for efficacy. Males appeared to have 24% lower steady state exposure and shorter PFS than females, but the E-R relationship in males was flat, therefore no dose adjustment is warranted for males.Conclusions: The popPK and E-R efficacy analyses adequately supported the weight-tiered Q3W IV regimen of AMI in combination with CP for the first-line treatment of NSCLC patients with EGFR exon20ins mutations.Citations: [1] Haddish-Berhane N, Su Y, Russu A, Thayu M, Knoblauch RE, Mehta J, Xie J, Gibbs E, Sun YN, Zhou H. Determination and Confirmation of Recommended Ph2 Dose of Amivantamab in Epidermal Growth Factor Receptor Exon 20 Insertion Non-Small Cell Lung Cancer. Clin Pharmacol Ther. 2024 Mar;115(3):468-477. doi: 10.1002/cpt.3064.

Objectives: Lazertinib (JNJ-73841937; YH25448) is a mutant-selective irreversible epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor targeting both the T790M mutation and activating EGFR mutations while sparing wild-type EGFR. Lazertinib in combination with amivantamab is being investigated in a Phase 3 Study 73841937NSC3003 (MARIPOSA) as a first-line treatment in patients with EGFR-mutated, locally advanced or metastatic non-small cell lung cancer (NSCLC). The objectives of the analyses were to characterize the PK of lazertinib in patients with NSCLC and explore lazertinib exposure response (E-R) relationships in MARIPOSA.Methods: The lazertinib Population PK (PPK) analyses were based on data from MARIPOSA and supportive studies 61186372EDI1001, 73841937NSC1001, YH25448-201(lazertinib monotherapy), and YH25448-301(lazertinib monotherapy). A total of 14,936 measurable lazertinib plasma concentrations from 1,389 participants were included. The PPK model was developed in NONMEM (ICON plc). Covariate relationships were identified using exploratory graphical evaluations and generalized additive modeling and then tested in the stepwise covariate model. The E-R analyses included PK, efficacy, and safety data from 416 participants treated with amivantamab and lazertinib combination therapy in MARIPOSA.Results: The observed lazertinib plasma concentration-time data were adequately described by a 2 compartment model with sequential zero- and first order absorption. The PPK model included covariate effects of body weight, Glutathione S-Transferase Mu 1 (GSTM1) genotype, sex, Japanese population, prior treatment (naïve vs non-naïve) on CL/F, and body weight, sex on V2/F. Patients with GSTM1 non-null genotype had 44% and 34% lower exposure compared to GSTM1 null participants based on AUC0-24h.ss and Cmax.ss, respectively. PFS was similar between GSTM1 non-null and null participants despite the PK difference in these two patient groups. No clinically meaningful differences in lazertinib PK were observed based on age, sex, body weight, race, ethnicity, hepatic function, and renal function. Lazertinib plasma exposure was comparable when administered either in combination with amivantamab or as monotherapy.E-R analyses showed no apparent E-R relationship between lazertinib exposures and PFS, supporting lazertinib dose in MARIPOSA seeking for approval. There were no observed E-R relationships across the examined safety endpoints including rash, pneumonitis/interstitial lung disease, venous thromboembolic events, paronychia, hypoalbuminemia, and diarrhea. Paresthesia and stomatitis appeared to show a mild increase in incidence with increasing exposure.Conclusions: Overall, the findings from PPK and E-R analyses supported the proposed lazertinib oral dosing of 240 mg once daily in combination with amivantamab. No dose adjustment is recommended based on the investigated covariates from PPK, efficacy, and safety E-R analyses.Citations: NA

This review aims to delineate the framework of pediatric physiologically based pharmacokinetic (PBPK) modeling, highlight pertinent guidelines, and examine its current applications and future potential in pediatric drug development. Pediatric PBPK modeling has emerged as a critical tool by integrating drug property data with developmental physiology, thereby enhancing drug development for children. Regulatory agencies have acknowledged its significance, issuing various guidance documents that promote its use. Researchers and pharmaceutical developers are continually refining pediatric PBPK models to address the unique challenges of pediatric pharmacotherapy. Advances include improved model accuracy and predictive capabilities, which are instrumental in bridging gaps in pediatric pharmacokinetics and pharmacodynamics. Recent studies demonstrate that PBPK models are effective in predicting drug behavior in pediatric populations, thus facilitating safer and more effective dosing regimens. With ongoing technological advancements and increasing data availability, PBPK models are set to play a pivotal role in pediatric drug development. Future efforts will likely focus on deepening the understanding of pediatric pharmacology and expanding the integration of PBPK modeling with other modeling approaches and technologies. These advancements will significantly enhance the utility of pediatric PBPK models, offering numerous opportunities to improve pediatric drug development. This article does not contain original data from any clinical trials.

