Combining Therapeutic Drug Monitoring and Pharmacokinetic Modelling Deconvolutes Physiological and Environmental Sources of Variability in Clozapine Exposure

Background: Clozapine is a key antipsychotic drug for treatment-resistant schizophrenia but exhibits highly variable pharmacokinetics and a propensity for serious adverse effects. Currently, these challenges are addressed using therapeutic drug monitoring (TDM). This study primarily sought to (i) verify the importance of covariates identified in a prior clozapine population pharmacokinetic (popPK) model in the absence of environmental covariates using physiologically based pharmacokinetic (PBPK) modelling, and then to (ii) evaluate the performance of the popPK model as an adjunct or alternative to TDM-guided dosing in an active TDM population. Methods: A popPK model incorporating age, metabolic activity, sex, smoking status and weight was applied to predict clozapine trough concentrations (Cmin) in a PBPK-simulated population and an active TDM population comprising 142 patients dosed to steady state at Flinders Medical Centre in Adelaide, South Australia. Post hoc analyses were performed to deconvolute the impact of physiological and environmental covariates in the TDM population. Results: Analysis of PBPK simulations confirmed age, cytochrome P450 1A2 activity, sex and weight as physiological covariates associated with variability in clozapine Cmin (R2 = 0.7698; p = 0.0002). Prediction of clozapine Cmin using a popPK model based on these covariates accounted for <5% of inter-individual variability in the TDM population. Post hoc analyses confirmed that environmental covariates accounted for a greater proportion of the variability in clozapine Cmin in the TDM population. Conclusions: Variability in clozapine exposure was primarily driven by environmental covariates in an active TDM population. Pharmacokinetic modelling can be used as an adjunct to TDM to deconvolute sources of variability in clozapine exposure.

Population Pharmacokinetic Model Development of Tacrolimus in Pediatric and Young Adult Patients Undergoing Hematopoietic Cell Transplantation

Background: With a notably narrow therapeutic window and wide intra- and interindividual pharmacokinetic (PK) variability, initial weight-based dosing along with routine therapeutic drug monitoring of tacrolimus are employed to optimize its clinical utilization. Both supratherapeutic and subtherapeutic tacrolimus concentrations can result in poor outcomes, thus tacrolimus PK variability is particularly important to consider in the pediatric population given the differences in absorption, distribution, metabolism, and excretion among children of various sizes and at different stages of development. The primary goals of the current study were to develop a population PK (PopPK) model for tacrolimus IV continuous infusion in the pediatric and young adult hematopoietic cell transplant (HCT) population and implement the PopPK model in a clinically available Bayesian forecasting tool.Methods: A retrospective chart review was conducted of 111 pediatric and young adult patients who received IV tacrolimus by continuous infusion early in the post-transplant period during HCT from February 2016 to July 2020 at our institution. PopPK model building was performed in NONMEM. The PopPK model building process included identifying structural and random effects models that best fit the data and then identifying which patient-specific covariates (if any) further improved model fit.Results: A total of 1,648 tacrolimus plasma steady-state trough concentrations were included in the PopPK modeling process. A 2-compartment structural model best fit the data. Allometrically-scaled weight was a covariate that improved estimation of both clearance and volume of distribution. Overall, model predictions only showed moderate bias, with minor under-prediction at lower concentrations and minor over-prediction at higher predicted concentrations. The model was implemented in a Bayesian dosing tool and made available at the point-of-care.Discussion: Novel therapeutic drug monitoring strategies for tacrolimus within the pediatric and young adult HCT population are necessary to reduce toxicity and improve efficacy in clinical practice. The model developed presents clinical utility in optimizing the use of tacrolimus by enabling model-guided, individualized dosing of IV, continuous tacrolimus via a Bayesian forecasting platform.

465 Bintrafusp alfa in combination with chemotherapy in patients with stage IV NSCLC: safety and pharmacokinetic results of the INTR@PID LUNG 024 study

