First-Line Nivolumab and Relatlimab Plus Chemotherapy for Gastric or Gastroesophageal Junction Adenocarcinoma: The Phase II RELATIVITY-060 Study.

PURPOSE: Open-label phase II study (RELATIVITY-060) to investigate the efficacy and safety of first-line nivolumab, a PD-1-blocking antibody, plus relatlimab, a lymphocyte-activation gene 3 (LAG-3)-blocking antibody, plus chemotherapy in patients with previously untreated advanced gastric cancer (GC) or gastroesophageal junction cancer (GEJC). METHODS: Patients with unresectable, locally advanced or metastatic GC/GEJC were randomly assigned 1:1 to nivolumab + relatlimab (fixed-dose combination) + chemotherapy or nivolumab + chemotherapy. The primary end point was objective response rate (ORR; per RECIST v1.1 by blinded independent central review [BICR]) in patients whose tumors had LAG-3 expression ≥1%. RESULTS: Of 274 patients, 138 were randomly assigned to nivolumab + relatlimab + chemotherapy and 136 to nivolumab + chemotherapy. Median follow-up was 11.9 months. In patients with LAG-3 expression ≥1%, BICR-assessed ORR (95% CI) was 48% (38 to 59) in the nivolumab + relatlimab + chemotherapy arm and 61% (51 to 71) in the nivolumab + chemotherapy arm; median progression-free survival (95% CI) by BICR was 7.0 months (5.8 to 8.4) versus 8.3 months (6.9 to 12.1; hazard ratio [HR], 1.41 [95% CI, 0.97 to 2.05]), and median overall survival (95% CI) was 13.5 months (11.9 to 19.1) versus 16.0 months (10.9 to not estimable; HR, 1.04 [95% CI, 0.70 to 1.54]), respectively. Grade 3 or 4 treatment-related adverse events (TRAEs) occurred in 69% and 61% of all treated patients, and 42% and 36% of patients discontinued because of any-grade TRAEs in the nivolumab + relatlimab + chemotherapy and nivolumab + chemotherapy arms, respectively. CONCLUSION: RELATIVITY-060 did not meet its primary end point of improved ORR in patients with LAG-3 expression ≥1% when relatlimab was added to nivolumab + chemotherapy compared with nivolumab + chemotherapy. Further studies are needed to address whether adding anti-LAG-3 to anti-PD-1 plus chemotherapy can benefit specific GC/GEJC patient subgroups.

Final results of urelumab, an anti-CD137 agonist monoclonal antibody, in combination with cetuximab or nivolumab in patients with advanced solid tumors.

BACKGROUND: Resistance to immune checkpoint inhibitors and targeted treatments for cancer is common; thus, novel immunotherapy agents are needed. Urelumab is a monoclonal antibody agonist that binds to CD137 receptors expressed on T cells. Here, we report two studies that evaluated urelumab in combination with cetuximab or nivolumab in patients with select, advanced solid tumors. METHODS: CA186-018: Patients with metastatic colorectal cancer or metastatic squamous cell carcinoma of the head and neck (SCCHN) were treated in a dose-evaluation phase with urelumab 0.1 mg/kg (urelumab-0.1) every 3 weeks (Q3W)+cetuximab 250 mg/m2 (cetuximab-250) weekly; and in a dose-expansion phase with urelumab 8 mg flat dose (urelumab-8) Q3W+cetuximab-250 weekly. CA186-107: The dose-escalation phase included patients with previously treated advanced solid tumors (or treated or treatment-naive melanoma); patients received urelumab 3 mg flat dose (urelumab-3) or urelumab-8 every 4 weeks+nivolumab 3 mg/kg (nivolumab-3) or 240 mg (nivolumab-240) every 2 weeks. In the expansion phase, patients with melanoma, non-small cell lung cancer, or SCCHN were treated with urelumab-8+nivolumab-240. Primary endpoints were safety and tolerability, and the secondary endpoint included efficacy assessments. RESULTS: CA186-018: 66 patients received study treatment. The most frequent treatment-related adverse events (TRAEs) were fatigue (75%; n=3) with urelumab-0.1+cetuximab-250 and dermatitis (45%; n=28) with urelumab-8+cetuximab-250. Three patients (5%) discontinued due to TRAE(s) (with urelumab-8+cetuximab-250). One patient with SCCHN had a partial response (objective response rate (ORR) 5%, with urelumab-8+cetuximab-250).CA186-107: 134 patients received study treatment. Fatigue was the most common TRAE (32%; n=2 with urelumab-3+nivolumab-3; n=1 with urelumab-8+nivolumab-3; n=40 with urelumab-8+nivolumab-240). Nine patients (7%) discontinued due to TRAE(s) (n=1 with urelumab-3+nivolumab-3; n=8 with urelumab-8+nivolumab-240). Patients with melanoma naive to anti-PD-1 therapy exhibited the highest ORR (49%; n=21 with urelumab-8+nivolumab-240). Intratumoral gene expression in immune-related pathways (CD3, CD8, CXCL9, GZMB) increased on treatment with urelumab+nivolumab. CONCLUSIONS: Although the addition of urelumab at these doses was tolerable, preliminary response rates did not indicate an evident additive benefit. Nevertheless, the positive pharmacodynamics effects observed with urelumab and the high response rate in treatment-naive patients with melanoma warrant further investigation of other anti-CD137 agonist agents for treatment of cancer. TRIAL REGISTRATION NUMBERS: NCT02110082; NCT02253992.