Introduction: Teclistamab is the first approved B-cell maturation antigen (BCMA) × CD3 bispecific antibody for the treatment of triple-class exposed relapsed/refractory multiple myeloma (RRMM), with weight-based dosing and the longest study follow-up of any bispecific antibody in MM. In the phase 1/2 MajesTEC-1 study (NCT03145181/NCT04557098) in patients with heavily pretreated RRMM, rapid, deep, and durable responses were observed over a median follow-up of 30.4 months, including in patients who switched to less frequent dosing schedules according to depth and duration of clinical response. Based on these results, teclistamab dosing at 1.5 mg/kg every other week (Q2W) was approved by the US Food and Drug Administration and European Medicines Agency in patients who achieved and maintained complete response (CR) or better for ≥6 months. Using population pharmacokinetics (PK), exposure-response (E-R), and quantitative systems pharmacology (QSP) approaches, this analysis assessed the PK and pharmacodynamics of teclistamab in patients who switched to less frequent teclistamab dosing, which supported the approval of the Q2W schedule in responders. Methods: Patients enrolled in MajesTEC-1 received subcutaneous teclistamab at the recommended phase 2 dose of 1.5 mg/kg weekly (QW) after step-up dosing, with the option to switch to the Q2W schedule if they achieved a partial response or better after ≥4 cycles (phase 1) or ≥CR for ≥6 months (phase 2). Teclistamab PK following less frequent dosing (1.5 mg/kg Q2W) was assessed using a population PK approach. E-R analysis was performed for duration of response (DOR), progression-free survival (PFS), and overall survival (OS) based on individual estimated serum trough concentration (Ctrough) after the first Q2W dose in the 63 patients who switched to the 1.5 mg/kg Q2W dosing schedule. A QSP model was used to generate a virtual RRMM population with sustained response for ≥6 cycles to estimate the impact of teclistamab dose switching (QW to Q2W) on TBE complex formation (simultaneous engagement of target antigen on MM cells [BCMA; T] and effector antigen on T cells [CD3; E] by the bispecific antibody [teclistamab; B]) and antitumor activity. Additionally, teclistamab PK metrics were estimated for the approved 1.5 mg/kg Q2W dosing schedule and 3 mg/kg monthly (Q4W) dosing based on simulation of the teclistamab population PK model. Results: The median predicted teclistamab Ctrough was lower after the first and fourth Q2W doses (14.4 and 11.7 µg/mL, respectively) than that prior to the first Q2W dose (20.4 µg/mL) but remained above the 90% maximal effective concentration (6.039 µg/mL). No statistically significant E-R relationship was observed for DOR, PFS, or OS in patients switching to Q2W dosing, suggesting that the range of exposure observed in the 63 patients who switched to Q2W dosing did not lead to a difference in maintenance of response. The QSP model estimated comparable TBE complex formation, tumor volume reduction, and DOR for responders who switched to Q2W vs those who remained on QW dosing. Based on PK simulations, teclistamab exposure (steady-state PK parameters [Ctrough, maximum concentration, and area under the curve]) at the 3 mg/kg Q4W dose was estimated to be comparable with that of the 1.5 mg/kg Q2W dose. Conclusions: These modeling and simulation results from the MajesTEC-1 study support the approved switch to teclistamab 1.5 mg/kg Q2W in patients who have maintained ≥CR for ≥6 months. Furthermore, results from the population PK model indicate that teclistamab PK at the approved 1.5 mg/kg Q2W dosing schedule is comparable with that at 3 mg/kg Q4W.

