Retrospective Evaluation of Cycled Resin in Viral Clearance Studies-A Multiple Company Collaboration.

The BioPhorum Development Group Viral Clearance Workstream performed a collaborative retrospective analysis to evaluate packed bed chromatographic resin performance after repeated cycling for two commonly used chromatography steps in biopharmaceutical manufacturing: protein A and anion exchange. Key variables evaluated in the assessment included virus type, resin type, number of reuse cycles, and virus challenge. In this retrospective analysis of viral clearance data on naïve versus cycled resin, powered by the availability of a decade's worth of accumulated industry data, clearance capability was not negatively impacted by resin cycling. This finding is consistent with publications showing that surrogates for viral clearance capabilities could be employed in lieu of testing the viral clearance of cycled resins for protein A and anion exchange chromatography. The rigorous analysis of the retrospective data supports the view that viral clearance studies for cycled resins are not necessary provided that appropriate cleaning methods are applied during repeated use of the chromatography columns.LAY ABSTRACT: The manufacturing processes for biopharmaceutical products often include reusable chromatographic resins that remove process- and product-related impurities as well as potential contaminating viruses. Typically, chromatography resin is "cycled" through repeated steps of resin conditioning, product purification, and resin cleaning. The cycling approach has been evaluated in both small- and full-scale studies that show the performance parameters are maintained. The ability to remove virus is demonstrated separately in a focused small-scale virus-spiking study that is resource-intensive and costly. This paper is a retrospective review of industry data comparing virus removal by naïve and repeatedly cycled resins that summarizes the viral clearance impact of re-using protein A and anion exchange chromatography resins. The key variables evaluated in the assessment included virus type, resin type, number of cycles, and virus challenge. In this retrospective analysis, it was found that the viral clearance capability is not negatively impacted by resin cycling. This finding is consistent with other publications and supports the view that viral clearance studies for cycled resins are not necessary if appropriate cleaning methods are applied during the repeated use of the chromatography columns.Abbreviations: AAV-2, Adeno-associated virus; A-MuLV, Amphotropic murine leukemia virus; AEX, Anion-exchange chromatography; B/E, Bind and elute; BVDV, Bovine viral diarrhea virus; C.P.G., Controlled pore glass; DEAE, Diethylaminoethanol; EMCV, Encephalomyocarditis virus; FT, Flow through; HAV, Hepatitis A virus; HSV-1, Herpes simplex virus type 1; LOD, Limit of detection; LOQ, Limit of quantification; LRF, Log10 reduction factor; mAb, Monoclonal antibody; MVM, Minute virus of mice; NaOH, Sodium hydroxide; PA, Protein A; PPV, Porcine parvovirus; QA, Quaternary amine; QP, Quaternized polyethyleneimine; qPCR, Quantitative polymerase chain reaction; Reo3, Reovirus type 3; SuHV-1, Suid herpesvirus; SV40, Simian virus 40; X-MuLV, Xenotropic murine leukemia virus.

Quantifying the Vial Capping Process: Residual Seal Force and Container Closure Integrity.