Model-Informed Clinical Pharmacology Profile of a Novel Fixed-Dose Combination of Nivolumab and Relatlimab in Adult and Adolescent Patients with Solid Tumors.

PURPOSE: Progression-free survival (PFS) was significantly improved with nivolumab 480 mg plus relatlimab 160 mg fixed-dose combination (FDC) every 4 weeks (Q4W) vs nivolumab alone in patients with previously untreated advanced melanoma in RELATIVITY-047. Additionally, RELATIVITY-020 (Part D) demonstrated a manageable safety profile and potential for durable response with nivolumab plus relatlimab in previously treated patients. Here we evaluate the clinical pharmacology profile (CPP) of nivolumab plus relatlimab to support the approved regimen for adult and adolescent patients with advanced melanoma and its continued clinical development in solid tumors. PATIENTS AND METHODS: The pharmacokinetics (PK) and immunogenicity of relatlimab and nivolumab were assessed using data from RELATIVITY-047 and RELATIVITY-020. Patients with advanced solid tumors received relatlimab alone or nivolumab plus relatlimab as single-agent vials (SAV) or FDC. PK was characterized using a population PK (popPK) model. RESULTS: Relatlimab demonstrated nonlinear and time-varying PK. Nonlinearity in relatlimab PK represented ~31% of total CL of relatlimab 160 mg Q4W. Relatlimab PK was dose proportional at doses ≥160 mg Q4W. Geometric mean exposures were similar for SAV and FDC cohorts receiving equivalent dosing regimens. No dose adjustment was required for covariates. Incidence of relatlimab antidrug antibodies was <6% for nivolumab plus relatlimab and had no clinically meaningful impact. There was no PK-related drug interaction of nivolumab plus relatlimab. CONCLUSION: The CPP of relatlimab alone or in combination with nivolumab supports the approved dosing in advanced melanoma and the continued evaluation of nivolumab and relatlimab across other solid tumors.

Nivolumab and Relatlimab in Patients With Advanced Melanoma That Had Progressed on Anti-Programmed Death-1/Programmed Death Ligand 1 Therapy: Results From the Phase I/IIa RELATIVITY-020 Trial.

PURPOSE: Nivolumab and relatlimab activity in advanced melanoma with prior progression on anti-programmed death-1/programmed death ligand 1 (PD-(L)1)-containing regimens is under investigation. RELATIVITY-047 demonstrated significantly improved progression-free survival (PFS) for nivolumab and relatlimab over nivolumab in previously untreated advanced melanoma. METHODS: The phase I/IIa, open-label RELATIVITY-020 trial part D assessed efficacy and safety of nivolumab and relatlimab in advanced melanoma with progression during, or within 3 months of, 1 (D1) or ≥ 1 (D2) anti-PD-(L)1-containing regimens. Safety was a primary end point. Objective response rate (coprimary end point) and PFS by blinded independent central review (BICR) were assessed. RESULTS: Five hundred eighteen patients (D1 = 354; D2 = 164) received nivolumab and relatlimab. Among evaluable patients, the objective response rate by BICR was 12.0% (95% CI, 8.8 to 15.8) in D1 (n = 351) and 9.2% (95% CI, 5.2 to 14.7) in D2 (n = 163). Responses appeared to be enriched among patients with tumors expressing programmed death ligand 1 or lymphocyte activation gene 3; however, responses were observed regardless of programmed death ligand 1 and lymphocyte activation gene 3 expression (1%). The median duration of response was not reached (95% CI, 12.9 to not reached) in D1 and 12.8 months (95% CI, 6.9 to 12.9) in D2. The median PFS by BICR was 2.1 months (95% CI, 1.9 to 3.5) in D1 and 3.2 months (95% CI, 1.9 to 3.6) in D2; the 6-month PFS rate was 29.1% (95% CI, 24.2 to 34.1) and 27.7% (95% CI, 20.5 to 35.4), respectively. The grade 3-4 treatment-related adverse event incidence was 15.0% in D1 and 12.8% in D2. One case of grade 3 myocarditis and no treatment-related deaths occurred across part D. CONCLUSION: Nivolumab and relatlimab had a manageable safety profile and demonstrated durable clinical activity in a proportion of patients with heavily pretreated advanced melanoma with prior progression on anti-PD-(L)1-containing regimens.[Media: see text].

