Search

Tremelimumab, an anti‐cytotoxic T‐lymphocyte antigen‐4 monoclonal antibody that enhances T‐cell activation, was evaluated in a randomized, double‐blind, placebo‐controlled, phase IIb study (NCT01843374) in patients with unresectable malignant mesothelioma. The study demonstrated no clinically meaningful differences in overall survival (OS). The objective of this analysis was to evaluate the relationship of exposure with OS. A population pharmacokinetic (PK) model adequately described the PK data. Three factors (sex, C‐reactive protein, and baseline tumor size) were identified as statistically significant PK predictors (P

Linear models are generally reliable methods for analyzing tumor growth in vivo, with drug effectiveness being represented by the steepness of the regression slope. With immunotherapy, however, not all tumor growth follows a linear pattern, even after log transformation. Tumor kinetics models are mechanistic models that describe tumor proliferation and tumor killing macroscopically, through a set of differential equations. In drug combination studies, although an additional drug-drug interaction term can be added to such models, however, the drug interactions suggested by tumor kinetics models cannot be translated directly into synergistic effects. We have developed a novel statistical approach that simultaneously models tumor growth in control, monotherapy, and combination therapy groups. This approach makes it possible to test for synergistic effects directly and to compare such effects among different studies.

Durvalumab is an anti-PD-L1 monoclonal antibody approved for patients with locally advanced or metastatic urothelial carcinoma (UC) that has progressed after platinum-containing chemotherapy. A population tumor kinetic model, coupled with dropout and survival models, was developed to describe longitudinal tumor size data and predict overall survival in UC patients treated with durvalumab (NCT01693562) and to identify prognostic and predictive biomarkers of clinical outcomes. Model-based covariate analysis identified liver metastasis as the most influential factor for tumor growth and immune-cell PD-L1 expression and baseline tumor burden as predictive factors for tumor killing. Tumor or immune-cell PD-L1 expression, liver metastasis, baseline hemoglobin, and albumin levels were identified as significant covariates for overall survival. These model simulations provided further insights into the impact of PD-L1 cutoff values on treatment outcomes. The modeling framework can be a useful tool to guide patient selection and enrichment strategies for immunotherapies across various cancer indications.

Immunotherapy and immune checkpoint blocking antibodies such as anti-PD-1 are approved and significantly improve the survival of advanced non-small cell lung cancer (NSCLC) patients, but there has been little success in identifying biomarkers capable of separating the responders from non-responders before the onset of the therapy. In this study, we developed a quantitative system pharmacology (QSP) model to represent the anti-tumor immune response in human NSCLC that integrated our knowledge of tumor growth, antigen processing and presentation, T cell activation and distribution, antibody pharmacokinetics, and immune checkpoint dynamics. The model was calibrated with the available data and was used to identify potential biomarkers as well as patient-specific response based on the patient parameters. The model predicted that in addition to tumor mutational burden (TMB), a known biomarker for anti-PD-1 therapy in NSCLC, the number of effector T cells and regulatory T cells in the tumor and blood is a predictor of the responders. Furthermore, the model simulated a set of 12 patients with known TMB and MHC/antigen-binding affinity from a recent clinical trial (ClinicalTrials.gov number, NCT02259621) on neoadjuvant nivolumab therapy in resectable lung cancer and predicted an augmented durable response in patients with adjuvant nivolumab treatment in addition to the clinical trial protocol of neoadjuvant nivolumab treatment followed by resection. Overall, the model provides a valuable framework to model tumor immunity and response to immune checkpoint blockers to enhance biomarker discovery and performing virtual clinical trials to aid in design and interpretation of the current trials with fewer patients. Electronic supplementary material The online version of this article (10.1208/s12248-019-0350-x) contains supplementary material, which is available to authorized users.

The low response rate of immune checkpoint blockade in breast cancer has highlighted the need for predictive biomarkers to identify responders. While a number of clinical trials are ongoing, testing all possible combinations is not feasible. In this study, a quantitative systems pharmacology model is built to integrate immune–cancer cell interactions in patients with breast cancer, including central, peripheral, tumour-draining lymph node (TDLN) and tumour compartments. The model can describe the immune suppression and evasion in both TDLN and the tumour microenvironment due to checkpoint expression, and mimic the tumour response to checkpoint blockade therapy. We investigate the relationship between the tumour response to checkpoint blockade therapy and composite tumour burden, PD-L1 expression and antigen intensity, including their individual and combined effects on the immune system, using model-based simulations. The proposed model demonstrates the potential to make predictions of tumour response of individual patients given sufficient clinical measurements, and provides a platform that can be further adapted to other types of immunotherapy and their combination with molecular-targeted therapies. The patient predictions demonstrate how this systems pharmacology model can be used to individualize immunotherapy treatments. When appropriately validated, these approaches may contribute to optimization of breast cancer treatment.

Over the past decade, several immunotherapies have been approved for the treatment of melanoma. The most prominent of these are the immune checkpoint inhibitors, which are antibodies that block the inhibitory effects on the immune system by checkpoint receptors, such as CTLA-4, PD-1 and PD-L1. Preclinically, blocking these receptors has led to increased activation and proliferation of effector cells following stimulation and antigen recognition, and subsequently, more effective elimination of cancer cells. Translation from preclinical to clinical outcomes in solid tumors has shown the existence of a wide diversity of individual patient responses, linked to several patient-specific parameters. We developed a quantitative systems pharmacology (QSP) model that looks at the mentioned checkpoint blockade therapies administered as mono-, combo- and sequential therapies, to show how different combinations of specific patient parameters defined within physiological ranges distinguish different types of virtual patient responders to these therapies for melanoma. Further validation by fitting and subsequent simulations of virtual clinical trials mimicking actual patient trials demonstrated that the model can capture a wide variety of tumor dynamics that are observed in the clinic and can predict median clinical responses. Our aim here is to present a QSP model for combination immunotherapy specific to melanoma.