Cachexia is associated with increased morbidity and mortality in cancer. The White adipose tissue (WAT) synthesizes and releases several pro-inflammatory cytokines that play a role in cancer cachexia-related systemic inflammation. IFN-γ is a pleiotropic cytokine that regulates several immune and metabolic functions. To assess whether IFN-γ signalling in different WAT pads is modified along cancer-cachexia progression, we evaluated IFN-γ receptors expression (IFNGR1 and IFNGR2) and IFN-γ protein expression in a rodent model of cachexia (7, 10, and 14 days after tumour implantation). IFN-γ protein expression was heterogeneously modulated in WAT, with increases in the mesenteric pad and decreased levels in the retroperitoneal depot along cachexia progression. Ifngr1 was up-regulated 7 days after tumour cell injection in mesenteric and epididymal WAT, but the retroperitoneal depot showed reduced Ifngr1 gene expression. Ifngr2 gene expression was increased 7 and 14 days after tumour inoculation in mesenteric WAT. The results provide evidence that changes in IFN-γ expression and signalling may be perceived at stages preceding refractory cachexia, and therefore, might be employed as a means to assess the early stage of the syndrome.

Amivantamab has demonstrated durable responses with a tolerable safety profile in non-small cell lung cancer with EGFR exon 20 insertions (Ex20ins) who progressed after prior platinum chemotherapy. Data supporting the amivantamab recommended phase II dose (RP2D) in this patient population are presented. Pharmacokinetic (PK) analysis and population PK (PopPK) modeling were conducted using serum concentration data obtained following amivantamab intravenous administration (140-1,750 mg). Pharmacodynamics (PDs) were evaluated using depletion of soluble EGFR and MET. Exposure-response (E-R) analyses were performed using the primary efficacy end point of objective response rate in patients with EGFR Ex20ins. The E-R relationship for safety was explored for adverse events of clinical interest. Amivantamab exhibited linear PKs at 350-1,750 mg dose levels following administration, with no maximum tolerated dose identified. A two-compartment PopPK model with linear clearance adequately described the observed PKs. Body weight was a covariate of clearance and volume of distribution in the central compartment. PopPK modeling showed that a weight-based, 2-tier (< 80 and ≥ 80 kg) dosing strategy reduces PK variability and provides comparable exposure across 2 weight groups, with 87% of patients achieving exposures above the target threshold. The final confirmed RP2D of amivantamab was 1,050 mg for < 80 kg (1,400 mg for ≥ 80 kg) weekly in cycle 1 (28 days) and every 2 weeks thereafter. No significant exposure-efficacy or safety correlation was observed. In conclusion, the amivantamab RP2D is supported by PK, PD, safety, and efficacy analyses. E-R analyses confirmed that the current regimen provides durable efficacy with tolerable safety.

Tesnatilimab is a human immunoglobulin G4 isotype monoclonal antibody that blocks the natural killer group 2 member D (NKG2D) receptor and prevents the downstream signaling of proinflammatory cytokines and cytotoxic mediators. Subcutaneous tesnatilimab was investigated in a phase 2 randomized, double-blind, placebo-controlled trial in patients with moderately to severely active Crohn disease (CD). While the proof-of-concept part I of the study demonstrated significant treatment effects, part II (dose-ranging) revealed an unexpected lack of dose-response and a modest degree of clinical benefit for treatment groups. To inform further drug development, population pharmacokinetic (PopPK) modeling and exposure-response (E-R) analyses were planned and performed. A 1-compartment PopPK model with first-order absorption and parallel linear and nonlinear elimination pathways was established for tesnatilimab in patients with CD. No clinically significant covariates were identified, and overall consistent pharmacokinetics were observed between part I and part II patients. Receptor occupancy data suggested full occupancy of the peripheral blood natural killer group 2 member D receptors and target engagement at all tested dose levels. Pooled part I and part II data showed a positive efficacy E-R relationship; however, this was driven by data from part I. Part II-only analysis did not show an apparent efficacy E-R relationship. No important covariates were identified in efficacy E-R analyses, overall, and in various subpopulations. No apparent E-R relationships were observed for the investigated safety end points. The PopPK and E-R analyses indicated that the inadequate efficacy of tesnatilimab in CD was unlikely due to insufficient drug exposure and target engagement.

