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Amsterdam-Zuidoost, Netherlands

Rao S.K.,Life science
Journal of Commercial Biotechnology

Cancer is one of the most challenging diseases of all - not only in terms of the clinical barriers to offering its sufferers respite from devastating consequences, but also to manufacturers and marketers of treatments that attempt to control its impact. Products developed and manufactured through biotechnology dominate the commercial landscape for treating a variety of cancer types. The recent spate of new biologic launches for treating cancer delivered through injections, infusions and oral formulations will only increase in the next five years. The task of developing a viable commercial model for the effective delivery of cancer treatments to its customers lies at the center of ensuring that advances in cancer care are harnessed for their full potential. Both by definition and due to the reality of the cancer landscape, such a model is best conceptualized with the patient at its center. This article describes elements of a patient centric commercial model for cancer care, after recognizing the challenges and opportunities inherent in its commercialization and marketing. The impact of such a model resides in its ability to offer tangible benefits to patients by improving access to leading edge treatments, energizing communication at the point of care, and adequately harnessing the emerging promise of new technology. By viewing the patient at the center of a commercial model, manufacturers and marketers of cancer care treatments can offer products that provide ongoing care for the cancer patient from initiation through palliation, thereby building loyalty and realizing the full potential inherent in such treatments. Source

Carlsen K.,Life science
VTT Symposium (Valtion Teknillinen Tutkimuskeskus)

The lecture embraces a process description and an informative case describing validation of an isolator for a new installation for sterility testing validated recently. The lecture will also include a description of the practical challenges related to sterility testing operations as well as regulatory requirements. The purpose of the lecture is to present the problems that need to be addressed in the aseptic handling, the reasons to choose an isolator among different alternatives, a description of the installation and daily handling of the samples. Finally the presentation will exemplify a step-by-step validation. The method of validation comprises activities as BI's, smoke study, and cycle performed with an empty chamber as well as PQ with a defined load. Key features of the installation and validation will be clarified; dedicated biodecontamination unit, Rapid transfer systems, particle counter and air sampling. Sterility testing as the last QC test for injectable products brings a continuity in the control of aseptic processing and it must be performed with at least the same environmental quality than the in-process controls. Isolator technology gives this quality and a full traceability. Source

Abts K.C.,Purdue University | Ivy J.A.,Life science | DeWoody J.A.,Purdue University

The study of the koala transcriptome has the potential to advance our understanding of its immunome—immunological reaction of a given host to foreign antigens—and to help combat infectious diseases (e.g., chlamydiosis) that impede ongoing conservation efforts. We used Illumina sequencing of cDNA to characterize genes expressed in two different koala tissues of immunological importance, blood and spleen. We generated nearly 600 million raw sequence reads, and about 285 million of these were subsequently assembled and condensed into ~70,000 subcomponents that represent putative transcripts. We annotated ~16 % of these subcomponents and identified those related to infection and the immune response, including Toll-like receptors (TLRs), RIG-I-like receptors (RLRs), major histocompatibility complex (MHC) genes, and koala retrovirus (KoRV). Using phylogenetic analyses, we identified 29 koala genes in these target categories and report their concordance with currently accepted gene groups. By mapping multiple sequencing reads to transcripts, we identified 56 putative SNPs in genes of interest. The distribution of these SNPs indicates that MHC genes (34 SNPs) are more diverse than KoRV (12 SNPs), TLRs (8 SNPs), or RLRs (2 SNPs). Our sequence data also indicate that KoRV sequences are highly expressed in the transcriptome. Our efforts have produced full-length sequences for potentially important immune genes in koala, which should serve as targets for future investigations that aim to conserve koala populations. © 2015, Springer-Verlag Berlin Heidelberg. Source

White A.J.,University of Regina | Poulin R.G.,Life science | Wissel B.,University of Regina | Doucette J.L.,University of Regina | Somers C.M.,University of Regina
Canadian Journal of Zoology

Habitat conversion is among the most important causes of environmental change worldwide, yet relatively little is known about its potential influence on trophic interactions. We investigated the effects of agricultural land use on carbon and nitrogen stable isotope values, trophic status, population density, and body condition of deer mice (Peromyscus maniculatus (Wagner, 1845)) in a grassland ecosystem. Muscle δ15N (cropland = 7.6‰ ± 1.3‰; hay fields = 7.9‰ ± 1.3‰; native prairie = 7.2‰ ± 2.1‰) from deer mice did not vary with land use despite baseline soil and vegetation δ15N differences. Enrichment of deer mice over vegetation (Δδ15N) was, on average, a full trophic level (~2.5‰) higher on native prairie (6.4‰ ± 1.6‰) than on cropland (3.9‰ ± 2.3‰), and intermediate in hay fields (5.9‰ ± 2.0‰). Relative density of deer mice was more than twofold higher in crop and hay fields compared with native prairie, but body condition did not vary with land use. Our results suggest that agricultural activity caused a shift in the trophic level and relative abundance of a generalist grassland omnivore. Soil and vegetation δ15N reflected anthropogenic N inputs to agricultural fields but were not useful as general markers of habitat use in this study. Source

Staiger C.,Life science | Staiger C.,Netherlands Cancer Institute | Cadot S.,Netherlands Cancer Institute | Gyorffy B.,Hungarian Academy of Sciences | And 4 more authors.
Frontiers in Genetics

Integrating gene expression data with secondary data such as pathway or protein-protein interaction data has been proposed as a promising approach for improved outcome prediction of cancer patients. Methods employing this approach usually aggregate the expression of genes into new composite features, while the secondary data guide this aggregation. Previous studies were limited to few data sets with a small number of patients. Moreover, each study used different data and evaluation procedures. This makes it difficult to objectively assess the gain in classification performance. Here we introduce the Amsterdam Classification Evaluation Suite (ACES). ACES is a Python package to objectively evaluate classification and feature-selection methods and contains methods for pooling and normalizing Affymetrix microarrays from different studies. It is simple to use and therefore facilitates the comparison of new approaches to best-in-class approaches. In addition to the methods described in our earlier study (Staiger et al., 2012), we have included two prominent prognostic gene signatures specific for breast cancer outcome, one more composite feature selection method and two network-based gene ranking methods. Employing the evaluation pipeline we show that current composite-feature classification methods do not outperform simple single-genes classifiers in predicting outcome in breast cancer. Furthermore, we find that also the stability of features across different data sets is not higher for composite features. Most stunningly, we observe that prediction performances are not affected when extracting features from randomized PPI networks. © 2013 Staiger, Cadot, Györffy, Wessels and Klau. Source

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