The role of phospholipid modification initiated by phospholipase D (PLD) in enzymatic browning has been revoked through this study. Various alcohols and aldehydes were tried to read out their PLD controlling behaviour. Based on in-vitro results, reagents like hexanal and inositol were used to regulate PLD activity of litchi fruit stored at ambient temperature and their effects on fruit quality and physiological characteristics were also investigated. The results showed that combinatorial chemical treatment was successful in maintaining freshness of fruit through delayed physiological loss in weight and hence maintaining firmness. Combinatorial treated fruit had lower browning index than control by day 7. This novel treatment also maintained comparable levels of total phenolics and lowered the level of malondialdehyde. Evaluation of antioxidative enzymatic profile also confirmed the alleviation of oxidative stress of litchi fruit at ambient temperature. Thus, this strategy of enzyme regulation could play a vital role in overall quality maintenance of litchi fruit.

Background TNF-related apoptosis-inducing ligand (TRAIL) receptor agonists are attractive anti-tumor agents because of their capability to induce apoptosis in cancer cells by activating death receptors (DR) 4 and 5 with little toxicity against normal cells. Despite an attractive mechanism of action, previous clinical efforts to use TRAIL receptor agonists have been unsuccessful. In this study, we examined MEDI3039, a highly potent multivalent DR5 agonist, in breast cancer cell lines and in vivo models. Methods As in vitro model systems, we used 19 breast cancer cell lines that are categorized into four subtypes: ER+, HER2 amplified, basal A (triple-negative breast cancer) TNBC, and basal B TNBC. Cell viability was analyzed by MTS and RealTime live/dead assays. As in vivo model systems, MDA-MB231T orthotopic primary tumor growth in the mammary fat pad (MFP) and two experimental lung metastasis models were used. The effect of MEDI3039 on MFP tumors was assessed with immunohistochemical analysis. Lung metastases were analyzed with Bouin’s and H&E staining. Results MEDI3039 killed multiple breast cancer cell lines, but the sensitivity varied among different subtypes. Sensitivity was basal B TNBC >> basal A TNBC > HER2 amplified > ER+ (average IC50 = 1.4, 203, 314, 403 pM, respectively). While the pattern of relative sensitivity was similar to GST-TRAIL in most cell lines, MEDI3039 was at least two orders of magnitude more potent compared with GST-TRAIL. In the MFP model, weekly treatment with 0.1 or 0.3 mg/kg MEDI3039 for 5 weeks inhibited tumor growth by 99.05% or 100% (median), respectively, compared with the control group, and extended animal survival (p = 0.08 or p = 0.0032 at 0.1 or 0.3 mg/kg, respectively). MEDI3039-induced caspase activation was confirmed in tumors grown in MFP (p 4 mm], p

Introduction Two clinical studies (Study 1108 and ATLANTIC) were analyzed to evaluate the prognostic value of baseline liver metastases (LMs) in advanced/metastatic non–small-cell lung cancer patients treated with durvalumab 10 mg/kg every 2 weeks. Patients and Methods A multivariate Cox proportional hazards analysis was conducted; covariates included performance status, tumor stage, histology, sex, age, smoking status, and programmed cell death ligand 1 (PD-L1) status. Results In all, 569 patients were included. LMs were present in 31.6% (96/304) of Study 1108 patients and 17.9% (47/263) of ATLANTIC patients. Median overall survival (OS) was shorter in patients with LMs than in those without in both studies. In both studies, LMs were an independent negative prognostic factor for OS and progression-free survival. Objective response rates were also significantly lower. PD-L1 independently predicted benefit across all patients. Conclusion Liver metastases were associated with worse outcomes irrespective of PD-L1 status, but PD-L1 status predicted benefit from durvalumab irrespective of LMs.

INTRODUCTION: Durvalumab is a selective, high-affinity human immunoglobulin G1 monoclonal antibody that blocks programmed cell death ligand 1 (PD-L1) binding to programmed death 1. Here we report safety and clinical activity in the NSCLC cohort of a phase I/II trial that included multiple tumor types (Study 1108; NCT01693562). METHODS: Patients with stage IIIB-IV NSCLC (squamous or nonsquamous) received durvalumab 10 mg/kg every 2 weeks for 12 months or until confirmed progressive disease or unacceptable toxicity. Primary objectives were safety and antitumor activity. Tumoral PD-L1 expression was assessed using the VENTANA SP263 Assay. Responses were assessed by blinded independent central review (Response Evaluation Criteria in Solid Tumors v1.1). Adverse events were graded according to National Cancer Institute's Common Terminology Criteria for Adverse Events (v4.03). RESULTS: Of 304 patients, 79.0% were previously treated. Confirmed objective response rate was 21.8% in patients with greater than or equal to 25% PD-L1 expression and 6.4% in those with less than 25%; 25.9% in first-line patients and 12.7% in previously treated patients; and 14.0% in squamous and 16.7% in nonsquamous disease. Median overall survival was 12.4 months and median progression-free survival was 1.7 months; both were numerically longer in the PD-L1 greater than or equal to 25% group than in the PD-L1 less than 25% group (overall survival 16.4 versus 7.6 months, respectively; progression-free survival 2.6 versus 1.4 months, respectively). Treatment-related adverse events occurred in 57.2%, were grade 3/4 in 10.2%, and led to discontinuation in 5.6%. One patient (0.3%) died of treatment-related pneumonia with underlying pneumonitis. CONCLUSIONS: Durvalumab was clinically active irrespective of histology in this mostly pretreated population, with a manageable safety profile. Response rates and survival appeared to be enhanced in patients with greater tumoral PD-L1 expression. ispartof: JOURNAL OF THORACIC ONCOLOGY vol:14 issue:10 pages:1794-1806 ispartof: location:United States status: published

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.