Nivolumab exposure-response analysis for adjuvant treatment of melanoma supporting a change in posology.

Nivolumab monotherapy is approved as adjuvant treatment for melanoma based on results from the pivotal CheckMate 238 trial. We present a model-based, benefit-risk assessment of nivolumab in adjuvant melanoma supporting a posology change from a weight-based to a less frequent, flat-dosing regimen. The exposure-response (E-R) relationship for efficacy was evaluated using recurrence-free survival (RFS) and distant metastasis-free survival (DMFS) end points from the CheckMate 238 trial. The E-R for safety was evaluated using data from 14 studies across a broad range of doses in several tumor types using grade 3+ adverse event (AE) and grade 2+ immune-mediated AE (IMAE) end points. Nivolumab trough exposures were not significant predictors of RFS or DMFS. Covariates significantly associated with increased risk of disease recurrence or death were programmed death ligand 1 (PD-L1; less than 5% cutoff), lower baseline lactate dehydrogenase, and higher age. Covariates associated with increased risk of distant metastasis or death were PD-L1 (less than 5% cutoff) and higher age. Higher nivolumab maximum concentration after first dose (Cmax1) was significantly associated with grade 2+ IMAEs, but not grade 3+ AEs. The risk of grade 3+ AEs was significantly lower in adjuvant versus advanced melanoma. Eastern Cooperative Oncology Group Performance Status higher than zero was associated with higher incidences of grade 2+ IMAEs and grade 3+ AEs. Female patients had significantly higher incidences of grade 2+ IMAEs than male patients. Nivolumab monotherapy in adjuvant melanoma demonstrated a relatively flat E-R relationship over the range of exposures produced by 3 mg/kg every 2 weeks and predicted a comparable benefit-risk profile to flat-dosing regimens.

Pharmacokinetics and Clinical Pharmacology of Monoclonal Antibodies in Pediatric Patients.

Monoclonal antibodies (mAbs) and their derivatives are increasingly used in pediatric pharmacotherapy, and the number of antibody-based drug products with approved pediatric indications is continuously growing. In most instances, pediatric use is being pursued after the efficacy and safety of novel antibody medications have been established in adult indications. The pediatric extrapolation exercise that is frequently used in this context to bridge efficacy and safety from adults to children is oftentimes challenged through uncertainties and knowledge gaps in how to reliably extrapolate pharmacokinetics and clinical pharmacology of mAbs to different pediatric age groups, and how to derive age-appropriate dosing regimens that strike a balance between precision dosing and practicability. The article highlights some of the pharmacokinetic and clinical pharmacology challenges with regard to therapeutic use of mAbs and antibody derivatives in children, including immunogenicity events. Although considering body size-based differences in drug disposition can account for many of the perceived and actual differences in the distribution and elimination of antibody-based therapeutics between children and adults, increasing evidence suggests potential or actual age-associated differences beyond size differences, especially for young pediatric patients such as newborns and infants. To overcome age-associated differences in antibody disposition, various different dosing approaches have been applied to ensure safe and efficacious antibody exposure for pediatric populations of different ages. The development of such dosing regimens and the associated pathway to pediatric indication approval is illustrated in more detail for two antibody-based biologics, the fusion protein abatacept and the mAb tocilizumab.

Urelumab alone or in combination with rituximab in patients with relapsed or refractory B-cell lymphoma.

