Quality control of membrane filters for bacteriological examination of water

A standard protocol for quality control of membrane filters for bacteriological examination of water is presented. It is based on the screening test proposed by Brenner and Rankin (1990) making use of Enterobacter aerogenes ATCC 49701 as a test strain and tryptone soya agar as medium for incubation. The protocol is standardized to achieve adequate statistical power. A diluted culture of the test strain is filtered through samples of 20 filters of a test batch and a reference batch. Filters and colony morphology are screened for visual defects and criteria for acceptance are given. Variation in the colony counts within the batches is checked for randomness, because filters of a batch must be of equal quality and must not cause overdispersion. The protocol requires that the mean count of the reference batch should lie between 50 and 80 cfu. Homogeneity of the counts (i.e. variation no greater than random) between the batches is tested at a 99% confidence level. In this way an actual difference in recovery between filter batches of 13% to 16% can be detected with a probability of 90%. Results of several tests within this laboratory show good reproducibility.     

Scale up, optimization and stability analysis of Curcumin C3 complex-loaded nanoparticles for cancer therapy

ABSTRACT: BACKGROUND: Nanoparticle based delivery of anticancer drugs have been widely investigated. However, a very important process for Research & Development in any pharmaceutical industry is scaling nanoparticle formulation techniques so as to produce large batches for preclinical and clinical trials. This process is not only critical but also difficult as it involves various formulation parameters to be modulated all in the same process. METHODS: In our present study, we formulated curcumin loaded poly (lactic acid-co-glycolic acid) nanoparticles (PLGA-CURC). This improved the bioavailability of curcumin, a potent natural anticancer drug, making it suitable for cancer therapy. Post formulation, we optimized our process by Reponse Surface Methodology (RSM) using Central Composite Design (CCD) and scaled up the formulation process in four stages with final scale-up process yielding 5 g of curcumin loaded nanoparticles within the laboratory setup. The nanoparticles formed after scale-up process were characterized for particle size, drug loading and encapsulation efficiency, surface morphology, in vitro release kinetics and pharmacokinetics. Stability analysis and gamma sterilization were also carried out. RESULTS: Results revealed that that process scale-up is being mastered for elaboration to 5 g level. The mean nanoparticle size of the scaled up batch was found to be 158.5 [PLUS-MINUS SIGN] 9.8 nm and the drug loading was determined to be 10.32 [PLUS-MINUS SIGN] 1.4 %. The in vitro release study illustrated a slow sustained release corresponding to 75 % drug over a period of 10 days. The pharmacokinetic profile of PLGA-CURC in rats following i.v. administration showed two compartmental model with the area under the curve (AUC0-[INFINITY]) being 6.139 mg/L h. Gamma sterilization showed no significant change in the particle size or drug loading of the nanoparticles. Stability analysis revealed long term physiochemical stability of the PLGA-CURC formulation. CONCLUSIONS: A successful effort towards formulating, optimizing and scaling up PLGA-CURC by using Solid-Oil/Water emulsion technique was demonstrated. The process used CCD-RSM for optimization and further scaled up to produce 5 g of PLGA-CURC with almost similar physicochemical characteristics as that of the primary formulated batch.     

A Two-Way Analysis of Covariance Model for Classification of Stability Data

This paper proposes a procedure for testing and classifying data with multiple factors. A two-way analysis of covariance is used to classify the differences among the batches as well as another factor such as package type and/or product strength. In the test procedure, slopes and intercepts of the main effects are tested using a combination of simultaneous and sequential F-tests. Based on the test procedure results, the data are classified into one of four different groups. For each group, shelf life can be calculated accordingly. We examine if the procedure produces satisfactory control of the probability of a Type I error and the power of detecting the difference of degradation rates and intercepts for different nominal levels. The method is evaluated with a Monte Carlo simulation study. The proposed procedure is compared with the current FDA procedure using real data.     

Removing batch effects in analysis of expression microarray data: an evaluation of six batch adjustment methods

The expression microarray is a frequently used approach to study gene expression on a genome-wide scale. However, the data produced by the thousands of microarray studies published annually are confounded by "batch effects," the systematic error introduced when samples are processed in multiple batches. Although batch effects can be reduced by careful experimental design, they cannot be eliminated unless the whole study is done in a single batch. A number of programs are now available to adjust microarray data for batch effects prior to analysis. We systematically evaluated six of these programs using multiple measures of precision, accuracy and overall performance. ComBat, an Empirical Bayes method, outperformed the other five programs by most metrics. We also showed that it is essential to standardize expression data at the probe level when testing for correlation of expression profiles, due to a sizeable probe effect in microarray data that can inflate the correlation among replicates and unrelated samples.     