Milk clotting enzyme (MCE) was immobilized in alginate-pectate interwoven gel with the yield of 73%. The encapsulated enzyme retained most of the protein load while soluble enzyme lost major proportion of activity after few hours. The immobilized enzyme showed high operational stability by retaining 40% activity even after 10 uses. The narrow optimal working pH of soluble enzyme changed to a broader range after encapsulation and a shift in optimum temperature from 45 to 50°C was also recorded for encapsulated enzyme. Studies on isokinetic temperature showed that immobilized enzyme is more thermo-stable at higher temperature. Immobilization, therefore, not only improved the catalytic properties and stability but also its suitability in food processes like cheese preparation with reduced cost and time.

The present investigation was carried out to study the in vitro antioxidant potential of red rose petals. The total compounds from the petals were partitioned into six fractions using solvents of different polarity starting from non-polar (hexane) to polar (water). All the six fractions were evaluated for their antioxidant potential using various in vitro assay systems viz. metal chelating activity, total reducing power (TRP) and total antioxidant activity (TAA). Total phenolic compounds and flavonoids contents were also estimated in all the six fractions. Water extract showed maximum DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging and metal chelation activity with IC50 values of 25.66 and 793.24 μg, respectively. Acetone extract exhibited maximum 2,2′-azinobis[3-ethylbenzothiazoline-6-sulfonate] (ABTS) decolorization activity. TRP of water extract was found to be highest (AU0.5 = 165.88 μg). Water extract also exhibited maximum TAA and FRAP (ferric reducing activating power) with AU0.5 values of 116.0 and 18.5 µg, respectively. Total phenolic and flavonoids contents were found maximum in methanol and ethyl acetate fraction, respectively. On an average basis, water extract was found most potent in terms of its antioxidant potential and it was found to have rutin (182.45 μg g−1) as the most abundant phenolic compounds.

Extracellular milk clotting enzyme from Bacillus subtilis MTCC 10422, which has the capacity of forming milk curds, was purified 32.9 fold with 20.82% recovery using sequential chromatographic techniques. The molecular weight of the enzyme was found to be 27 kDa which is of monomeric nature. The optimum temperature of the enzyme was found to be 45 °C and it was quite stable in the temperature range of 35–65 °C. The enzyme showed the p H optima of 6.0, and quite stable in broad p H range of 5.0–8.0 and showed a typical hyperbolic velocity saturation curve with K m value of 5 mg mL −1 with skim milk as a substrate. Calcium chloride at the concentration of 10 mM was found to be the most effective stimulator, accelerating the enzyme activity by about 2.8 folds. Various kinetic parameters towards thermo-inactivation of milk clotting enzyme were studied. Thermal inactivation behaviour of the purified enzyme suggested its thermostability and also its sensitivity to duration of heat treatment. After purification, both yield and recovery of purified preparation were found appreciable. Since this enzyme has wider p H stability and thermostability, usage of this high activity microbial enzyme for various cheese preparations can be evaluated at commercial scale.

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 .

There are no approved drug therapies that can prevent or slow the progression of Parkinson's disease (PD). Accumulation and aggregation of α-synuclein protein is observed throughout the nervous system in PD. α-Synuclein is a core component of Lewy bodies and neurites that neuropathologically define PD, suggesting that α-synuclein may be a key causative agent in PD. Recent experimental data suggest that PD progression may arise due to spreading of pathological forms of extracellular α-synuclein throughout the brain via a cellular release, uptake and seeding mechanism. We have developed a high affinity α-synuclein antibody, MEDI1341, that can enter the brain, sequester extracellular α-synuclein and attenuate α-synuclein spreading in vivo. MEDI1341 binds both monomeric and aggregated forms of α-synuclein. In vitro, MEDI1341 blocks cell-to-cell transmission of pathologically relevant α-synuclein preformed fibrils (pffs). After intravenous injection into rats and cynomolgus monkeys, MEDI1341 rapidly enters the central nervous system and lowers free extracellular α-synuclein levels in the interstitial fluid (ISF) and cerebrospinal fluid (CSF) compartments. Using a novel lentiviral-based in vivo mouse model of α-synuclein spreading in the brain, we show that treatment with MEDI1341 significantly reduces α-synuclein accumulation and propagation along axons. In this same model, we demonstrate that an effector-null version of the antibody was equally as effective as one with effector function. MEDI1341 is now in Phase 1 human clinical trial testing as a novel treatment for α-synucleinopathies including PD with the aim to slow or halt disease progression.

Utilizing decision making biomarkers in drug development requires thorough assay validation. Special considerations need to be taken into account when monitoring biomarkers using immunoassays in the presence of therapeutic antibodies. We have developed robust and sensitive assays to assess target engagement and proof of mechanism to support the clinical progression of a human monoclonal antibody against the neurotoxic amyloid-β (Aβ)42 peptide. Here we present the introduction of novel pre-treatment steps to ensure drug-tolerant immunoassays and describe the validation of the complete experimental procedures to measure total Aβ42 concentration (bound and unbound) in cerebrospinal fluid (CSF) and plasma, free Aβ42 concentration (unbound) in CSF, and Aβ40 concentration in CSF. The difference in composition of the matrices (CSF and plasma) and antigen levels therein, in combination with the hydrophobic properties of Aβ protein, adds to the complexity of validation. Monitoring pharmacodynamics of an Aβ42 specific monoclonal antibody in a non-human primate toxicology study using these assays, we demonstrated a 1500-fold and a 3000-fold increase in total Aβ42 in plasma, a 4-fold and 8-fold increase in total Aβ42 in CSF together with a 95% and 96% reduction of free Aβ42 in CSF following weekly intravenous injections of 10 mg/kg and 100 mg/kg, respectively. Levels of Aβ40 were unchanged. The accuracy of these data is supported by previous pre-clinical studies as well as predictive pharmacokinetic/pharmacodynamics modeling. In contrast, when analyzing the same non-human primate samples excluding the pre-treatment steps, we were not able to distinguish between free and total Aβ42. Our data clearly demonstrate the importance of thorough evaluation of antibody interference and appropriate validation to monitor different types of biomarkers in the presence of a therapeutic antibody.