Teclistamab, a B-cell maturation antigen × CD3 bispecific antibody, is approved in patients with relapsed/refractory multiple myeloma (RRMM) who have previously received an immunomodulatory agent, a proteasome inhibitor, and an anti-CD38 antibody. We report the population pharmacokinetics of teclistamab administered intravenously and subcutaneously (SC) and exposure–response relationships from the phase I/II, first-in-human, open-label, multicenter MajesTEC-1 study. Phase I of MajesTEC-1 consisted of dose escalation and expansion at the recommended phase II dose (RP2D; 1.5 mg/kg SC weekly, preceded by step-up doses of 0.06 and 0.3 mg/kg); phase II investigated the efficacy of teclistamab RP2D in patients with RRMM. Population pharmacokinetics and the impact of covariates on teclistamab systemic exposure were assessed using a 2-compartment model with first-order absorption for SC and parallel time-independent and time-dependent elimination pathways. Exposure–response analyses were conducted, including overall response rate (ORR), duration of response (DoR), progression-free survival (PFS), overall survival (OS), and the incidence of grade ≥ 3 anemia, neutropenia, lymphopenia, leukopenia, thrombocytopenia, and infection. In total, 4840 measurable serum concentration samples from 338 pharmacokinetics-evaluable patients who received teclistamab were analyzed. The typical population value of time-independent and time-dependent clearance were 0.449 L/day and 0.547 L/day, respectively. The time-dependent clearance decreased rapidly to < 10

The aims of this work were to develop a population pharmacokinetic (PK) model for chimeric antigen receptor (CAR) transgene after single intravenous infusion administration of ciltacabtagene autoleucel in adult patients with relapsed or refractory multiple myeloma. CAR transgene level in blood were measured by quantitative polymerase chain reaction (qPCR) from 97 subjects in a phase Ib/II CARTITUDE-1 study (NCT03548207), with a targeted cilta-cel dose of 0.75 × 106 (range 0.5-1.0 × 106 ) CAR positive viable T-cells per kg body weight. The population PK model development was primarily guided by the current mechanistic understanding of CAR-T kinetics and the principles of building a parsimonious model. Cilta-cel PK was adequately described by a two-compartment model (with a fast and a slow apparent decline rate from each compartment, respectively) and a chain of four transit compartments with a lag time empirically representing the process from infused CAR-T cell to measurable CAR transgene. No apparent relationship was observed between cilta-cel dose (i.e., the actual number of CAR positive viable T-cells infused), given the narrow dose range, and the observed transgene level. Based on covariate search and subgroup analysis of maximum systemic CAR transgene level (Cmax ) and area under curve from the first dose to day 28 (AUC0-28d ), none of the investigated subjects' demographics, baseline characteristics, and manufactured product characteristics had significant effects on cilta-cel PK. The developed model is deemed robust and adequate for enabling subsequent exposure-safety and exposure-efficacy analyses.

Objectives: Ciltacabtagene autoleucel (cilta-cel, CARVYKTI, previously JNJ-68284528) is a B-cell maturation antigen (BCMA)-directed genetically modified autologous T-cell immunotherapy indicated for the treatment of adult patients with relapsed or refractory multiple myeloma. Due to the restricted expression of BCMA in normal tissue and expression primarily on late-stage B-cells, plasma cells and malignant B-lineage cells, BCMA is an attractive target for cell therapy for multiple myeloma. The chimeric antigen receptor (CAR) consists of two BCMA-targeting single domain antibodies designed to confer avidity, a CD3ζ signaling domain and a 4-1BB costimulatory domain. The aims of this work were to develop a population pharmacokinetic (PK) model for CAR transgene after single intravenous infusion administration of cilta-cel and to evaluate the effects of subjects’ demographic characteristics and other covariates on CAR transgene PK. Methods: Subjects CAR transgene level in blood, as measured by quantitative polymerase chain reaction (qPCR) were available from 97 subjects in a Phase 1b/2 CARTITUDE-1 study (NCT03548207). A targeted cilta-cel dose of 0.75x106 (range 0.5-1.0x106) CAR-positive viable T-cells/kg body weight was given 5-7 days after lymphodepletion (300 mg/m2 cyclophosphamide, 30 mg/m2 fludarabine daily for 3 d). The data were analyzed by a non-linear mixed effects modeling approach implemented in NONMEM V7.4.3. The population PK model development was based on existing information on CAR T-cell (CAR-T) PK with some modifications. Model qualification was guided by the objective function value, diagnostic plots, standard error of parameters, evaluation of condition number, shrinkage, and visual predictive checks. Results: The PK of cilta-cel following IV infusion was adequately described by a 2-compartment model (with a fast and a slow apparent decline rate from each compartment, respectively) and a chain of 4 transit compartments with a lag time empirically representing the process from infused CAR-T cell to measurable CAR transgene. The model diagram is shown in Figure 1, consisting of 5 parameters and their respective inter-individual variability (lognormal distribution). The dose was defined as the number of CAR-positive viable T cells infused, and the fitted CAR transgene level (units of copies/μg genomic DNA) observation was the sum of the 2 CAR-T cell compartments. Conclusion: A population PK model has been developed to characterize CAR transgene level of cilta-cel in blood following IV infusion of 0.75x106 (range 0.5-1.0x106) CAR-positive viable T-cells/kg body weight. The developed model is robust and adequate for investigating the covariate effects on CAR transgene level of cilta-cel and enabling subsequent exposure-safety and exposure-efficacy analyses. Citation Format: Liviawati S. Wu, Yaming Su, Claire Li, Wangda Zhou, Carolyn Jackson, Yu-Nien Sun, Honghui Zhou. Population pharmacokinetic modeling of ciltacabtagene autoleucel in subjects with relapsed or refractory multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5182.