BackgroundBintrafusp alfa is a first-in-class bifunctional fusion protein composed of the extracellular domain of the TGF-βRII receptor (a TGF-β ”trap”) fused to a human IgG1 mAb blocking PD-L1. Here we report cumulative safety and pharmacokinetic (PK) results from the global, phase 1b/2 INTR@PID LUNG 024 study (NCT03840915), which evaluated bintrafusp alfa in combination with chemotherapy (CT) in patients with stage IV NSCLC.MethodsAdult patients with stage IV nonsquamous or squamous NSCLC and an ECOG PS ≤1 were included. Cohorts A, B, and C included patients with no prior systemic therapy; patients in cohort D had disease that progressed with previous anti–PD-(L)1 therapy. Cohorts received bintrafusp alfa 2400 mg every 3 weeks intravenously in combination with CT for 4 cycles (A [nonsquamous only]: cisplatin or carboplatin + pemetrexed; B: carboplatin + nab-paclitaxel or paclitaxel; C: cisplatin or carboplatin + gemcitabine; D: docetaxel) followed by bintrafusp alfa maintenance (monotherapy or in combination with pemetrexed in cohort A) for up to 31 cycles. The primary objective of this study was to evaluate the safety of bintrafusp alfa in combination with CT. Dose-limiting toxicities (DLTs) were assessed during a 3-week observation period. Serial samples were drawn to assess serum concentration and calculate PK parameters by noncompartmental analysis.ResultsAs of the May 5, 2021, data cutoff, 70 patients received bintrafusp alfa in combination with CT. Of 35 patients included in the DLT analysis, 4 experienced 1 DLT according to a safety monitoring committee (data cutoff May 5, 2021; A: n=1/8; B: n=1/8; C: n=0/8; D: n=2/11). Cumulative safety data are reported in table 1. PK data were available for 67 patients (A: n=38; B: n=9; C: n=8; D: n=12). PK profiles were similar across cohorts and between patients who did and did not experience a DLT. Observed bintrafusp alfa first-cycle exposures (Cmax, AUC, and Ctrough) were consistent with the published population PK (popPK) model.1Abstract 465 Table 1Safety results from the INTR@PID LUNG 024 studyConclusionsThe safety profile of bintrafusp alfa in combination with CT was manageable and similar to that reported for ICIs in combination with CT, with the exception of TGF-β–related skin lesions known to occur with TGF-β inhibition. No new safety signals were identified and there were no treatment-related deaths. The PK profile was consistent with the predicted monotherapy popPK model, suggesting no victim DDI potential for bintrafusp alfa with CT.AcknowledgementsThe authors thank the patients and their families, investigators, co-investigators, and the study teams at each of the participating centers, at the healthcare business of Merck KGaA, Darmstadt, Germany, and at EMD Serono, Billerica, Massachusetts, USA.Trial RegistrationNCT03840915ReferenceWilkins JJ, Vugmeyster Y, Dussault I. Population pharmacokinetic analysis of bintrafusp alfa in different cancer types. Adv Ther 2019;36:2414–2433.Ethics ApprovalThe trial was approved by each site’s independent ethics committee.

Pharmacokinetic/Pharmacodynamic Model of Neutropenia in Real-Life Palbociclib-Treated Patients

Palbociclib is an oral CDK4/6 inhibitor indicated in HR+/HER2- advanced or metastatic breast cancer in combination with hormonotherapy. Its main toxicity is neutropenia. The aim of our study was to describe the kinetics of circulating neutrophils from real-life palbociclib-treated patients. A population pharmacokinetic (popPK) model was first constructed to describe palbociclib pharmacokinetic (PK). Individual PK parameters obtained were then used in the pharmacokinetic/pharmacodynamic (PK/PD) model to depict the relation between palbociclib concentrations and absolute neutrophil counts (ANC). The models were built with a population of 143 patients. Palbociclib samples were routinely collected during therapeutic drug monitoring, whereas ANC were retrospectively retrieved from the patient files. The optimal popPK model was a mono-compartmental model with a first-order absorption constant of 0.187 h−1 and an apparent clearance Cl/F of 57.09 L (32.8% of inter individuality variability (IIV)). The apparent volume of distribution (1580 L) and the lag-time (Tlag: 0.658 h) were fixed to values from the literature. An increase in creatinine clearance and a decrease in alkaline phosphatase led to an increase in palbociclib Cl/F. To describe ANC kinetics during treatment, Friberg’s PK/PD model, with linear drug effect, was used. Parameters estimated were Base (2.92 G/L; 29.6% IIV), Slope (0.0011 L/µg; 28.8% IIV), Mean Transit Time (MTT; 5.29 days; 17.9% IIV) and γ (0.102). The only significant covariate was age on the initial ANC (Base), with lower ANC in younger patients. PK/PD model-based simulations show that the higher the estimated CressSS (trough concentration at steady state), the higher the risk of developing neutropenia. In order to present a risk lower than 20% to developing a grade 4 neutropenia, the patient should show an estimated CressSS lower than 100 µg/L.