Capping completes the closure of parenteral drug products in the final packaging container and is critical in maintaining an integral seal to ensure product quality. Residual seal force (RSF) is considered the sole quantifiable attribute for measuring seal "goodness" and potentially enables nonsubjective, consistent setting of cappers across manufacturing sites. However, the consistency and reliability of RSF measurement and data have been scarcely reported, and the relationship between RSF and container closure integrity (CCI) remains poorly understood.Here, we present a large data set generated from a commercial capper and the results from a laboratory capper of glass vials and rubber stoppers with aluminum caps. All RSF values exhibited significant variability. We evaluated four potential sources of variability: the capper, the RSF tester, the time-dependent nature of RSF, and the components. We determined that the capper, the tester, and the time-dependent nature are not main sources. Dimensional tolerances of the packaging components were the root cause for the container closure system (CCS) configurations tested in this study.This study correlated RSF with CCI (via helium leakage), although CCI is not sensitive to RSF; CCI was maintained even for loosely capped vials with no measurable RSF. This was attributed to the stopper's two sealing surfaces: the valve seal and the land seal. A methodology capable of differentiating the two seals' functions demonstrated that vials with only the valve seal always passed leakage testing for a selected CCS configuration in this study, while vials with only the land seal failed CCI at low RSF values. This observation allows proposal of a low RSF limit that is safe even when the valve seal is defective. Simplified statistical analysis of commercial capping data, with the input of sample size, allowed the relationship between RSF's low limit and an allowable failing rate to be established. Overall, despite the inherent variability of RSF, this study shows that it is a feasible parameter for capping process quantification and demonstrates the potential of RSF measurement in capper setup.LAY ABSTRACT: Pharmaceutical vials are typically closed off with an elastomeric stopper that is secured onto the vial with an aluminum crimp cap (or seal) such that the entire assembly is meant to protect the vial's contents from external contamination. Therefore, the capping process is critical for ensuring container closure integrity. Characterizing the effectiveness of a seal in a nonsubjective and quantifiable manner is challenging. In this communication, we report the evaluation of residual seal force measurements (the compression force that the crimp cap exerts on the stopper) to evaluate capping for a large set of samples generated on both an at-scale commercial capper and a benchtop laboratory capper. We propose a test methodology, based on a statistical approach, for establishing permissible lower residual force limits that would provide a high degree of confidence to the capping process. This is a useful tool for consistent capper setup and capping process quantification.

Proportion of U.S. Trends in Breast Cancer Incidence Attributable to Long-term Changes in Risk Factor Distributions.

Background: U.S. breast cancer incidence has been changing, as have distributions of risk factors, including body mass index (BMI), age at menarche, age at first live birth, and number of live births.Methods: Using data for U.S. women from large nationally representative surveys, we estimated risk factor distributions from 1980 to 2008. To estimate ecologic associations with breast cancer incidence, we fitted Poisson models to age- and calendar year-specific incidence data from the NCI's Surveillance, Epidemiology and End Results registries from 1980 to 2011. We then assessed the proportion of incidence attributable to specific risk factors by comparing incidence from models that only included age and calendar period as predictors with models that additionally included age- and cohort-specific categorized mean risk factors. Analyses were stratified by age and race.Results: Ecologic associations usually agreed with previous findings from analytic epidemiology. From 1980 to 2011, compared with the risk factor reference level, increased BMI was associated with 7.6% decreased incidence in women ages 40 to 44 and 2.6% increased incidence for women ages 55 to 59. Fewer births were associated with 22.2% and 3.99% increased incidence in women ages 40 to 44 and 55 to 59 years, respectively. Changes in age at menarche and age at first live birth in parous women did not significantly impact population incidence from 1980 to 2011.Conclusions: Changes in BMI and number of births since 1980 significantly impacted U.S. breast cancer incidence.Impact: Quantifying long-term impact of risk factor trends on incidence is important to understand the future breast cancer burden and inform prevention efforts. Cancer Epidemiol Biomarkers Prev; 27(10); 1214-22. ©2018 AACR.

An imputation-based solution to using mismeasured covariates in propensity score analysis.

Although covariate measurement error is likely the norm rather than the exception, methods for handling covariate measurement error in propensity score methods have not been widely investigated. We consider a multiple imputation-based approach that uses an external calibration sample with information on the true and mismeasured covariates, multiple imputation for external calibration, to correct for the measurement error, and investigate its performance using simulation studies. As expected, using the covariate measured with error leads to bias in the treatment effect estimate. In contrast, the multiple imputation for external calibration method can eliminate almost all the bias. We confirm that the outcome must be used in the imputation process to obtain good results, a finding related to the idea of congenial imputation and analysis in the broader multiple imputation literature. We illustrate the multiple imputation for external calibration approach using a motivating example estimating the effects of living in a disadvantaged neighborhood on mental health and substance use outcomes among adolescents. These results show that estimating the propensity score using covariates measured with error leads to biased estimates of treatment effects, but when a calibration data set is available, multiple imputation for external calibration can be used to help correct for such bias.

