Safety and efficacy of pegunigalsidase alfa in patients with Fabry disease who were previously treated with agalsidase alfa: results from BRIDGE, a phase 3 open-label study

BACKGROUND: Pegunigalsidase alfa is a novel, PEGylated α-galactosidase-A enzyme-replacement therapy approved in the EU and US to treat patients with Fabry disease (FD). OBJECTIVE/METHODS: BRIDGE is a phase 3 open-label, switch-over study designed to assess safety and efficacy of 12 months of pegunigalsidase alfa (1 mg/kg every 2 weeks) treatment in adults with FD who had been previously treated with agalsidase alfa (0.2 mg/kg every 2 weeks) for ≥ 2 years. RESULTS: Twenty-seven patients were screened; 22 met eligibility criteria; and 20 (13 men, 7 women) completed the study. Pegunigalsidase alfa was well-tolerated, with 97% of treatment-emergent adverse events (TEAEs) being of mild or moderate severity. The incidence of treatment-related TEAEs was low, with 2 (9%) discontinuations due to TEAEs. Five patients (23%) reported infusion-related reactions. Overall mean (SD; n = 22) baseline estimated glomerular filtration rate (eGFR) was 82.5 (23.4) mL/min/1.73 m2 and plasma lyso-Gb3 level was 38.3 (41.2) nmol/L (men: 49.7 [45.8] nmol/L; women: 13.8 [6.1] nmol/L). Before switching to pegunigalsidase alfa, mean (standard error [SE]) annualized eGFR slope was − 5.90 (1.34) mL/min/1.73 m2/year; 12 months post-switch, the mean eGFR slope was − 1.19 (1.77) mL/min/1.73 m2/year; and mean plasma lyso-Gb3 reduced by 31%. Seven (35%) out of 20 patients were positive for pegunigalsidase alfa antidrug antibodies (ADAs) at ≥ 1 study timepoint, two of whom had pre-existing ADAs at baseline. Mean (SE) changes in eGFR slope for ADA-positive and ADA-negative patients were + 5.47 (3.03) and + 4.29 (3.15) mL/min/1.73 m2/year, respectively, suggesting no negative impact of anti-pegunigalsidase alfa ADAs on eGFR slope. CONCLUSION: Pegunigalsidase alfa may offer a safe and effective treatment option for patients with FD, including those previously treated with agalsidase alfa. TRN: NCT03018730. Date of registration: January 2017

Taming Volatile High Frequency Data with Long Lag Structure: An Optimal Filtering Approach for Forecasting

We propose a Bayesian optimal filtering setup for improving out-of-sample forecasting performance when using volatile high frequency data with long lag structure for forecasting low-frequency data. We test this setup by using real-time Swiss construction investment and construction permit data. We compare our approach to different filtering techniques and show that our proposed filter outperforms various commonly used filtering techniques in terms of extracting the more relevant signal of the indicator series for forecasting

In Silico Simulation of Corticosteroids Effect on an NFkB- Dependent Physicochemical Model of Systemic Inflammation

During the onset of an inflammatory response signaling pathways are activated for "translating" extracellular signals into intracellular responses converging to the activation of nuclear factor (NF)-kB, a central transcription factor in driving the inflammatory response. An inadequate control of its transcriptional activity is associated with the culmination of a hyper-inflammatory response making it a desired therapeutic target. Predicated upon the nature of the response, a systems level analysis might provide rational leads for the development of strategies that promote the resolution of the response.A physicochemical host response model is proposed to integrate biological information in the form of kinetic rules and signaling cascades with pharmacokinetic models of drug action for the modulation of the response. The unifying hypothesis is that the response is triggered by the activation of the NFkB signaling module and corticosteroids serve as a template for assessing anti-inflammatory strategies. The proposed in silico model is evaluated through its ability to predict and modulate uncontrolled responses. The pre-exposure of the system to hypercortisolemia, i.e. 6 hr before or simultaneously with the infectious challenge "reprograms" the dynamics of the host towards a balanced inflammatory response. However, if such an intervention occurs long before the inflammatory insult a symptomatic effect is observed instead of a protective relief while a steroid infusion after inducing inflammation requires much higher drug doses.We propose a reversed engineered inflammation model that seeks to describe how the system responds to a multitude of external signals. Timing of intervention and dosage regimes appears to be key determinants for the protective or symptomatic effect of exogenous corticosteroids. Such results lie in qualitative agreement with in vivo human studies exposed both to LPS and corticosteroids under various time intervals thus improving our understanding of how interacting modules generate a behavior

Pre-natal and post-natal exposure to respiratory infection and atopic diseases development: a historical cohort study