The objectives of this analysis were to develop a population pharmacokinetics (PK) model of durvalumab, an anti-PD-L1 antibody, and quantify the impact of baseline and time-varying patient/disease characteristics on PK. Pooled data from two studies (1,409 patients providing 7,407 PK samples) were analyzed with nonlinear mixed effects modeling. Durvalumab PK was best described by a two-compartment model with both linear and nonlinear clearances. Three candidate models were evaluated: a time-invariant clearance (CL) model, an empirical time-varying CL model, and a semimechanistic time-varying CL model incorporating longitudinal covariates related to disease status (tumor shrinkage and albumin). The data supported a slight decrease in durvalumab clearance with time and suggested that it may be associated with a decrease in nonspecific protein catabolic rate among cancer patients who benefit from therapy. No covariates were clinically relevant, indicating no need for dose adjustment. Simulations indicated similar overall PK exposures following weight-based and flat-dosing regimens.

When the immune system responds to tumour development, patterns of immune infiltrates emerge, highlighted by the expression of immune checkpoint-related molecules such as PDL1 on the surface of cancer cells. Such spatial heterogeneity carries information on intrinsic characteristics of the tumour lesion for individual patients, and thus is a potential source for biomarkers for anti-tumour therapeutics. We developed a systems biology multiscale agent-based model to capture the interactions between immune cells and cancer cells, and analysed the emergent global behaviour during tumour development and immunotherapy. Using this model, we are able to reproduce temporal dynamics of cytotoxic T cells and cancer cells during tumour progression, as well as three-dimensional spatial distributions of these cells. By varying the characteristics of the neoantigen profile of individual patients, such as mutational burden and antigen strength, a spectrum of pretreatment spatial patterns of PDL1 expression is generated in our simulations, resembling immuno-architectures obtained via immunohistochemistry from patient biopsies. By correlating these spatial characteristics with in silico treatment results using immune checkpoint inhibitors, the model provides a framework for use to predict treatment/biomarker combinations in different cancer types based on cancer-specific experimental data.

Background: Durvalumab [D] is a human mAb that binds to PD-L1 and blocks its interaction with PD-1 and CD80. Tremelimumab [T] blocks the inhibitory effects of CTLA-4, and therefore enhances T-cell activation. The objectives of this analysis were to develop a model linking overall survival (OS) to baseline risk factors and changes in tumor size during treatment to identify key factors impacting response to D or D +T. Methods: The analysis dataset included UC patients from two clinical trials: Study 1108 (D 10 mg/kg Q2W; n=201) and Study 10 (D 20 mg/kg Q4W + T 1 mg/kg Q4W for 4 doses, followed by D 20 mg/kg Q4W alone; n=168). Longitudinal tumor size data were analyzed using a nonlinear mixed effect model with key parameters describing tumor growth, tumor killing, and delay in immune response. Subsequently, a parametric survival model was developed to link baseline risk factors and predicted percent change in tumor size at week 8 to OS. Results: Tumor kinetic model adequately described the longitudinal tumor size data from UC patients. Baseline tumor size (p Conclusions: The parametric survival model coupled with tumor kinetic model adequately described clinical outcomes in UC patients treated with D or D+T and enabled identification of key factors potentially impacting response to immune therapy in UC. This approach can be a useful tool for guiding patient selection/enrichment strategies and optimizing trial designs for immuno-oncology (IO) therapies. Further validation and prospective evaluation of this model may be conducted in other IO trials. Citation Format: Mei Tang, Yu Jiang, Han Si, Yanan Zheng, Chen Gao, Guozhi Gao, Natasha Angra, Shaad Abdullah, Brandon Higgs, Lorin Roskos, Rajesh Narwal. Prediction of overall survival in urothelial cancer patients using tumor sizes and baseline risk factors: longitudinal modeling approach for durvalumab and durvalumab + tremelimumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3158.

Background: In 2010, there were an estimated 15 million preterm births worldwide (90%) survive without neurodevelopmental impairment. Developing effective means of prevention of preterm birth should be a longer term priority, but major burden reduction could be made immediately with improved coverage and quality of care. Improved newborn care would reduce mortality, especially in low-income countries and is likely to reduce impairment in survivors, particularly in middle-income settings.