Urelumab, a fully human, non-ligand binding, CD137 agonist IgG4 monoclonal antibody, enhances T-cell and natural killer-cell antitumor activity in preclinical models, and may enhance cytotoxic activity of rituximab. Here we report results in patients with relapsed or refractory diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and other B-cell lymphomas, in phase 1 studies evaluating urelumab alone (NCT01471210) or combined with rituximab (NCT01775631). Sixty patients received urelumab (0.3 mg/kg IV Q3W, 8 mg IV Q3W, or 8 mg IV Q6W); 46 received urelumab (0.1 mg/kg, 0.3 mg/kg, or 8 mg IV Q3W) plus rituximab 375 mg/m2 IV QW. The maximum tolerated dose (MTD) of urelumab was determined to be 0.1 mg/kg or 8 mg Q3W after a single event of potential drug-induced liver injury occurred with urelumab 0.3 mg/kg. Treatment-related AEs were reported in 52% (urelumab: grade 3/4, 15%) and 72% (urelumab + rituximab: grade 3/4, 28%); three led to discontinuation (grade 3 increased AST, grade 4 acute hepatitis [urelumab]; one death from sepsis syndrome [urelumab plus rituximab]). Objective response rates/disease control rates were 6%/19% (DLBCL, n = 31), 12%/35% (FL, n = 17), and 17%/42% (other B-cell lymphomas, n = 12) with urelumab and 10%/24% (DLBCL, n = 29) and 35%/71% (FL, n = 17) with urelumab plus rituximab. Durable remissions in heavily pretreated patients were achieved; however, many were observed at doses exceeding the MTD. These data show that urelumab alone or in combination with rituximab demonstrated manageable safety in B-cell lymphoma, but the combination did not enhance clinical activity relative to rituximab alone or other current standard of care.

Linking Tumor Growth Dynamics to Survival in Ipilimumab-Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling.

Early tumor assessments have been widely used to predict overall survival (OS), with potential application to dose selection and early go/no-go decisions. Most published tumor dynamic models assume a uniform pattern of tumor growth dynamics (TGDs). We developed a mixture TGD model to characterize different patterns of longitudinal tumor sizes. Data from 688 patients with advanced melanoma who received ipilimumab 3 or 10 mg/kg every 3 weeks in a phase III study (NCT01515189) were used in a TGD-OS analysis. The mixture model described TGD profiles using three subpopulations (no-growth, intermediate, and fast). The TGD model showed a positive exposure/dose-response (i.e., a higher proportion of patients in no/intermediate growth subpopulations and a lower tumor growth rate with ipilimumab 10 mg/kg relative to the 3 mg/kg dose). Finally, the mixture TGD model-based measures of tumor response provided better predictions of OS compared with the nonmixture model.

Evaluation of covariate effects on pharmacokinetics of monoclonal antibodies in oncology.

AIMS: The development of monoclonal antibodies (mAbs) requires an understanding of the interindividual variability (IIV) in pharmacokinetics (PK) at the population level facilitated by population PK (PopPK) modelling. However, there is no clear rationale for selecting which covariates to screen during PopPK model development. Here, we compare the effect of covariates on PK parameters for mAbs in oncology and identify the most commonly used covariates affecting PK parameters. METHODS: All 25 mAbs approved for therapeutic use in oncology until December 2017 by the Food and Drug Administration and the European Medicines Agency were selected for study. Literature searches revealed 23 available PopPK models for these mAbs. To understand the magnitude and types of covariate effect on PK parameters, all covariates included in the final PopPK model for each mAb were summarized. RESULTS: The most commonly identified covariates were baseline body weight (BW; 17 mAbs), baseline serum albumin (8 mAbs), and sex (7 mAbs) on clearance; and BW (16 mAbs) and sex (12 mAbs) on central volume of distribution. A reduced PopPK model was developed for nivolumab and ipilimumab using these covariates, and the percentage of explained IIV from the reduced model (20.3% and 16.8%, respectively) was compared with that from the full model (24.5% and 27.9%, respectively). CONCLUSIONS: This analysis provides a uniform platform for selecting covariates and suggests that the effect of BW, albumin and sex should be included during the development of PopPK models for mAbs in oncology. The reduced model was able to explain IIV to a similar extent as the full model.

Reporting, Visualization, and Modeling of Immunogenicity Data to Assess Its Impact on Pharmacokinetics, Efficacy, and Safety of Monoclonal Antibodies.