P497 The value of endoscopic healing index monitoring for guiding infliximab dosing in patients with Crohn’s disease

Background The endoscopic healing index (EHI) is a novel multi-protein serum biomarker test developed and validated to assess endoscopic disease activity in patients with Crohn’s disease (CD). Evidence for the use of EHI to guide decision-making during infliximab (IFX) treatment remains scarce. Therefore, we aimed to characterise the relationships between IFX dose, serum IFX concentrations, EHI, and endoscopic remission (ER). Methods Data were obtained from 118 biologic naïve adult patients with CD enrolled in the phase 4 TAILORIX trial (EudraCT 2011 003038 14). All patients had confirmed active CD at baseline based on clinical, biological, and endoscopic criteria. IFX and EHI (scores ranging from 0–100) were measured using a homogenous mobility shift assay (HMSA) and immunoassay, respectively (Prometheus Laboratories). First, the previously published population pharmacokinetic (popPK) model of the TAILORIX study population was revisited to describe the HMSA data. The effect of EHI, faecal calprotectin (FC), C-reactive protein (CRP), and serum albumin (ALB) on IFX clearance was evaluated. Next, a minimal continuous-time Markov model was developed to describe the time course of EHI within patients. EHI was considered as a three-stage ordinal variable (scores 0–19, 20–49, and 50–100) with the lowest score stage (0–19) indicative of ER. The course-modifying effect of IFX on EHI was assessed. Finally, a generalised linear model was used to describe the relationship between EHI and the probability of attaining ER (Simple Endoscopic Score for CD [SES-CD] ≤2). The predictive ability of EHI for ER was compared with that of FC, CRP, ALB, and IFX using a receiver operating characteristic (ROC) curve analysis. Results The revisited two-compartment popPK model described the IFX data with adequate descriptive and predictive accuracies. EHI, FC, CRP, and ALB at week (w)0 were not found to explain interpatient variability in IFX clearance. In contrast, higher IFX at w14 was associated with a higher probability of achieving EHI &lt;20 at w14 (Figure 1). The probability of attaining EHI &lt;20 at w14 was predicted to increase more than four-fold when IFX at w14 was targeted at 10 mg/L instead of 5 mg/L (Table 1). EHI and FC equally well predicted the probability of attaining ER at the same time point (Figure 2, Table 2). Conclusion EHI, FC, ALB, and CRP at w0 should not be considered for a priori IFX dose optimisation. Nevertheless, a posteriori IFX dose optimisation (based on IFX concentrations measurements) towards a predefined IFX concentration at w14 may lead to lower post-induction EHI scores and thus improved ER rates. An IFX target of 10 mg/L at w14 is associated with four-fold higher normalisation of EHI as compared to the commonly used target of 5 mg/L.

P304 Rational infliximab induction dosing to achieve long-term deep remission in children with Inflammatory Bowel Diseases

Background Adequate infliximab (IFX) trough concentrations (TCs) during induction treatment are predictive for long-term clinical and endoscopic remission in paediatric patients with inflammatory bowel diseases (IBD). However, under the approved weight-based dosing (5 mg/kg), children often have low IFX TCs, since the relationship between bodyweight and the IFX pharmacokinetic (PK) parameters is nonlinear. Therefore, there is a need to optimise paediatric dosing to engage optimal IFX TCs during induction treatment. Methods Fifty-two paediatric patients with IBD (34 Crohn’s disease (CD), 18 ulcerative colitis (UC)) contributed IFX samples (246 intermediate and 150 trough samples) during either induction treatment (n=32) or maintenance treatment (n=20). A population PK (popPK) model was developed to describe the relationship between IFX dose and exposure. The previously published IFX popPK model based on data of 112 children with CD in the Phase 3 REACH trial was used as a frequentist prior to inform parameter estimation using NONMEM. Our popPK model was used to simulate IFX TCs during induction treatment under different induction dosing regimens (5 mg/kg, 7.5 mg/kg, and 10 mg/kg IFX at weeks 0, 2, and 6). Probabilities of TC target attainment (PTA) were compared. The TC target, associated with a 75% probability of achieving deep remission (DR) at six months after initiating IFX treatment, was identified using a logistic regression model and a ROC analysis. DR was defined as combined endoscopic remission (Simple Endoscopic Score for CD &lt;3 or Mayo endoscopic sub-score 0) and corticosteroid-free clinical remission (Paediatric CD or UC Activity Index &lt;10). Results The median boyweight was 44 kg (range 15-92 kg). A 2-compartment popPK model with first-order elimination described IFX concentrations well (Table 1). The IFX clearance by weight increased with decreasing bodyweight, decreasing serum albumin and absence of immunomodulator combo-therapy. Also, the IFX volume of distribution in the central and peripheral compartment by weight increased with decreasing bodyweight. A total of 18/32 (56%) patients in the induction treatment achieved DR at six months. An IFX TC of 23.0 mg/L at week 6 was identified as the TC target (100% sen, 33% spe, 100% npv, and 50% ppv). Children with a bodyweight less than 30 kg could only reach a 50% PTA when receiving 10 mg/kg IFX combo-therapy during induction (Figure 1). While children with a bodyweight above 30 kg had more than 50% PTA when receiving either 10 mg/kg IFX monotherapy or 7.5 mg/kg IFX combo-therapy (Table 2). Conclusion IFX doses higher than 5 mg/kg are needed during induction in children with IBD to facilitate the attainment of the TC target, thereby increasing the chance of long-term DR.