Lowering levels of peripheral amyloid-β has been proposed as a strategy to reduce plaques in patients with Alzheimer’s disease. Henderson et al. test a modified version of the amyloid-degrading enzyme neprilysin in rats, monkeys and Tg2576 mice. Levels of amyloid-β were reduced in the bloodstream, but not in the CNS., Alzheimer’s disease is characterized by the accumulation of amyloid deposits in the brain and the progressive loss of cognitive functions. Although the precise role of amyloid-β in disease progression remains somewhat controversial, many efforts to halt or reverse disease progression have focussed on reducing its synthesis or enhancing its removal. It is believed that brain and peripheral soluble amyloid-β are in equilibrium and it has previously been hypothesized that a reduction in peripheral amyloid-β can lower brain amyloid-β, thereby reducing formation of plaques predominantly composed of insoluble amyloid-β; the so-called peripheral sink hypothesis. Here we describe the use of an amyloid-β degrading enzyme, the endogenous metallopeptidase neprilysin, which is fused to albumin to extend plasma half-life and has been engineered to confer increased amyloid-β degradation activity. We used this molecule to investigate the effect of degradation of peripheral amyloid-β on amyloid-β levels in the brain and cerebrospinal fluid after repeated intravenous dosing for up to 4 months in Tg2576 transgenic mice, and 1 month in rats and monkeys. This molecule proved highly effective at degradation of amyloid-β in the periphery but did not alter brain or cerebrospinal fluid amyloid-β levels, suggesting that the peripheral sink hypothesis is not valid and is the first time that this has been demonstrated in non-human primates.

Sifalimumab is a fully human immunoglobulin G1κ monoclonal antibody that binds to and neutralizes a majority of the subtypes of human interferon-α. Sifalimumab is being evaluated as a treatment for systemic lupus erythematosus (SLE). The primary objectives of this analysis were (a) to develop a population pharmacokinetic model for sifalimumab in SLE; (b) to identify and quantitate the impact of patient/disease characteristics on pharmacokinetic variability; and (c) to evaluate fixed versus body weight (WT)-based dosing regimens. Sifalimumab serum concentration-time data were collected from a phase Ib study (MI-CP152) designed to evaluate the safety and tolerability of sifalimumab in adult patients with SLE. Sifalimumab was administered every 14 days as a 30- to 60-minute intravenous infusion with escalating doses of 0.3, 1.0, 3.0, and 10 mg/kg and serum concentrations were collected over 350 days. A total of 120 patients provided evaluable pharmacokinetic data with a total of 2,370 serum concentrations. Sifalimumab serum concentrations were determined using a validated colorimetric enzyme-linked immunosorbent assay (ELISA) with a lower limit of quantitation of 1.25 μg/mL. Population pharmacokinetic modeling of sifalimumab was performed using a non-linear mixed effects modeling approach with NONMEM VII software. Impact of patient demographics, clinical indices, and biomarkers on pharmacokinetic parameters were explored using a stepwise forward selection and backward elimination approach. The appropriateness of the final model was tested using visual predictive check (VPC). The impact of body WT-based and fixed dosing of sifalimumab was evaluated using a simulation approach. The final population model was utilized for phase IIb dosing projections. Sifalimumab pharmacokinetics were best described using a two-compartment linear model with first order elimination. Following intravenous dosing, the typical clearance (CL) and central volume of distribution (V 1) were estimated to be 176 mL/day and 2.9 L, respectively. The estimates (coefficient of variation) of between-subject variability for CL and V 1 were 28 and 31 %, respectively. Patient baseline body WT, interferon gene signature from 21 genes, steroid use, and sifalimumab dose were identified as significant covariates for CL, whereas only baseline body WT was a significant covariate for V 1 and peripheral volume of distribution (V 2). Although the above-mentioned covariates were statistically significant, they did not explain variability in pharmacokinetic parameters to any relevant extent (

Objectives: National Rural Health Mission (NRHM) – India was launched in 2005 to tackle urban-rural health inequalities, especially in maternal and child health. We examined national and state level trends in Infant Mortality Rates (IMR) from 2000 through 2009 to: 1) assess whether the NRHM had increased the average annual reduction rate (AARR) of IMR 2) evaluate state-wise progress towards Millennium Development Goals (MDG4) and estimate required AARRs for ‘off track’ states. Methods: Log-linear regression models were applied to national and state IMR data collated from the Sample Registration System (SRS)-India to estimate average annual reduction rates and compare AAARs before and after introduction of NRHM. The log-linear trend of infant mortality rates was also projected forward to 2015. Results: The infant mortality rate in rural India declined from 74 to 55/1000 live births between 2000 and 2009, with AARR of 3.0% (95% CI=2.6%-3.4%) and the urban-rural gap in infant mortality narrowed (p =0.036). However there was no evidence (p=0.49) that AARR in rural India increased post NRHM (3.4%, 95% CI 2.0-4.7%) compared to pre NRHM (2.8%, 95% CI 2.1%-3.5%). States varied widely in rates of infant mortality reduction. Projections of infant mortality rates suggested that only eight states might be on track to help India achieve MDG4 by 2015. Conclusions and Public Health Implications: Despite a narrowing urban-rural gap and high AARRs in some states, there was no evidence that the rate of reduction in infant mortality has increased in rural India post NRHM introduction. India appears unlikely to achieve child survival-related NRHM and millennium development goals. Government should revisit the child survival related NRHM strategies and ensure equitable access to health services. More robust monitoring and evaluation mechanisms must be inbuilt for following years. Key Words: India • National Rural Health Mission • Infant Mortality Rate • Millennium Development Goals • Health Systems Copyright © 2013 Narwal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