Relationship between embryo development in vitro and 56-day nonreturn rates of cows inseminated with frozen-thawed semen from dairy bulls

Frozen-thawed bull semen with > 50% post-thaw motility from 40 batches (21 bulls, 2 consecutive ejaculates per batch) was used for fertilization (IVF) and embryo development in vitro to assess the relationship between field and laboratory fertility using a retrospective approach. Each frozen batch was tested in 3 or 4 replicates with 30 oocytes per replicate. Field fertility, quantified as the 56-d nonreturn rate and based on 89 to 441 artificial inseminations per frozen batch, ranged between 46.2 and 74.8%. The cleavage and blastocyst rates after IVF varied from 29.0 to 81.9% and from 1.8 to 32.0%, respectively, with significant differences among frozen batches. Rates of cleavage and blastocyst formation were significantly related to the nonreturn rate (r = 0.59, P < 0.001; r = 0.35, P < 0.05, respectively). The interaction between cleavage and blastocyst rate was 0.69 (P < 0.001). Significant variations (P < 0.05) among frozen semen batches within 15 bulls with >/= 2 different semen batches were found for the nonreturn rate (13.3%) of 2 bulls, for cleavage rates (26.7%) in 4 bulls and for blastocyst rates (20.0%) in 3 bulls. Significant differences (P < 0.05) among replicates within the 40 frozen semen batches were only found in 3 batches (7.5%) for the cleavage rate and in 7 batches (17.5%) for blastocyst rate. Overall, bull and frozen semen batch were the greatest sources of variation in the cleavage rate (30.6 and 29.4%, respectively), while testing date was the greatest source of variation in the blastocyst development rate (21.7%). The results indicated that in vitro fertilization and, to a lesser extent, culture to the blastocyst stage could be useful in estimating the potential fertilizing ability of frozen-thawed semen from dairy bulls.     

Combined vaccines – Case study

Application of the principles outlined in the WHO Guideline on Stability Evaluation of Vaccines is complicated by the nature of combination vaccines. Differences in degradation rates among the immunogens impose the restriction that shelf life is based on the most labile component. There is also a testing challenge with numerous components held at different stages of production.     

Batch effects in a multiyear sequencing study: False biological trends due to changes in read lengths

High‐throughput sequencing is a powerful tool, but suffers biases and errors that must be accounted for to prevent false biological conclusions. Such errors include batch effects; technical errors only present in subsets of data due to procedural changes within a study. If overlooked and multiple batches of data are combined, spurious biological signals can arise, particularly if batches of data are correlated with biological variables. Batch effects can be minimized through randomization of sample groups across batches. However, in long‐term or multiyear studies where data are added incrementally, full randomization is impossible, and batch effects may be a common feature. Here, we present a case study where false signals of selection were detected due to a batch effect in a multiyear study of Alpine ibex (Capra ibex). The batch effect arose because sequencing read length changed over the course of the project and populations were added incrementally to the study, resulting in nonrandom distributions of populations across read lengths. The differences in read length caused small misalignments in a subset of the data, leading to false variant alleles and thus false SNPs. Pronounced allele frequency differences between populations arose at these SNPs because of the correlation between read length and population. This created highly statistically significant, but biologically spurious, signals of selection and false associations between allele frequencies and the environment. We highlight the risk of batch effects and discuss strategies to reduce the impacts of batch effects in multiyear high‐throughput sequencing studies.     

Statistical approaches to handle proportions as characters

The handling of morphometric proportions as characters in phylogenetics is methodically hardly elaborated. Common approaches are either to search for statistically significant differences in "index"-values, usually quotients of measures, or to compare regression lines for logarithmic values. The former have their weakness in an insufficient consideration of allometric proportions, the latter in a lack of appropriate methods for testing statistical significance of differences. This contribution presents a methodical approach which considers both allometry and statistical significance. Moreover, not only significance, but also the size of mean differences, as compared to standard deviations, is calculated. If differences are too small, they do not allow to draw a clear distinction between compared groups, and therefore have a low quality as characters. At the beginning of the procedure a test for gradient differences between allometry lines is applied, and if no such are found, a second test for parallel shift between the two lines. If a difference is found, the extent of which exceeds a prearranged limit, it is accepted as a character difference suitable for phylogenetic reconstruction. This method was practically applied by Wiesemüller & Rothe (1999) in a phylogenetic investigation of New World monkeys (Platyrrhini, Primates).     