Personalized Dosing of Intravenous Vancomycin Among Critically Ill Neonates in Hong Kong: Harnessing Electronic Health Records to Develop a Web-Based Dosing Interface (Preprint)

BACKGROUND Intravenous (IV) vancomycin is used in the treatment of severe infection in neonates. It is efficacious but also associated with elevated risks of developing acute kidney injury. The risk is even higher in neonates admitted to the neonatal intensive care unit (NICU) because the pharmacokinetics of vancomycin in neonates vary widely. Therapeutic drug monitoring has been an integral part of the management to guide individual dose adjustments based on observed serum vancomycin concentrations (Cs) to balance efficacy against toxicity. However, the existing trough-based approach shows poor evidence for improved clinical outcomes. The updated clinical practice guideline recommends population pharmacokinetic (popPK) model-based approaches, targeting area under curve preferably through the Bayesian approach. Since Bayesian methods cannot be performed manually and require specialized computer programs, there is an urgent need to provide the clinicians with a user-friendly interface to facilitate accurate, personalized dosing recommendations for vancomycin in critically ill neonates. OBJECTIVE To utilize medical data from electronic health records (EHRs) to develop a popPK model and subsequently a web-based interface to perform model-based approaches to individual dose optimization of IV vancomycin for NICU patients in local medical institutions. METHODS Data were collected from EHR sources, namely Clinical Information System, In-Patient Medication Order Entry, and electronic Patient Record for subjects prescribed IV vancomycin in the NICU of Prince of Wales Hospital and Queen Elizabeth Hospital in Hong Kong. Patient demographics, serum creatinine (SCr), vancomycin administration records and Cs were collected. The popPK model used comprises a two-compartment infusion model, and various covariate models were tested against body weight, postmenstrual age (PMA), and SCr for the best goodness-of-fit. A previously published web-based dosing interface was replicated and adapted to the needs in this study. RESULTS The final dataset consisted of EHR data extracted from 207 subjects, obtaining a total of 689 Cs measurements. The final model chosen explains 82% of the variability in vancomycin clearance. All parameter estimates are within the bootstrapping confidence intervals. Predictive plots, residual plots, and visual predictive checks demonstrate good model predictability. Model approximations show that the model-based Bayesian approach consistently promotes the probability of target attainment (PTA) above 75%, while only half of the subjects can achieve PTA over 50% with the trough-based approach. The dosing interface was developed with the capability to optimize individual doses with the model-based empirical or Bayesian approach. CONCLUSIONS Utilizing EHRs, a satisfactory popPK model has been verified and used to develop the web-based individual dose optimization interface. The interface is expected to improve treatment outcomes of IV vancomycin in the treatment of severe infections among neonates in local NICUs. This study provides the foundation upon which to conduct a cohort study to demonstrate the utility of the new approach compared with previous dosing methods.