MEDI-575, an immunoglobulin G2κ monoclonal antibody, selectively binds to platelet-derived growth factor-α receptor (PDGFR-α) with high specificity. This multicenter, single-arm, open-label, phase II study evaluated the efficacy and safety of MEDI-575 in patients with recurrent glioblastoma. Adults with first recurrence of glioblastoma following surgery, temozolomide, and radiation received MEDI-575 25 mg/kg intravenously over 60 min every 21 days until disease progression or unacceptable toxicity. Six-month progression-free survival rate (PFS-6) was the primary end point; secondary measures included response rate, overall survival (OS), and safety/tolerability. PDGFR-α expression was evaluated by immunohistochemistry. Fifty-six patients were enrolled; median age was 56.5 years (range 23–79), 66 % were male, and 66 % were aged ≥65 years. PFS-6 was 15.4 % [90 % confidence interval (CI) 8.1–24.9]. No complete or partial responses were observed; 23 (41.1 %) patients had stable disease as best response. Median PFS was 1.4 months (90 % CI 1.4, 1.8); median OS was 9.7 months (90 % CI 6.5, 11.8). The most common treatment-related adverse events (AEs) were diarrhea (16 %), nausea (13 %), and fatigue (13 %). Twelve (21 %) patients reported grade ≥3 AEs, with hydrocephalus (n = 3), dysphagia (n = 2), and convulsion (n = 2) reported in more than 1 patient. Two patients had treatment-related Grade ≥3 AEs of decreased lymphocyte count and asthenia (n = 1 each). Seven patients (13 %) discontinued MEDI-575 owing to AEs. Labeling of PDGFRα in glioblastoma cells and tumor-associated stromal cells was highly variable, with no correlation with PFS. MEDI-575, although well tolerated, had limited clinical activity in recurrent glioblastoma.

Background: The anti-PD-L1 antibody durvalumab (D) has shown manageable safety and encouraging clinical activity in patients with advanced NSCLC. Combination of D with anti-CTLA-4 antibody tremelimumab (T) may amplify T-cell responses against tumors through non-redundant immune checkpoint blockade and provide synergistic antitumor activity. We previously reported that D+T showed antitumor activity and manageable tolerability in the dose-escalation part of a phase 1b study (NCT02000947) of patients with advanced NSCLC. Here we present safety, clinical activity, and long-term follow-up for one of 3 expansion cohorts. Methods: Immunotherapy-naive patients with non-squamous NSCLC who progressed after 1 prior platinum-based therapy, ECOG PS 0-1, received D IV 20 mg/kg every 4 weeks (Q4W) for up to 12 months and T IV 1 mg/kg Q4W with the first 4 cycles of D. Tumor PD-L1 expression (fresh biopsy or archival sample within 3 mo) was assessed with the Ventana PD-L1 (SP263) assay, PD-L1 cutoff: ≥25% of tumor cells with membrane staining. Results: As of 20 Oct 2017, 213 patients (71% ECOG PS 1) received therapy and were followed for a median of 13.3 (0.5-21.0) mo. Treatment-related adverse events (AEs) were reported in 76% of patients; the most common were fatigue (19%), pruritus (17%), diarrhea (15%), decreased appetite (14%), and rash (14%). 14 patients (7%) had a treatment-related AE leading to discontinuation, with colitis (1%), diarrhea (1%), and pneumonitis (1%) reported in more than 1 patient. Grade 3/4 treatment-related AEs occurred in 23% of patients; the most common were increased lipase (5%), colitis (3%), and increased amylase (3%). There was 1 treatment-related death (multifactorial hypoxia). The 12-month OS rate was 53.8% (95% CI, 46.4-60.6). The Table shows antitumor activity and survival by PD-L1 status. Conclusions: Second-line D+T had a manageable safety profile in patients with non-squamous NSCLC. Clinical activity was seen in both PD-L1 ≥25% and Response and survivalPD-L1 ≥25% n=57PD-L1 Citation Format: Jamie Chaft, Byoung Chul Cho, Myung-Ju Ahn, Sylvestre Le Moulec, Eun Kyung Cho, Vassiliki Papadimitrakopoulou, Edward Garon, Sylvia Lee, Santiago Ponce Aix, Patrick C. Ma, Gregory Otterson, Rajesh Narwal, Guozhi Gao, Jennifer McDevitt, Judson Englert, Scott Antonia. Safety and activity of second-line durvalumab + tremelimumab in non-squamous advanced NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr CT113.

Summary Background PD-L1 and CTLA-4 immune checkpoints inhibit antitumour T-cell activity. Combination treatment with the anti-PD-L1 antibody durvalumab and the anti-CTLA-4 antibody tremelimumab might provide greater antitumour activity than either drug alone. We aimed to assess durvalumab plus tremelimumab in patients with advanced squamous or non-squamous non-small cell lung cancer (NSCLC). Methods We did a multicentre, non-randomised, open-label, phase 1b study at five cancer centres in the USA. We enrolled immunotherapy-naive patients aged 18 years or older with confirmed locally advanced or metastatic NSCLC. We gave patients durvalumab in doses of 3 mg/kg, 10 mg/kg, 15 mg/kg, or 20 mg/kg every 4 weeks, or 10 mg/kg every 2 weeks, and tremelimumab in doses of 1 mg/kg, 3 mg/kg, or 10 mg/kg every 4 weeks for six doses then every 12 weeks for three doses. The primary endpoint of the dose-escalation phase was safety. Safety analyses were based on the as-treated population. The dose-expansion phase of the study is ongoing. This study is registered with ClinicalTrials.gov, number NCT02000947. Findings Between Oct 28, 2013, and April 1, 2015, 102 patients were enrolled into the dose-escalation phase and received treatment. At the time of this analysis (June 1, 2015), median follow-up was 18·8 weeks (IQR 11–33). The maximum tolerated dose was exceeded in the cohort receiving durvalumab 20 mg/kg every 4 weeks plus tremelimumab 3 mg/kg, with two (30%) of six patients having a dose-limiting toxicity (one grade 3 increased aspartate aminotransferase and alanine aminotransferase and one grade 4 increased lipase). The most frequent treatment-related grade 3 and 4 adverse events were diarrhoea (11 [11%]), colitis (nine [9%]), and increased lipase (eight [8%]). Discontinuations attributable to treatment-related adverse events occurred in 29 (28%) of 102 patients. Treatment-related serious adverse events occurred in 37 (36%) of 102 patients. 22 patients died during the study, and three deaths were related to treatment. The treatment-related deaths were due to complications arising from myasthenia gravis (durvalumab 10 mg/kg every 4 weeks plus tremelimumab 1 mg/kg), pericardial effusion (durvalumab 20 mg/kg every 4 weeks plus tremelimumab 1 mg/kg), and neuromuscular disorder (durvalumab 20 mg/kg every 4 weeks plus tremelimumab 3 mg/kg). Evidence of clinical activity was noted both in patients with PD-L1-positive tumours and in those with PD-L1-negative tumours. Investigator-reported confirmed objective responses were achieved by six (23%, 95% CI 9–44) of 26 patients in the combined tremelimumab 1 mg/kg cohort, comprising two (22%, 95% CI 3–60) of nine patients with PD-L1-positive tumours and four (29%, 95% CI 8–58) of 14 patients with PD-L1-negative tumours, including those with no PD-L1 staining (four [40%, 95% CI 12–74] of ten patients). Interpretation Durvalumab 20 mg/kg every 4 weeks plus tremelimumab 1 mg/kg showed a manageable tolerability profile, with antitumour activity irrespective of PD-L1 status, and was selected as the dose for phase 3 studies, which are ongoing. Funding MedImmune.