A need for careful evaluation of endotoxin contents in acellular pertussis-based combination vaccines

Two batches each of diphtheria-tetanus-acellular pertussis vaccine (DTaP) and that combined with inactivated polio vaccine purchased from foreign markets were tested by mouse body weight decreasing (BWD) toxicity test and Limulus amaebocyte lysate (LAL) test. Three out of the four imported vaccine batches showed the levels of BWD toxicity even comparable to that of DT-whole cell pertussis vaccine. BWD toxicity test is based on endotoxin dose-dependent weight loss of mice and has been used for controlling endotoxin in DTaP. Although of the strong BWD toxicity of the imported vaccines, there was no marked difference in LAL test results between the imported vaccines and Japanese DTaP. However, one imported DTaP batch showed very strong interference with LAL activity of spiked lipopolysaccharide (LPS). The batch interfered not only with LAL activity but also with pyrogenicity and prostaglandin E₂ induction activity. However, the pyrogenicity of the spiked LPS could be recovered from the precipitated fraction of the batch by treating with phosphate buffer to suggest the possibility of recovering in vivo toxicity. As an adequate in vitro test method could not be identified for controlling the safety of the interfering batch, an appropriate in vivo test would be required for testing such vaccines.     

Adjusting batch effects in microarray expression data using empirical Bayes methods

Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to combine microarray data sets is advantageous to researchers to increase statistical power to detect biological phenomena from studies where logistical considerations restrict sample size or in studies that require the sequential hybridization of arrays. In general, it is inappropriate to combine data sets without adjusting for batch effects. Methods have been proposed to filter batch effects from data, but these are often complicated and require large batch sizes ( > 25) to implement. Because the majority of microarray studies are conducted using much smaller sample sizes, existing methods are not sufficient. We propose parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples. We illustrate our methods using two example data sets and show that our methods are justifiable, easy to apply, and useful in practice. Software for our method is freely available at: http://biosun1.harvard.edu/complab/batch/.     

Side-by-side comparability of batch and continuous downstream for the production of monoclonal antibodies

Continuous processing is the future production method for monoclonal antibodies (mAbs). A fully continuous, fully automated downstream process based on disposable equipment was developed and implemented inside the MoBiDiK pilot plant. However, a study evaluating the comparability between batch and continuous processing based on product quality attributes was not conducted before. The work presented fills this gap comparing both process modes experimentally by purifying the same harvest material (side-by-side comparability). Samples were drawn at different time points and positions in the process for batch and continuous mode. Product quality attributes, product-related impurities, as well as process-related impurities were determined. The resulting polished material was processed to drug substance and further evaluated regarding storage stability and degradation behavior. The in-process control data from the continuous process showed the high degree of accuracy in providing relevant process parameters such as pH, conductivity, and protein concentration during the entire process duration. Minor differences between batch and continuous samples are expected as different processing conditions are unavoidable due to the different nature of batch and continuous processing. All tests revealed no significant differences in the intermediates and comparability in the drug substance between the samples of both process modes. The stability study of the final product also showed no differences in the stability profile during storage and forced degradation. Finally, online data analysis is presented as a powerful tool for online-monitoring of chromatography columns during continuous processing.     

The Target Animal Safety Test—Is it Still Relevant?

In Europe, the target animal safety test (TAST) is stipulated by 52 European Pharmacopoeia monographs, by three European Union (EU) Directives and a number of EU guidelines as a routine test for veterinary immunologicals, to be carried out on the finished product. TAST data from seven European Official Member States Control Laboratories (OMCLs) and 14 manufacturers were retrospectively analysed. During 1994–1997, 11 185 vaccine batches had been submitted for batch release, and the OMCLs had tested 670 batches in the TAST (665 passed, 4 passed after retesting, 1 failed). In total, 82 of these batches were not released; however, in only one case this was due to failure in the TAST. The data received from the 14 manufacturers covered the years from 1997 to 1999. 11 386 batches were tested in the TAST, of which 215 passed after retesting and 7 failed. Although only 30% of the OMCLs provided data and the data of the manufacturers are not complete they clearly indicate that the TAST does not contribute to the safety of veterinary vaccines and should therefore not be required as a routine batch test. In cases, where it appears to be necessary, detailed guidance on the test design and evaluation should be given. Copyright 2002 Published by Elsevier Science Ltd on behalf of The International Association for Biologicals.     