BACKGROUND: According to the hygiene hypothesis, infections in early life protect from allergic diseases. However, in earlier studies surrogate measures of infection rather than clinical infections were associated with decreased frequencies of atopic diseases. Exposure to infection indicating sub-clinical infection rather than clinical infection might protect from atopic diseases. Objective: to investigate whether exposure to acute respiratory infections within pregnancy and the first year of life is associated with atopic conditions at age 5–14 years and to explore when within pregnancy and the first year of life this exposure is most likely to be protective. METHODS: Historical cohort study: Population level data on acute respiratory infections from the routine reporting system of the former German Democratic Republic were linked with individual data from consecutive surveys on atopic diseases in the same region (n = 4672). Statistical analyses included multivariate logistic regression analysis and polynomial distributed lag models. RESULTS: High exposure to acute respiratory infection between pregnancy and age one year was associated with overall reduced odds of asthma, eczema, hay fever, atopic sensitization and total IgE. Exposure in the first 9 months of life showed the most pronounced effect. Adjusted odds ratio's for asthma, hay fever, inhalant sensitization and total IgE were statistical significantly reduced up to around half. CONCLUSION: Exposure to respiratory infection (most likely indicating sub-clinical infection) within pregnancy and the first year of life may be protective in atopic diseases development. The post-natal period thereby seems to be particularly important

A Plant-Derived Recombinant Human Glucocerebrosidase Enzyme—A Preclinical and Phase I Investigation

Gaucher disease is a progressive lysosomal storage disorder caused by the deficiency of glucocerebrosidase leading to the dysfunction in multiple organ systems. Intravenous enzyme replacement is the accepted standard of treatment. In the current report, we evaluate the safety and pharmacokinetics of a novel human recombinant glucocerebrosidase enzyme expressed in transformed plant cells (prGCD), administered to primates and human subjects. Short term (28 days) and long term (9 months) repeated injections with a standard dose of 60 Units/kg and a high dose of 300 Units/kg were administered to monkeys (n = 4/sex/dose). Neither clinical drug-related adverse effects nor neutralizing antibodies were detected in the animals. In a phase I clinical trial, six healthy volunteers were treated by intravenous infusions with escalating single doses of prGCD. Doses of up to 60 Units/kg were administered at weekly intervals. prGCD infusions were very well tolerated. Anti-prGCD antibodies were not detected. The pharmacokinetic profile of the prGCD revealed a prolonged half-life compared to imiglucerase, the commercial enzyme that is manufactured in a costly mammalian cell system. These studies demonstrate the safety and lack of immunogenicity of prGCD. Following these encouraging results, a pivotal phase III clinical trial for prGCD was FDA approved and is currently ongoing.ClinicalTrials.gov NCT00258778

Modeling Corticosteroid Effects in a Rat Model of Rheumatoid Arthritis I: Mechanistic Disease Progression Model for the Time Course of Collagen-Induced Arthritis in Lewis Rats

ABSTRACT A mechanism-based model was developed to describe the time course of arthritis progression in the rat. Arthritis was induced in male Lewis rats with type II porcine collagen into the base of the tail. Disease progression was monitored by paw swelling, bone mineral density (BMD), body weights, plasma corticosterone (CST) concentrations, and tumor necrosis factor (TNF)-␣, interleukin (IL)-1␤, IL-6, and glucocorticoid receptor (GR) mRNA expression in paw tissue. Bone mineral density was determined by PIXImus II dual energy X-ray densitometry. Plasma CST was assayed by high-performance liquid chromatography. Cytokine and GR mRNA were determined by quantitative real-time polymerase chain reaction. Disease progression models were constructed from transduction and indirect response models and applied using S-ADAPT software. A delay in the onset of increased paw TNF-␣ and IL-6 mRNA concentrations was successfully characterized by simple transduction. This rise was closely followed by an up-regulation of GR mRNA and CST concentrations. Paw swelling and body weight responses peaked approximately 21 days after induction, whereas bone mineral density changes were greatest at 23 days after induction. After peak response, the time course in IL-1␤, IL-6 mRNA, and paw edema slowly declined toward a disease steady state. Model parameters indicate TNF-␣ and IL-1␤ mRNA most significantly induce paw edema, whereas IL-6 mRNA exerted the most influence on BMD. The model for bone mineral density captures rates of turnover of cancellous and cortical bone and the fraction of each in the different regions analyzed. This small systems model integrates and quantitates multiple factors contributing to arthritis in rats

Real-Time Forecasting with a MIDAS VAR

This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon lag polynomial scheme which is designed to reduce the parameter space while keeping models flexible. We show how to recast the resulting non-linear MIDAS type mixed frequency VAR into a linear equation system that can be easily estimated. A pseudo out-of-sample forecasting exercise with US real-time data yields that the mixed frequency VAR substantially improves predictive accuracy upon a standard VAR for different VAR specififications. Forecast errors for, e.g., GDP growth decrease by 30 to 60 percent for forecast horizons up to six months and by around 20 percent for a forecast horizon of one year

Differential Glucose-Regulation of MicroRNAs in Pancreatic Islets of Non-Obese Type 2 Diabetes Model Goto-Kakizaki Rat

The Goto-Kakizaki (GK) rat is a well-studied non-obese spontaneous type 2 diabetes (T2D) animal model characterized by impaired glucose-stimulated insulin secretion (GSIS) in the pancreatic beta cells. MicroRNAs (miRNAs) are short regulatory RNAs involved in many fundamental biological processes. We aim to identify miRNAs that are differentially-expressed in the pancreatic islets of the GK rats and investigate both their short- and long term glucose-dependence during glucose-stimulatory conditions