Population pharmacokinetic characteristics of cemiplimab in patients with advanced malignancies

Cemiplimab, a human monoclonal antibody targeting programmed cell death-1 (PD-1) receptor, demonstrated antitumor activity in patients with advanced malignancies and a safety profile comparable to other anti–PD-1 therapies. This population pharmacokinetics (PopPK) analysis of cemiplimab included 11,178 pharmacokinetics (PK) observations from 548 patients pooled from a first-in-human study (Study 1423; NCT02383212) in advanced malignancies and a Phase 2 study (Study 1540; NCT02760498) in advanced cutaneous squamous cell carcinoma (CSCC). Most patients (80.3%) received cemiplimab 3 mg/kg every 2 weeks (Q2W) intravenously (IV). A PopPK model was developed by evaluating two-compartment linear models with an empirical non-linear function describing time-varying change in cemiplimab clearance and covariates that improved goodness-of-fit. PopPK simulations were used to describe cemiplimab exposure generated by a fixed 350 mg every 3 weeks (Q3W) IV dose regimen. PopPK modeling showed that a two-compartment model with zero-order IV infusion rate and first-order elimination rate well described individual concentrations of cemiplimab. Although several covariates, including baseline body weight and albumin concentrations, had a modest impact on cemiplimab exposure, the magnitude of influence was within the typical observed PK variability of approximately 30%. Based on PopPK simulation results, the 350 mg Q3W dose regimen was selected for further studies in advanced malignancies, including advanced CSCC. Similarity in observed cemiplimab exposure at the fixed 350 mg Q3W and the weight-based 3 mg/kg Q2W dose regimens confirmed this fixed dose selection. A robust PopPK model was developed to describe cemiplimab concentrations and supported use of the fixed 350 mg Q3W IV dose regimen.

Population Pharmacokinetics and Exposure–Safety Relationship of Paclitaxel Liposome in Patients With Non-small Cell Lung Cancer

PurposePaclitaxel liposome (Lipusu) is the first commercialized liposomal formulation of paclitaxel. There has been little data collected on the pharmacokinetics (PK) of paclitaxel liposome, especially in relation to patient use. This study aimed to build a population pharmacokinetic (PopPK) model and further explore the exposure–safety relationship for paclitaxel liposome in patients with non-small cell lung cancer (NSCLC).MethodsData from 45 patients with a total of 349 plasma concentrations were analyzed. The PopPK model was built using the non-linear mixed effect modeling technique.ResultsThe PK of paclitaxel liposome were well described by a three-compartment model with first-order elimination. For a dose of 175 mg m–2, the estimated clearance of total plasma paclitaxel was 21.55 L h–1. Age, sex, body weight, total bilirubin, albumin, serum creatinine, and creatinine clearance did not influence the paclitaxel PK. Exposure to paclitaxel had no significant change in the presence of the traditional Chinese medicine, aidi injection. The exploratory exposure–safety relationship was well described by a generalized linear regression model. Higher probabilities of grade &gt;1 neutropenia were observed in patients with higher exposure to paclitaxel.ConclusionThis PopPK model adequately described the PK of paclitaxel liposome in patients with NSCLC. Predicted exposure of paclitaxel did not change in the presence of the traditional Chinese medicine, aidi injection. The exposure–safety analysis suggested that a higher risk of neutropenia was correlated with higher exposure to paclitaxel.

Population Pharmacokinetics and Exposure-Response Analyses for Glofitamab in Relapsed/Refractory B-Cell Non-Hodgkin Lymphoma (R/R NHL): Confirmation of Efficacy and CRS Mitigation in Patients with Step-up Dosing

