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313 Background: In a phase II study in uHCC (Study 22, NCT02519348), a novel, priming combination regimen of tremelimumab (T; anti-CTLA-4) and durvalumab (D; anti-PD-L1) (T300+D) has shown favorable clinical activity vs each agent as monotherapy or vs another combination (T75+D). The analyses presented here assess the pharmacokinetics (PK) and relationships between tremelimumab exposure, as monotherapy or in combination, and safety, efficacy, and pharmacodynamics (PD) in this study. Methods: Overall, 216 pts were included in these analyses (T, n=65; T300+D, n=72; T75+D, n=79). Safety, antitumor activity, PK, PD, and immunogenicity were analyzed using standard pharmacometrics methods. A previously developed population PK model for T across solid tumors was validated using T monotherapy and combination therapy data from Study 22, including a post-hoc covariate analysis to assess the impact of covariates on individual PK parameters. Population PK and PD models related individual T exposures to safety parameters, PD, and efficacy (overall survival, OS; progression-free survival, PFS; and objective response rate, ORR). The E-R relationships for time-to-event variables OS and PFS were explored by Kaplan-Meier estimates and analyzed by Cox proportional-hazards models (CPHM). Results: For T monotherapy and T+D combinations, no significant E-S relationships were observed for grade 3/4 treatment-related adverse events (TRAEs), grade 3/4 TRAEs of special interest, and AEs leading to treatment discontinuation. Analyses of each quartile of T exposure suggest pts with higher exposure (3rd and 4th quartile) may have longer OS vs lower quartiles. The CPHManalysis showed that after accounting for prognostic factors (baseline albumin and neutrophil-to-lymphocyte ratio), neither AUC nor Cmin appeared to be a significant factor for OS hazard. There was no significant relationship between response and ORR, PFS and any T PK exposure metric in T-treated pts. Saturable relationships (described by Emax) were observed for maximum change from baseline for proliferating T-cell counts as functions of exposure. Conclusions: The observed PK data are generally consistent with predictions based on a historical population PK model, suggesting the PK of T in uHCC pts is consistent with pts with other solid tumors. No significant relationships were observed between E-S and E-R; therefore, PK is not a significant predictor to evaluate for T efficacy or safety. Considering the small sample size limitation, still the saturable relationships observed in proliferating T-cells appear to support a dose of T300. Future studies of pooled data from Study 22 and the larger phase III HIMALAYA study (NCT03298451) will be conducted to further the characterization of E-R relationships and the development of the T300+D regimen. Clinical trial information: NCT02519348.

6549 Background: Optimal patient selection for immunotherapy remains a challenge as most patients fail to respond. We aim to assess baseline factors for association with long-term survival from durvalumab treatment in patients with recurrent/metastatic head and neck squamous cell carcinoma (HNSCC)1,2. Methods: Pooled longitudinal tumor size, survival, and dropout data from four trials (1108: NCT01693562, CONDOR: NCT02319044 , HAWK: NCT02207530, and EAGLE: NCT02369874) involving 467 HNSCC patients were used to develop tumor size-driven hazard models. A panel of 66 serum protein biomarkers at baseline and 4 relevant clinical markers from 346 out of 413 patients treated with durvalumab (all studies except 1108) were initially screened to select a pool of 21 candidate covariates. The criteria for dimensionality reduction comprised correlation strength between biomarkers and pharmacological hypotheses pertaining to a prior analysis3 (inflammation, immunomodulation, tumor burden and angiogenesis). Results: The final tumor model highlighted that high tumor burden, elevated LDH and neutrophil-lymphocyte ratio were associated with faster tumor growth while patients with lower baseline tumor burden had an increase in net tumor shrinkage. For overall survival, the model suggested that high levels of immunomodulators (IL23, Osteocalcin), low inflammation (IL6, NLR), low tumor burden, and low angiogenesis factors (von Willebrand factor (vWF), plasminogen activator inhibitor-1 (PAI-1)) were associated with survival benefits for patients treated with durvalumab. Specifically, these patients had baseline serum IL23 > 2.1 pg/mL and Osteocalcin > 32 pg/mL or serum PAI-1 < 229 pg/mL and serum IL6 < 5.4 pg/mL which corresponded to a hazard ratio estimate (HR and 95%CI) of 0.36 (0.27- 0.47), logrank p-value: 2.3x10−14. The median (n, 95%CI) overall survival time for the patients with favorable biomarker profile was 14.6 months (n = 129, 11.2-21.4) vs. 4.4 months (n = 217, 3.6-5.3). Conclusions: Our results corroborate the prior hypothesis highlighting the prognostic value of inflammation, disease burden, tumor angiogenesis, and immunomodulatory factors on the clinical outcomes of HNSCC patients treated with durvalumab3. Collectively, we identified a serum biomarker profile of HNSCC patients with median survival times exceeding 1 year which may potentially be used for patient enrichment following further validation in prospective studies. References: 1Yanan CPT 2017, 2Baverel, 2018 ENA, 3Guo, X, 2019 Asco P6048 Clinical trial information: NCT01693562, NCT02319044, NCT02207530, NCT02369874 .