Big Data and Neuroimaging.

Big Data are of increasing importance in a variety of areas, especially in the biosciences. There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas. Importantly, statisticians and statistical thinking have a major role to play in creating meaningful progress in this arena. We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big Data problems. We use the field of statistical neuroimaging to demonstrate these points. As such, this paper covers several applications and novel methodological developments of Big Data tools applied to neuroimaging data.

Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention.

We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation of risk-difference- and risk-ratio-based effects (RDs, RRs) using the ML, WLSMV and Bayes estimators in Mplus. Across most variations in path-coefficient and mediator-residual-correlation signs and strengths, and confounding situations investigated, the method performs well with all estimators, but favors ML/WLSMV for RDs with continuous mediators, and Bayes for RRs with ordinal mediators. Bayes outperforms WLSMV/ML regardless of mediator type when estimating RRs with small potential outcome probabilities and in two other special cases. An adolescent alcohol prevention study is used for illustration.

Survival and clinical features in Hispanic amyotrophic lateral sclerosis patients.

The demography, survival, and motor phenotypes of amyotrophic lateral sclerosis (ALS) patients have been rarely described in Hispanic countries. The clinical characteristics and survival of a series of Mexican ALS patients are described. Mexican patients with definite ALS were included in a five-year retrospective longitudinal study. Their demographic and clinical features, cumulative survival rates, and independent predictive factors for survival were analysed. Sixty-one definite ALS patients were included. The median follow-up period was 35 months (range 12-108 months). Males were predominant (1.8: 1), the mean age at onset was 47.5 ± 10.5 years, and the median interval from onset to diagnosis was 12 months. Spinal onset occurred in 66% of patients. Upper motor neuron phenotype was predominant in 53% of patients. The overall mean survival from onset was 68.6 months, and from diagnosis was 57.8 months. Longer survival was determined in patients aged ≤ 40 years (54.7 months) compared with other age groups (p = 0.006). In conclusion, the clinical heterogeneity, male predominance, and survival rates in our sample are consistent with those of other studies. Patients in this series had a younger age at onset and a clear trend toward longer survival compared with those of other population studies.

An influenza A/H1N1/2009 hemagglutinin vaccine produced in Escherichia coli.

BACKGROUND: The A/H1N1/2009 influenza pandemic made evident the need for faster and higher-yield methods for the production of influenza vaccines. Platforms based on virus culture in mammalian or insect cells are currently under investigation. Alternatively, expression of fragments of the hemagglutinin (HA) protein in prokaryotic systems can potentially be the most efficacious strategy for the manufacture of large quantities of influenza vaccine in a short period of time. Despite experimental evidence on the immunogenic potential of HA protein constructs expressed in bacteria, it is still generally accepted that glycosylation should be a requirement for vaccine efficacy. METHODOLOGY/PRINCIPAL FINDINGS: We expressed the globular HA receptor binding domain, referred to here as HA(63-286)-RBD, of the influenza A/H1N1/2009 virus in Escherichia coli using a simple, robust and scalable process. The recombinant protein was refolded and purified from the insoluble fraction of the cellular lysate as a single species. Recombinant HA(63-286)-RBD appears to be properly folded, as shown by analytical ultracentrifugation and bio-recognition assays. It binds specifically to serum antibodies from influenza A/H1N1/2009 patients and was found to be immunogenic, to be capable of triggering the production of neutralizing antibodies, and to have protective activity in the ferret model. CONCLUSIONS/SIGNIFICANCE: Projections based on our production/purification data indicate that this strategy could yield up to half a billion doses of vaccine per month in a medium-scale pharmaceutical production facility equipped for bacterial culture. Also, our findings demonstrate that glycosylation is not a mandatory requirement for influenza vaccine efficacy.