The availability of fruit like litchi has been limited by variability in yield, alternate bearing, seasonal differences and most commonly post harvest problems. The litchi fruit has a very short shelf-life during which red color turns brown which greatly affects the appeal to consumer although not the unique flavor. This review article focuses on the post harvest problems especially browning of litchi. The pericarp of litchi is also sensitive to desiccation and turns brown and brittle once moisture is reduced to half. A large number of approaches have been tried to solve this problem starting from hydro-cooling to gamma irradiation but single approach could not suffice for all. In modern era, the logical base of controlling browning is either to control the responsible enzyme or remove the undesirable product of enzyme catalyzed reaction. Thus enzyme technology with good postharvest practice can definitely solve this problem.

Cancer immunotherapy focuses on stimulating and promoting the immune system to recognize and eliminate cancer cells, with several FDA approvals in recent years. However, identifying patients best suited for specific immune therapies, and determining optimal treatment regimens continue to be a clinical challenge. Using a molecular-detailed computational systems pharmacology model to identify cellular biomarkers and optimize regimens, we may be able to predict the efficacy of regimens in specific patient populations, and expedite drug development for cancer treatment. We developed a cell/receptor-based multi-compartment systems pharmacology model focusing on the immune response against a growing tumor, with the intent to test the effects of immune checkpoint inhibitors against PD-1, PD-L1 and CTLA-4 administered as mono- and combination therapies. Additionally, the model also allows for testing of other immuno-therapies, such as adoptive cell therapies, which can be combined with the checkpoint inhibitors. The model was designed and developed using the SimBiology plug-in in MATLAB. Simulations were performed with parameters that define the immune response at particular tumor stages of melanoma and NSCLC. All results were qualitatively and quantitatively compared to experimental pre-clinical and clinical data for model validation, or used for the generation of predictions suitable for further experimental testing. In silico, we have identified that administrations of the prescribed doses of 1-10 mg/kg of anti-CLTA-4 (based on binding kinetics) effectively saturates the receptors on the T cells, and promotes both an extended life span of the antigen presenting cells (APCs), and the maximum attainable activation levels of the effector T cells. The model further predicts that the effectiveness of anti-CTLA-4 therapy is limited by the immunogenicity of the system (i.e., the antigen intensity level and number of APCs presenting the antigens) in a monotonic fashion. Furthermore, injecting activated APCs without therapy would show a temporary tumor response and a subsequent recovery by the tumor to its original growth trajectory, while raising the antigen intensity had a sustained effect on tumor response. Other simulations indicate that, despite the lack of apparent tumor response, a sustained immune attack may be ongoing in the body; however, the immune activity is proportionally limited by the tumor and regulatory cells. Lastly, several dose-responses and clinical trials were simulated for both combination and monotherapies, and correlated with published clinical trial data. Future work will focus on uncovering the cellular biomarkers responsible for such results, experimentally validating them, as well as simulating optimal combination treatment regimens for future evaluation. Citation Format: Oleg Milberg, Chang Gong, Bing Wang, Paolo Vicini, Rajesh Narwal, Lorin Roskos, Aleksander Popel. Systems pharmacology to predict cellular biomarkers and optimize mono- and combination-therapy regimens: Focusing on immune checkpoint targets PD-1, PD-L1 and CTLA-4 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4531. doi:10.1158/1538-7445.AM2017-4531