2566 Background: Durvalumab is a human monoclonal antibody that binds to PD-L1 and blocks its interaction with PD-1 and CD80. The objectives of this analysis were to develop a population pharmacokinetics (PK) model of durvalumab, to quantitate the effect of patient/disease characteristics on PK, and to compare weight (WT)-based versus fixed dosing regimens. Methods: Data were pooled from two studies: Study 1108 (Phase 1/2; various tumor types) and ATLANTIC (Phase 2; NSCLC). A total of 1324 patients provided data following 0.1 to 20 mg/kg IV durvalumab. The population PK was performed using a non-linear mixed effects modeling approach in NONMEM software. The impact of demographics, clinical indices, and biomarkers on PK was explored. Results: Durvalumab PK was best described using a 2-compartment model with both linear and non-linear clearances. The mean (between-patient variability) linear clearance (CL) and central volume of distribution (V1) were 226 mL/day (~29%) and 3.51 L (~21%), respectively. Although population PK analysis identified a few statistically significant covariates (WT, sex, CrCL, post-baseline ADA, ECOG performance status, LDH, sPDL1 levels, tumor type, and albumin), none were found to be clinically relevant (effect on PK parameters < 30%), indicating no need for dose adjustment. Simulations indicated similar overall PK exposures following WT-based (10 mg/kg Q2W) and fixed dosing regimens (1500 mg Q4W or 750 mg Q2W); with all regimens expected to maintain target trough exposure of ~50 µg/mL in ≥95% patients. In a post-hoc analysis, durvalumab clearance was found to decrease slightly over time, with a mean maximal reduction from baseline value of 15.5%. The decrease in CL was associated with tumor shrinkage, decreased LDH, increased albumin and decreased neutrophil to lymphocyte ratio. The small decrease in CL was not considered relevant to PK exposure or dosing. Conclusions: A population PK model of durvalumab was developed and validated. No dose adjustments were needed based on any patient or disease characteristics. The analysis demonstrated the feasibility of switching to a fixed dose regimen. Clinical trial information: NCT02087423 and NCT01693562.

11555 Background: Durvalumab is a human monoclonal antibody that binds to PD-L1 and blocks its interaction with PD-1 and CD80. The primary objectives of this analysis were to describe the longitudinal tumor size profiles and identify the key factors predicting tumor growth and regression following durvalumab. Methods: Longitudinal tumor size data obtained from NSCLC patients in study 1108 (all lines of therapy) and ATLANTIC (third line and beyond) following durvalumab treatment were modeled using nonlinear mixed effect modeling. Tumor kinetics were described by four key parameters: tumor growth and killing rate constants, fraction of durvalumab-sensitive tumor cells, and delay time for tumor killing. Potential predictive factors for tumor growth and regression were evaluated in a multi-variable covariate analysis. The model was used to simulate response rates at different tumor PD-L1 expression cutoffs. Results: Tumor kinetic modeling accurately described the longitudinal tumor response profiles from NSCLC patients in both studies. The factors associated with more rapid tumor growth were liver metastases, ECOG score > 0, high neutrophil-to-lymphocyte ratio and EGFR/ALK mutation. Tumor cell PD-L1 expression, baseline tumor size and smoking history were identified as significant predictive factors for tumor killing or the fraction of sensitive tumor cells. Simulations using the tumor kinetic model showed increased response rates in patients with higher tumor cell PD-L1 expression (increased by 9-11% and 10-14% with 25% and 50% cutoff, respectively), patients receiving durvalumab as first-line therapy (increased by 12% vs. 2nd line/above), and patients with smoking histories (increased by 4-5% vs. non-smokers). Conclusions: Tumor kinetic modeling identified factors that predict tumor progression and response following durvalumab in NSCLC patients. The multivariate analysis accounts for various predictive factors within predictive biomarker strata, allowing better interpretation of different biomarker cutoffs. The modeling technique can potentially guide patient selection/enrichment, clinical trial design strategies and tumor biology. Clinical trial information: NCT02087423 and NCT01693562.