Background: Teclistamab (JNJ-64007957) is a B-cell maturation antigen (BCMA) × CD3 bispecific antibody that redirects CD3+ T cells to induce cytotoxicity of BCMA-expressing multiple myeloma (MM) cells. The objectives of this work were to develop a population pharmacokinetics (PK) model for serum teclistamab concentrations after intravenous (IV) infusion and subcutaneous (SC) administration, evaluate the effects of patients' demographic characteristics and other covariates (such as soluble BCMA [sBCMA]) on PK, and explore the exposure-efficacy/safety relationships in patients with relapsed/refractory MM (RRMM). Methods: Analyses were conducted using data from the phase 1/2 study MajesTEC-1 (NCT03145181/NCT04557098) in eligible patients with RRMM. A population PK model was developed using serum teclistamab concentrations from 338 patients who received IV (range, 0.0003-0.0192 mg/kg every 2 weeks and 0.0192-0.72 mg/kg weekly; n=83) or SC doses (range, 0.08 mg/kg weekly to 6 mg/kg [weekly in cycles 1-2, biweekly in cycles 3-6, monthly in cycle 7+]; n=255). Exposure-response (E-R) analyses for efficacy were evaluated based on the predicted exposure metrics (average concentration of the first treatment dose and trough concentration after the first 4 weekly treatment doses) on overall response rate (ORR), duration of response (DOR), progression-free survival (PFS), and overall survival (OS) at the recommended phase 2 dose (RP2D; 1.5 mg/kg teclistamab SC administered weekly with the first treatment dose preceded by step-up doses of 0.06 and 0.3 mg/kg) as well as 0.08 to 6 mg/kg SC doses in Phase 1. Safety E-R analyses were conducted based on the predicted maximum concentrations (after the first treatment dose and the first 4 weekly treatment doses) on Grade ≥3 treatment-emergent adverse events of anemia, neutropenia, lymphopenia, thrombocytopenia, and infection. Results: The PK of teclistamab was adequately described by a 2-compartment model with first-order absorption (associated with SC administration) and parallel time-independent (CL1) and time-dependent (CL2; decreased over time to reflect the change in tumor burden) elimination pathways. The covariate effects in the final model included the effect of body weight on CL1, volume of distribution in the central compartment (V1), and volume of distribution in the peripheral compartment (V2); the effects of International Staging System stage on CL1; and the effect of type of myeloma (IgG vs non-IgG) on CL1 and CL2. A rapid decrease in sBCMA was observed in the majority of responders within the first month of treatment. At 1.5 mg/kg, E-R for ORR was near flat, and DOR, PFS, and OS were not significantly correlated with teclistamab exposures. For 0.08 to 6 mg/kg SC doses in phase 1, a positive E-R relationship was observed for ORR and the response rate at the concentration range associated with 1.5 mg/kg weekly was approaching the plateau (or maximum response). No apparent positive E-R trend was observed in the incidence of grade ≥3 anemia, neutropenia, lymphopenia, thrombocytopenia, and infections across the predicted exposure quartiles in patients who received teclistamab SC. Conclusions: Teclistamab population PK following IV and SC dosing has been well characterized. The E-R analyses for ORR showed positive trend with a plateau at the RP2D, while there was no apparent E-R trend between teclistamab exposure and the grade ≥3 hematologic and infection treatment-emergent adverse events. These results support 1.5 mg/kg teclistamab SC weekly as the recommended dose regimen for the treatment of RRMM.