Potency estimation of vaccine batches remains unaffected by anesthesia for intracerebral injection

Potency testing of rabies and whole-cell pertussis vaccine batches is still performed by an intracerebral (i.c.) challenge test, in conformity with international regulatory requirements. For the i.c. injection, the use of anesthesia is strongly recommended to alleviate the severe pain induced by the procedure. Today, anesthesia is not consistently mentioned in regulatory requirements, in contrast to the times when the potency tests were developed. The introduction of anesthesia is hampered, due to the lack of data on a hypothetical impact of anesthesia on potency estimation. Here, we show the comparative analysis of the extensive batch release data set of a rabies vaccine for human use that was tested in two laboratories of which only one applied anesthesia. In essence, we find that the mean batch test results were similar to each other, demonstrating that anesthesia for i.c. injection does not interfere with potency estimation. Consequently, we recommend the update of regulatory requirements and protocols and support the implementation of anesthesia for i.c. injection.     

Laboratory host systems for extraneous agent testing in avian live virus vaccines: Problems encountered

The regulation for batch testing of avian live viral vaccines for extraneous agents was modified recently in order to reduce animal use, and routine batch testing had to be adapted to this new regulation. As a result, however, some tests have become more complicated and time-consuming. Due to systematic technical problems, the new methods required could only be applied to a small proportion of the batches produced. As a consequence, the majority of batches are still tested in animals.     

Resampling in Multiple‐Dose Factorial Designs

Multiple‐dose factorial designs may provide confirmatory evidence that (fixed) combination drugs are superior to either component drug alone. Moreover, a useful and safe range of dose combinations may be identified. In our study, we focus on (A) adjustments of the overall significance level made necessary by multiple testing, (B) improvement of conventional statistical methods with respect to power, distributional assumptions and dimensionality, and (C) construction of corresponding simultaneous confidence intervals. We propose novel resampling algorithms, which in a simple way take the correlation of multiple test statistics into account, thus improving power. Moreover, these algorithms can easily be extended to combinations of more than two component drugs and binary outcome data. Published data summaries from a blood pressure reduction trial are analysed and presented as a worked example. An implementation of the proposed methods is available online as an R package.     

Experimental and statistical considerations to avoid false conclusions in proteomics studies using differential in-gel electrophoresis

In quantitative proteomics, the false discovery rate (FDR) can be defined as the number of false positives within statistically significant changes in expression. False positives accumulate during the simultaneous testing of expression changes across hundreds or thousands of protein or peptide species when univariate tests such as the Student's t test are used. Currently most researchers rely solely on the estimation of p values and a significance threshold, but this approach may result in false positives because it does not account for the multiple testing effect. For each species, a measure of significance in terms of the FDR can be calculated, producing individual q values. The q value maintains power by allowing the investigator to achieve an acceptable level of true or false positives within the calls of significance. The q value approach relies on the use of the correct statistical test for the experimental design. In this situation, a uniform p value frequency distribution when there are no differences in expression between two samples should be obtained. Here we report a bias in p value distribution in the case of a three-dye DIGE experiment where no changes in expression are occurring. The bias was shown to arise from correlation in the data from the use of a common internal standard. With a two-dye schema, where each sample has its own internal standard, such bias was removed, enabling the application of the q value to two different proteomics studies. In the case of the first study, we demonstrate that 80% of calls of significance by the more traditional method are false positives. In the second, we show that calculating the q value gives the user control over the FDR. These studies demonstrate the power and ease of use of the q value in correcting for multiple testing. This work also highlights the need for robust experimental design that includes the appropriate application of statistical procedures.     