3035 Background: Progression of cancer is often associated with biomarkers of cancer inflammation, cachexia, and increased protein catabolism. Anti-PD1 and PD-L1 therapy have demonstrated durable responses across a number of tumor types. Durvalumab is a human monoclonal antibody that binds to PD-L1 and blocks its interaction with PD-1 and CD80. The primary objective of this analysis was to prospectively assess potential correlations of longitudinal changes in ALB and NLR and durvalumab clearance (CL) rate to maximum decrease in tumor size and overall survival (OS) in patients (pts) with NSCLC and UC receiving durvalumab. Methods: Longitudinal target lesion size, serum chemistry, hematology and pharmacokinetic data were obtained from 3L+ NSCLC pts (n = 418) in study ATLANTIC and 2L+ UC pts (n = 182) in study 1108 during durvalumab treatment. Nonparametric correlations (Spearman’s rho) were evaluated between OS, maximum percent change in target lesion size, and the maximum percent change from baseline observed in ALB, NLR, and CL. Results: In NSCLC, maximum decrease in tumor size was correlated with increased ALB (r = 0.46, p < 0.0001), decreased NLR (r = 0.44, p < 0.0001), and decreased CL (r = 0.66, p < 0.0001). OS was similarly correlated with increased ALB (r = 0.47, p < 0.0001), decreased NLR (r = 0.41, p < 0.0001), and decreased CL (r = 0.76, p < 0.0001). In UC, decreased tumor size also correlated with increased ALB (r = 0.43, p < 0.0001), decreased NLR (r = 0.38, p < 0.0001), and decreased CL (r = 0.65, p < 0.0001). OS in UC also correlated with increased ALB (r = 0.50, p < 0.0001), decreased NLR (r = 0.33, p < 0.0001) and decreased CL (r = 0.82, p < 0.0001). Conclusions: In NSCLC and UC pts receiving durvalumab, tumor shrinkage and longer survival are associated with increased ALB, decreased NLR and decreased clearance of durvalumab. These findings support the hypothesis that durvalumab may be associated with a decrease in protein catabolism, inflammation and cachexia among pts who benefited from therapy. Additional biomarkers of cancer, inflammation and cachexia will be evaluated for relationships to clinical outcomes.

3038 Background: Immunotherapies have improved survival in NSCLC but not all pts benefit. Besides baseline PDL1 expression, routinely measured clinical factors may predict clinical outcomes in immunotherapy trials. LM are associated with poor prognosis in melanoma and bladder cancer pts treated with anti-PD1/L1, respectively. We examined correlation between pretreatment LM and survival in D-treated NSCLC pts. Methods: CP1108/NCT01693562 and ATLANTIC/NCT02087423 were nonrandomized phase 1/2 and 2 trials, respectively, of D 10 mg/kg Q2W in advanced NSCLC. As of Oct 24/Jun 3 2016, 304/265 primarily pretreated pts were enrolled in CP1108/ATLANTIC Cohort 2. Cox proportional hazards analysis was conducted, first among LM+/− pts, then LM+/− and PDL1 high/low pts. Both models accounted for tumor stage, ECOG/WHO PS, histology, sex, age, smoking and PDL1 status. PDL1 high was defined as ≥25% tumor cells immunostained for PDL1 at any intensity. Results: LM absence was a positive independent predictor of OS and PFS in both trials. LM− and PDL1 high or low pts had improved OS and PFS vs PDL1 low/LM+; PDL1 high/LM+ pts had improved PFS vs PDL1 low/LM+. An independent tumor kinetic model indicated LM as a predictive covariate of rapid tumor growth in D-treated pts. Conclusions: LM are associated with shorter survival in D-treated NSCLC pts in 2 trials irrespective of PDL1 status. Clinical trial information: NCT02087423 and NCT01693562. [Table: see text]