The rapidly increasing number of therapeutic biologics in development has led to a growing recognition of the need for improvements in immunogenicity assessment. Published data are often inadequate to assess the impact of an antidrug antibody (ADA) on pharmacokinetics, safety, and efficacy, and enable a fully informed decision about patient management in the event of ADA development. The recent introduction of detailed regulatory guidance for industry should help address many past inadequacies in immunogenicity assessment. Nonetheless, careful analysis of gathered data and clear reporting of results are critical to a full understanding of the clinical relevance of ADAs, but have not been widely considered in published literature to date. Here, we review visualization and modeling of immunogenicity data. We present several relatively simple visualization techniques that can provide preliminary information about the kinetics and magnitude of ADA responses, and their impact on pharmacokinetics and clinical endpoints for a given therapeutic protein. We focus on individual sample- and patient-level data, which can be used to build a picture of any trends, thereby guiding analysis of the overall study population. We also discuss methods for modeling ADA data to investigate the impact of immunogenicity on pharmacokinetics, efficacy, and safety.

Results from an Integrated Safety Analysis of Urelumab, an Agonist Anti-CD137 Monoclonal Antibody.

Purpose: Urelumab is an agonist antibody to CD137 with potential application as an immuno-oncology therapeutic. Data were analyzed to assess safety, tolerability, and pharmacodynamic activity of urelumab, including the dose selected for ongoing development in patients with advanced solid tumors and lymphoma.Experimental Design: A total of 346 patients with advanced cancers who had progressed after standard treatment received at least one dose of urelumab in one of three dose-escalation, monotherapy studies. Urelumab was administered at doses ranging from 0.1 to 15 mg/kg. Safety analyses included treatment-related and serious adverse events (AEs), as well as treatment-related AEs leading to discontinuation and death, with a focus on liver function test abnormalities and hepatic AEs.Results: Urelumab doses between 1 and 15 mg/kg given every 3 weeks resulted in a higher frequency of treatment-related AEs than 0.1 or 0.3 mg/kg every 3 weeks. Dose was the single most important factor contributing to transaminitis development, which was more frequent and severe at doses ≥1 mg/kg. At the MTD of 0.1 mg/kg every 3 weeks, urelumab was relatively well tolerated, with fatigue (16%) and nausea (13%) being the most common treatment-related AEs, and was associated with immunologic and pharmacodynamic activity demonstrated by the induction of IFN-inducible genes and cytokines.Conclusions: Integrated evaluation of urelumab safety data showed significant transaminitis was strongly associated with doses of ≥1 mg/kg. However, urelumab 0.1 mg/kg every 3 weeks was demonstrated to be safe, with pharmacodynamic activity supporting continued clinical evaluation of this dose as monotherapy and in combination with other immuno-oncology agents. Clin Cancer Res; 23(8); 1929-36. ©2016 AACR.

Preclinical pharmacokinetic/pharmacodynamic modeling and simulation in the pharmaceutical industry: an IQ consortium survey examining the current landscape.

The application of modeling and simulation techniques is increasingly common in preclinical stages of the drug discovery and development process. A survey focusing on preclinical pharmacokinetic/pharmacodynamics (PK/PD) analysis was conducted across pharmaceutical companies that are members of the International Consortium for Quality and Innovation in Pharmaceutical Development. Based on survey responses, ~68% of companies use preclinical PK/PD analysis in all therapeutic areas indicating its broad application. An important goal of preclinical PK/PD analysis in all pharmaceutical companies is for the selection/optimization of doses and/or dose regimens, including prediction of human efficacious doses. Oncology was the therapeutic area with the most PK/PD analysis support and where it showed the most impact. Consistent use of more complex systems pharmacology models and hybrid physiologically based pharmacokinetic models with PK/PD components was less common compared to traditional PK/PD models. Preclinical PK/PD analysis is increasingly being included in regulatory submissions with ~73% of companies including these data to some degree. Most companies (~86%) have seen impact of preclinical PK/PD analyses in drug development. Finally, ~59% of pharmaceutical companies have plans to expand their PK/PD modeling groups over the next 2 years indicating continued growth. The growth of preclinical PK/PD modeling groups in pharmaceutical industry is necessary to establish required resources and skills to further expand use of preclinical PK/PD modeling in a meaningful and impactful manner.