A combination of walk-back and optimum contribution selection in fish: a simulation study

The aim of this paper was to study the performance of a novel fish breeding scheme, which is a combination of walk-back and optimum contribution selection using stochastic simulation. In this walk-back selection scheme, batches of different sizes (50, 100, 1000, 5000 and 10 000) with the phenotypically superior fish from one tank with mixed families were genotyped to set up the pedigree. BLUP estimated breeding values were calculated. The optimum contribution selection method was used with the rate of inbreeding (ΔF) constrained to 0.005 or 0.01 per generation. If the constraint on ΔF could not be held, a second batch of fish was genotyped etc. Compared with the genotyping of all selection candidates (1000, 5000 or 10 000), the use of batches saves genotyping costs. The results show that two batches of 50 fish were often necessary. With a batch size of 100, genetic level was 76–92% of the genetic level achieved for schemes with all fish being genotyped and thus candidates for the optimum contribution selection step. More parents were selected for schemes with larger batches, resulting in a higher genetic gain, especially when all selection candidates were genotyped. There was little extra genetic gain in genotyping of 1000 fish instead of 100 for the larger schemes of 5000 and 10 000 candidates. The accuracy of breeding values was similar for all batch sizes (~0.30), but higher (~0.5) when all candidates were included. Since only the phenotypically most superior fish were genotyped, BLUP-EBV were biased. Compared with genotyping of all selection candidates, the use of batches saves genotyping costs, while simultaneously maintaining high genetic gains.     

Bootstrap tests for overdispersion in a zero-inflated Poisson regression model

Ridout, Hinde, and Demétrio (2001, Biometrics 57, 219-223) derived a score test for testing a zero-inflated Poisson (ZIP) regression model against zero-inflated negative binomial (ZINB) alternatives. They mentioned that the score test using the normal approximation might underestimate the nominal significance level possibly for small sample cases. To remedy this problem, a parametric bootstrap method is proposed. It is shown that the bootstrap method keeps the significance level close to the nominal one and has greater power uniformly than the existing normal approximation for testing the hypothesis.     

Laboratory methods for studying non-preference resistance to cabbage root fly in cruciferous crops

A laboratory method for testing cruciferous plants for their non-preference resistance to cabbage root fly is described. Test plants were fully randomized on a turntable inside a large chamber containing cabbage root flies. The apparatus was housed in a controlled environment room. The root-fly eggs, laid in the sand surrounding test plants, were extracted using a flask flotation method which was quicker and more efficient than the stirring technique which it superseded. Two batches of plants were tested alternately, one being exposed to the flies, while the other was sampled for eggs. Each batch of test plants received three 1-day exposures to egg-laying, their positions within the test chamber being changed for each exposure to ensure complete randomization. This test method gave highly consistent results and indicated that there were differences in the flies' preference both between cultivars of radish and cauliflower and for individual plants within cultivars. Plants representing the extremes of preferences discovered in the two crops were saved for further study. It was not possible to correlate seed weight, time of seedling emergence, foliage surface area, or hypocotyl attitude in relation to soil level, with the egg-laying preference of the cabbage root flies.     

A Short Term Quality Control Tool for Biodegradable Microspheres

Accelerated in vitro release testing methodology has been developed as an indicator of product performance to be used as a discriminatory quality control (QC) technique for the release of clinical and commercial batches of biodegradable microspheres. While product performance of biodegradable microspheres can be verified by in vivo and/or in vitro experiments, such evaluation can be particularly challenging because of slow polymer degradation, resulting in extended study times, labor, and expense. Three batches of Leuprolide poly(lactic-co-glycolic acid) (PLGA) microspheres having varying morphology (process variants having different particle size and specific surface area) were manufactured by the solvent extraction/evaporation technique. Tests involving in vitro release, polymer degradation and hydration of the microspheres were performed on the three batches at 55°C. In vitro peptide release at 55°C was analyzed using a previously derived modification of the Weibull function termed the modified Weibull equation (MWE). Experimental observations and data analysis confirm excellent reproducibility studies within and between batches of the microsphere formulations demonstrating the predictability of the accelerated experiments at 55°C. The accelerated test method was also successfully able to distinguish the in vitro product performance between the three batches having varying morphology (process variants), indicating that it is a suitable QC tool to discriminate product or process variants in clinical or commercial batches of microspheres. Additionally, data analysis utilized the MWE to further quantify the differences obtained from the accelerated in vitro product performance test between process variants, thereby enhancing the discriminatory power of the accelerated methodology at 55°C.