2568 Background: Durvalumab is a human monoclonal antibody that binds to PD-L1 and blocks its interaction with PD-1 and CD-80. The objective of this analysis was to evaluate the relationship between durvalumab PK exposure with efficacy and safety following 10 mg/kg Q2W durvalumab. Methods: Data from Study 1108 (Phase 1/2; all tumor types) and ATLANTIC (Phase 2; NSCLC) were used for exposure-safety analysis for Study 1108 UC cohort, Study 1108 all patients and ATLANTIC patients, respectively, whereas the exposure-efficacy analysis was performed using data from Study 1108 UC cohort. The observed PK exposure metrics included PK concentrations after the first, second or steady state doses. Efficacy endpoints used were objective response rate (ORR) and best percentage change in target lesion from baseline per BICR assessment. Safety endpoints included Grade 3+ AE (any AE, drug-related AE, AESI, and drug-related AESI) and AE leading to treatment discontinuation. Results: Overall, no association of PK exposure with efficacy or safety was observed. Distribution of PK metrics were similar between responders and non-responders. The probability of objective response was similar in all quartiles of exposure (p-value ranged from 0.37 to 0.67; n = 96) with no obvious trends between PK exposures and change in tumor size. For Grade 3+ AE (all types) and AE leading to treatment discontinuation, higher PK exposure was not associated with an increased risk of AE (p-value ranged from < 0.00005 to 0.88; n = 158, 929 and 434 for 1108 UC cohort, 1108 all patients and ATLANTIC all patients, respectively). A few inverse trends were observed, likely due to confounding effect of ECOG or albumin since covariate analysis demonstrated that both variables correlated with PK and AEs. In addition, the association of ECOG and albumin versus PK exposure were also observed in the population PK modeling. Conclusions: The exposure-efficacy and exposure-safety analyses suggested that 10 mg/kg IV Q2W regimen was an appropriate dose for durvalumab as single agent in UC patients. Overall, no relationship of PK exposure with either the efficacy or safety was observed following 10 mg/kg IV Q2W regimen. Clinical trial information: NCT02087423 and NCT01693562.

TPS2077 Background: Programmed cell death ligand-1 (PD-L1) is widely expressed on antigen presenting cells (APC) and other immune cells. PD-L1 binds two important regulatory receptors on T-cells: p...

3014 Background: The inhibitory PD-L1 and CTLA-4 pathways control T-cell activation. MEDI4736 (M) is a human IgG1 mAb that blocks PD-L1 binding to programmed cell death-1 and CD80 with high affinit...

3042 Background: Tremelimumab (T) is a selective human IgG2 mAb inhibitor of CTLA-4 that promotes T-cell activity though CTLA-4 inhibition. The primary objective of this analysis was to project the...

e14010 Background: MEDI4736 is a human IgG1 mAb that blocks PD-L1 binding to PD-1 and CD-80 with high affinity and selectivity. Tremelimumab is a selective human IgG2 mAb inhibitor of CTLA-4 that p...

e19137^ Background: CTLA-4 and PD-L1 are critical, non-redundant, signals responsible for controlling T-cell activation. Clinical trials have shown the therapeutic utility of blocking each of these...

2602 Background: MEDI4736 is a human immunoglobulin G1 kappa (IgG1κ) monoclonal antibody directed against human programmed death ligand 1 (PD-L1). MEDI4736 blocks inhibitory interaction of PD-L1 wi...