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Radar chart array analysis to visualize effects of formulation variables on IgG1 particle formation as measured by multiple analytical techniques.

ABSTRACT: This study presents a novel method to visualize protein aggregate and particle formation data to rapidly evaluate the effect of solution and stress conditions on the physical stability of an immunoglobulin G (IgG) 1 monoclonal antibody (mAb). Radar chart arrays were designed so that hundreds of microflow digital imaging (MFI) solution measurements, evaluating different mAb formulations under varying stresses, could be presented in a single figure with minimal loss of data resolution. These MFI radar charts show measured changes in subvisible particle number, size, and morphology distribution as a change in the shape of polygons. Radar charts were also created to visualize mAb aggregate and particle formation across a wide size range by combining data sets from size-exclusion chromatography, Archimedes resonant mass measurements, and MFI. We found that the environmental/mechanical stress condition (e.g., heat vs. agitation) was the most important factor in influencing the particle size and morphology distribution with this IgG1 mAb. Additionally, the presence of NaCl exhibited a pH and stress-dependent behavior resulting in promotion or inhibition mAb particle formation. This data visualization technique provides a comprehensive analysis of the aggregation tendencies of this IgG1 mAb in different formulations with varying stresses as measured by different analytical techniques.

SUBMITTER: Kalonia C

PROVIDER: S-EPMC3856888 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Radar chart array analysis to visualize effects of formulation variables on IgG1 particle formation as measured by multiple analytical techniques.

Kalonia Cavan C Kumru Ozan S OS Kim Jae Hyun JH Middaugh C Russell CR Volkin David B DB

Journal of pharmaceutical sciences 20131009 12

This study presents a novel method to visualize protein aggregate and particle formation data to rapidly evaluate the effect of solution and stress conditions on the physical stability of an immunoglobulin G (IgG) 1 monoclonal antibody (mAb). Radar chart arrays were designed so that hundreds of microflow digital imaging (MFI) solution measurements, evaluating different mAb formulations under varying stresses, could be presented in a single figure with minimal loss of data resolution. These MFI r ...[more]

PMID: 24122556

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Project description:Zinc deficiency continues to be a major concern for global public health. The zinc status of a target population is typically estimated by measuring circulating zinc levels, but the sampling procedures are not standardized and thus may result in analytical discrepancies. To examine this, we designed a study that controlled most of the technical parameters in order to focus on five pre-analytical variables reported to influence the measurement of zinc in blood samples, including (1) blood draw site (capillary or venous), (2) blood sample matrix (plasma or serum), (3) blood collection tube manufacturer (Becton, Dickinson and Company or Sarstedt AG & Co), (4) blood processing time (0, 4, or 24 hours), and (5) blood holding temperatures (4°C, 20°C, or 37°C). A diverse cohort of 60 healthy adults were recruited to provide sequential capillary and venous blood samples, which were carefully processed under a single chain of custody and measured for zinc content using inductively coupled plasma optical emission spectrometry. When comparing blood draw sites, the mean zinc content of capillary samples was 0.054 mg/L (8%; p<0.0001) higher than venous blood from the same donors. When comparing blood sample matrices, the mean zinc content of serum samples was 0.029 mg/L (5%; p<0.0001) higher than plasma samples from the same donors. When comparing blood collection tube manufacturer, the mean zinc content from venous blood samples did not differ between venders, but the mean zinc content from BD capillary plasma was 0.036 mg/L (6%; p<0.0001) higher than Sarstedt capillary plasma from the same donors. When comparing processing times, the mean zinc content of plasma and serum samples was 5-12% higher (p<0.0001) in samples processed 4-24 hour after collection. When comparing holding temperatures, the mean zinc content of plasma and serum samples was 0.5-7% higher (p = 0.0007 or p = 0.0061, respectively) in samples temporarily held at 20°C or 37°C after collection. Thus even with the same donors and blood draws, significant differences in zinc content were observed with different draw sites, tube types, and processing procedures, demonstrating that key pre-analytic variables can have an impact on zinc measurement, and subsequent classification of zinc status. Minimizing these pre-analytical variables is important for generating best practice guidelines for assessment of zinc status.

Project description:BackgroundIt is known from recent studies that more than 90% of human multi-exon genes are subject to Alternative Splicing (AS), a key molecular mechanism in which multiple transcripts may be generated from a single gene. It is widely recognized that a breakdown in AS mechanisms plays an important role in cellular differentiation and pathologies. Polymerase Chain Reactions, microarrays and sequencing technologies have been applied to the study of transcript diversity arising from alternative expression. Last generation Affymetrix GeneChip Human Exon 1.0 ST Arrays offer a more detailed view of the gene expression profile providing information on the AS patterns. The exon array technology, with more than five million data points, can detect approximately one million exons, and it allows performing analyses at both gene and exon level. In this paper we describe BEAT, an integrated user-friendly bioinformatics framework to store, analyze and visualize exon arrays datasets. It combines a data warehouse approach with some rigorous statistical methods for assessing the AS of genes involved in diseases. Meta statistics are proposed as a novel approach to explore the analysis results. BEAT is available at http://beat.ba.itb.cnr.it.ResultsBEAT is a web tool which allows uploading and analyzing exon array datasets using standard statistical methods and an easy-to-use graphical web front-end. BEAT has been tested on a dataset with 173 samples and tuned using new datasets of exon array experiments from 28 colorectal cancer and 26 renal cell cancer samples produced at the Medical Genetics Unit of IRCCS Casa Sollievo della Sofferenza.To highlight all possible AS events, alternative names, accession Ids, Gene Ontology terms and biochemical pathways annotations are integrated with exon and gene level expression plots. The user can customize the results choosing custom thresholds for the statistical parameters and exploiting the available clinical data of the samples for a multivariate AS analysis.ConclusionsDespite exon array chips being widely used for transcriptomics studies, there is a lack of analysis tools offering advanced statistical features and requiring no programming knowledge. BEAT provides a user-friendly platform for a comprehensive study of AS events in human diseases, displaying the analysis results with easily interpretable and interactive tables and graphics.

Dataset Information

Radar chart array analysis to visualize effects of formulation variables on IgG1 particle formation as measured by multiple analytical techniques.

Publications

Radar chart array analysis to visualize effects of formulation variables on IgG1 particle formation as measured by multiple analytical techniques.

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