When the immune system responds to tumor development, patterns of immune infiltrates emerge, highlighted by expression of immune checkpoint-related molecules such as PD-L1 on cancer cells and its receptor PD-1 on cytotoxic T cells. Pre-treatment tumor spatial heterogeneity could bear information on intrinsic characteristics of the tumor lesion for individual patient, and thus has the potential to comprise biomarkers for anti-tumor therapeutics. We developed a systems biology computational multiscale agent-based model to capture the interactions between immune cells and cancer cells during tumor progression. Cytotoxic T cells and cancer cells are modeled as free-moving agents in a 3-dimensional grid, where each cell acts in response to its local microenvironment and carries out functions such as division, apoptosis, cytotoxic killing and switching between states with different PD-1 or PD-L1 expression levels. Subsequently, we analyzed the emergent behavior of tumor progression by looking at all these local interactions as a whole. Using this model, we are able to reproduce temporal dynamics of cytotoxic T cells and cancer cells during general tumor progression, as well as 3-dimensional spatial distributions of these cells over the time course of the simulation. By varying the characteristics of the neoantigen profile of individual patients, such as mutational burden and immunogenicity, a spectrum of pre-treatment spatial patterns of PD-1/PD-L1 expression is generated in our simulations, resembling immune-architectures obtained via immunohistochemistry from patient biopsies. We evaluate potential prognostic biomarkers by correlating these spatial characteristics with in silico treatment results with immune checkpoint inhibitors. Simulation results demonstrate that the percentage of PD-L1 positive cancer cells which are not in close proximity of the tumor boundary or vasculature is more indicative of successful anti-PD1/anti-PD-L1 treatment. Our findings suggest that tumor spatial heterogeneity, especially its immune-architecture, reflects the course of tumor progression as well as patient-specific properties, and is thus likely to carry important information about tumor susceptibility to treatment such as with immune checkpoint inhibitors. We demonstrated how prognostic biomarkers could be realistically simulated in a general cancer scenario. The model is further refined for use to predict treatment/biomarker combinations in specific cancer types. Citation Format: Chang Gong, Oleg Milberg, Bing Wang, Paolo Vicini, Rajesh Narwal, Lorin Roskos, Aleksander S. Popel. A multiscale computational model for spatio-temporal tumor immune response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 975. doi:10.1158/1538-7445.AM2017-975

Background: MEDI0680 (AMP-514) is a humanized immunoglobulin gamma 4, kappa (IgG4κ) monoclonal antibody (mAb) specific for human programmed cell death-1 (PD-1), developed for the treatment of cancer. The primary objectives of this analysis were to (a) describe the pharmacokinetics (PK) of MEDI0680 and quantitate the impact of patient/disease characteristics on PK variability (b) to compare body weight (WT)-based and fixed dosing regimens of MEDI0680 and (c) to characterize PK-pharmacodynamic (receptor occupancy) relationship. Methods: A total of 905 serum concentration records from 58 patients in Phase 1 study (D6020C00002) designed to evaluate safety, tolerability and PK following 0.1, 0.5, 2.5, 10, and 20 mg/kg every 3 weeks (Q3W), every 2 weeks (Q2W) or weekly doses (QW) as intravenous (IV) infusion of MEDI0680 were included in this analysis. The population PK analysis was performed using a non-linear mixed effects modeling approach in NONMEM (version 7.2) software. Impact of patient demographics, clinical indices and biomarkers on PK parameters were explored. The appropriateness of the final model was tested using visual predictive check (VPC). A sequential PK-PD analysis was performed using receptor occupancy (RO) data from 35 subjects. Results: MEDI0680 PK profiles were best described using a 2-compartment model with linear clearance. The clearance (CL), volume of distribution (Vc) were 0.27 L/day, 5.07 L with a modest between-subject variability of 30% and 19%, respectively. None of the evaluated covariates showed any impact on PK parameters except a minor (not clinically relevant) impact of body weight on volume of distribution. VPC results demonstrated good predictability of the final population PK model. A direct Emax model described the PK-PD relationship of MEDI0680. The estimate of EC50 was approximately 9.3 µg/mL. PK/PD simulations indicate that following 20 mg/kg Q2W dose, >90% receptor occupancy can be maintained in all subjects. Based on preclinical/clinical PK, PD, and safety data, a dose of 20 mg/kg Q2W was selected for phase 2 studies. Conclusions: A population PK model of MEDI0680 was developed and validated. Modeling results indicate no need for dose adjustment based on patient/disease characteristics. Similar PK is expected following both WT-based and fixed dosing regimens. PK/PD findings support the dose of 20 mg/kg Q2W. Clinical studies are ongoing in various tumor types. Citation Format: Xuyang Song, Xizhe Gao, Bo Zheng, Chelsea Black, Matthew Gribbin, Joyson Karakunnel, Lorin Roskos, Rajesh Narwal. Pharmacokinetics and pharmacodynamics of MEDI0680, a fully human anti-PD1 monoclonal antibody, in patients with advanced malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5045. doi:10.1158/1538-7445.AM2017-5045

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.

Purpose The purpose of the study was to evaluate safety and determine the maximum tolerated dose (MTD) of MEDI-575, a fully human monoclonal antibody that selectively binds to platelet-derived growth factor receptor-α (PDGFRα), in patients with advanced solid tumors. Methods This phase I multicenter, open-label, single-arm study enrolled adults in a 3 + 3 dose escalation design to receive MEDI-575 (3, 6, 9, 12, or 15 mg/kg) once weekly (QW) until toxicity or disease progression occurred. One 0.5-mg/kg dose was given before the first dose in the 3-mg/kg cohort to determine pharmacokinetics (PK) and pharmacodynamics under unsaturated conditions. After completion of dose escalation in the QW cohorts, patients were enrolled in two additional cohorts and received MEDI-575 25 or 35 mg/kg every 3 weeks (Q3W). Secondary measures included assessments of PK, immunogenicity, and antitumor activity. Results A total of 35 patients received MEDI-575 QW (n = 23) or Q3W (n = 12). Most treatment-related adverse events were grade 1 or 2 in severity across all dose levels, with fatigue (n = 12) and nausea (n = 8) being reported most frequently. With no reports of dose-limiting toxicities (DLTs), the MTD was not reached. MEDI-575 exhibited a nonlinear PK profile and increased plasma platelet-derived growth factor-AA levels in a dose-dependent manner with limited immunogenicity. Stable disease was reported as the best tumor response in 9 of 29 evaluable patients; however, no objective responses were reported. Conclusion Administration of MEDI-575 QW or Q3W resulted in a favorable safety profile, including a lack of DLTs, but without evidence of antitumor activity in patients with refractory solid tumors.