Introduction: Glofitamab (RG6026; RO7082859; CD20-TCB) is a novel '2:1' format T-cell-engaging bispecific antibody that has two CD20 and one CD3 binding domains, enabling increased tumor antigen avidity, rapid T-cell activation, and enhanced tumor cell killing in B-cell malignancies. Clinical data from NP30179 demonstrated that fixed dosing of glofitamab (0.6-25mg) induced high and durable complete responses with a manageable safety profile in heavily pre-treated R/R NHL patients (pts; Dickinson, et al. EHA 2020). Obinutuzumab pretreatment (Gpt) 7 days prior to first administration of glofitamab was shown to be effective in mitigating the risk of cytokine release syndrome (CRS), allowing for rapid escalation of glofitamab to clinically active doses (Dickinson, et al. EHA 2020). We previously investigated population pharmacokinetics (popPK) and exposure-response (ER) relationships for glofitamab in NP30179; NCT03075696 (Djebli N, et al. Blood 2019), where modelling indicated step-up dosing would further mitigate CRS while maximizing efficacy. The present analysis is an update of previous models, including confirmatory data from the first step-up dosing (SUD) pts. Methods: Pts with indolent (i) or aggressive (a) R/R NHL received glofitamab fixed dosing (0.005-25mg every 2 or 3 weeks) or SUD (n=31, 2.5/10/16 and 2.5/10/30mg) following single Gpt 1000mg on Cycle (C) 1 Day (D) −7 to mitigate CRS. Serial and sparse glofitamab, and sparse G PK data were used to develop a popPK model in NONMEM® software (v7.4). The cut-off date of April 17, 2020 enabled inclusion of 16 (2.5/10/16mg) and 15 (2.5/10/30mg) SUD pts. Physiologically relevant covariates were investigated for their potential influence on glofitamab PK variability. Using the established G popPK model (Gibiansky, et al. CPT Pharmacometrics Syst Pharmacol 2014), G concentration-time profiles were constructed to estimate glofitamab receptor occupancy (RO%) in the presence of G competing for CD20 receptors over time. The relationship between glofitamab AvgRO% over the first 24 hours and CRS, with a focus on Grade (Gr) ≥2 CRS (defined by ASTCT criteria [Lee, et al. 2019]) was investigated in iNHL and aNHL pts combined. ER relationships between glofitamab time-averaged RO% (AvgRO%) up to C3D1, which is when the first response assessment was taken, and complete response rate (CRR) were characterized in aNHL pts who reached C3D1. Results : PopPK were analyzed in 230 iNHL and aNHL pts with ≥1 PK sample (fixed and SUD). ER relationships were analyzed in 95 aNHL pts with PK/efficacy data at C3D1, and in 204 iNHL and aNHL pts with PK/safety data. Glofitamab PK were best described using a two-compartment PK model with linear clearance and were comparable in pts with iNHL and aNHL. The effect of bodyweight on volumes and clearances was retained. Positive ER relationships were observed between AvgRO% over the first 24 hours and Gr ≥2 CRS in both iNHL and aNHL pts (p=0.002; Figure 1A), and between AvgRO% up to C3D1 and efficacy in aNHL pts (p=0.008; Figure 1B). Based on previous ER analyses (Djebli, et al. Blood 2019) of data from pts receiving fixed dosing, a SUD regimen (2.5/10/30mg Q3W) was selected to optimize the benefit/risk profile by beginning treatment at a dose to have CRS at manageable levels whilst allowing escalation to a higher dose associated with better clinical response. Updated ER analysis from fixed (n=199) and SUD (n=31) pts predicts an AvgRO% in the first 24 hours of 0.16% (0.10-0.29%), corresponding to a predicted Gr ≥2 CRS rate of 23.3% (20.8-26.8%) in iNHL and aNHL pts, and an AvgRO% to C3D1 of 0.75% (0.49-1.98%) corresponding to an anticipated CRR at Cycle 3 of 46.1% (42.7-53.8%) in aNHL pts. In comparison, clinical data from aNHL and iNHL pts receiving 2.5/10/16 and 2.5/10/30mg SUD (Hutchings, et al. ASH 2020) demonstrated a Gr ≥2 CRS rate of 21.6 % following the 2.5mg glofitamab dose (n=37), and a complete metabolic response rate of 40.6% (n=32). Conclusions: Glofitamab PopPK and ER relationships for efficacy/safety were updated, including data from SUD pts. These models and emerging SUD clinical data confirm that in NHL pts, the SUD regimen allowed glofitamab escalation up to 30mg to maximize efficacy while minimizing the risk of increased CRS at the first administration. These models are being developed further to support optimal biological-dose selection of glofitamab, both as monotherapy and in combination with other agents. Disclosures Djebli: F. Hoffmann-La Roche: Current Employment, Current equity holder in private company. Morcos:F. Hoffmann-La Roche: Current equity holder in publicly-traded company, Ended employment in the past 24 months. Jaminion:F. Hoffmann-La Roche: Current Employment, Current equity holder in private company. Guerini:F. Hoffmann-La Roche: Current Employment, Current equity holder in private company. Kratochwil:F. Hoffmann-La Roche: Current Employment. Justies:F. Hoffmann-La Roche: Current Employment. Schick:F. Hoffmann-La Roche: Current Employment. Kwan:Genentech, Inc./ F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Humphrey:F. Hoffmann-La Roche: Current Employment, Current equity holder in private company, Current equity holder in publicly-traded company. Lundberg:F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company. Carlile:F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company; AstraZeneca: Current equity holder in publicly-traded company, Ended employment in the past 24 months. OffLabel Disclosure: Glofitamab (RG6026; CD20-TCB) is a full-length, fully humanized immunoglobulin G1 (IgG1) bispecific antibody with a 2:1 molecular format that facilitates bivalent binding to CD20 on B-cells, and monovalent binding to CD3 on T-cells. Glofitamab redirects T cells to engage and eliminate malignant B cells. Glofitamab is an investigational agent.