Background: BCMA-targeted chimeric antigen receptor-engineered (anti-BCMA CAR) T-cell therapy has demonstrated favorable clinical outcomes in relapsed and refractory multiple myeloma (RRMM). Lymphodepleting (LD) chemotherapy including fludarabine (Flu) is hypothesized to promote expansion and persistence of CAR-T cells. Flu exhibits wide pharmacokinetic (PK) variability, with increased exposure as calculated by population PK model correlating with improved outcomes after anti-CD19+ CAR-T (Fabrizio VA, Blood Advances, 2022 & Dekker L. et al, Blood Advances, 2022). Using clinical data from patients enrolled in the CARTITUDE-1 clinical trial (NCT03548207, N=97), a phase 1b/2 study assessing ciltacabtagene autoleucel (cilta-cel) in patients with RRMM, we hypothesized that the developed population PK model may predict outcomes after cilta-cel in myeloma. Methods: Patients in the trial received a single cilta-cel infusion 5 to 7 days after fludarabine 30 mg/m2 and cyclophosphamide 300 mg/m2 for 3 consecutive days. Patients were excluded if they received any LD other than Flu/Cy or had any missing data needed to predict Flu exposure. Predicted exposure (pAUC) of Flu was determined by applying a population approach where eGFR is a covariate for Flu clearance and body weight is a covariate for Flu clearance and volume of distribution (Langenhorst JB, Clinical Pharmacokinetics, 2019). Individual Flu PK profiles and exposure metrics (Cmax, Ctrough and AUC0-72h) were simulated for each patient and were correlated with anti-BCMA CAR-T kinetics and efficacy (IMWG response, PFS and OS). Pearson/Spearman correlation coefficient was used to estimate the association between Flu PK parameters and LD effect, reflected by endogenous T cell changes (prior to versus post-LD), and CAR-T kinetics. Parametric t-test was used as the primary analysis and Mann-Whitney as the sensitivity analysis to determine if Flu AUC was associated with whether the patient can achieve stringent complete response (sCR) or not. PFS and OS rates were compared between 2 patient groups stratified by dichotomized LD exposure (AUC above and below the median). Results: We first investigated if there was variability in the two significant covariates of Flu PK in our cohort- body weight and eGFR. The eGFR distribution indicated large variability (mean=94.2, CV%=33.5) with 50 (51.5%) patients having renal dysfunction (eGFR <90 ml/min/1.73m2). Body weight ranged from 39 to 125.6 kg. The Flu pAUC in the entire population varied by 3.1-fold and the median was found to be 19.4 mg x h/L (IQR, 16.7-21.4; Figure 1A). No apparent association between Flu pAUC and CAR-T expansion and persistence was observed. Predicted peak Flu concentration (p=0.052) and AUC (p=0.058) appear to be slightly higher in sCR patients than non-sCR patients with significant overlapping (Figure 1B). Kaplan-Meier plot of PFS/OS (data cutoff: approximately 12 months of the last patient after CAR-T infusion) suggested no apparent association with LD exposure (p= 0.093 and 0.4 respectively). Analysis is ongoing to determine if there is an association between Flu pAUC and CRS/ICANS with results to be presented at the conference. Conclusions: Although we did not measure Flu blood levels, we report for the first time the application of a previously published population PK model to simulate Flu exposure in a prospective cohort of myeloma patients undergoing anti-BCMA CAR-T therapy. Predicted peak Flu concentration and AUC appears to be slightly higher in sCR patients than non-sCR patients and there was no apparent correlation with CART kinetics or PFS/OS. Our data suggests a trend in Flu exposure predicting PFS but this needs to be further validated with additional data and analysis. Because the actual individual Flu exposure may deviate from the predicted population mean, a definitive analysis will require measurement of Flu blood levels prospectively with lymphodepletion to confirm potential relationships between Flu AUC, CART expansion & persistence, and CART clinical activity. Figure 1. Distribution of Model-predicted Flu AUC0-72h (A). Boxplots of Peak Flu Concentration and Flu pAUC (B) with Stringent Complete Response. Boxplot shows the minimum, 25th quartile, median, 75th quartile, and maximum of the data. Symbols represent individual simulated data points in (B). Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal