Total quality in laboratory diagnostics: the role of commercial companies

Quality is a key focus for clinical laboratories, since it is viewed as a prerequisite for patient safety. It permeates all three phases of the total testing process (preanalytical, analytical and postanalytical), and relies heavily on the quality of diagnostic products, such as in vitro (IVD) devices (instruments, assays, reagents and specimen collection tubes) and medical devices (blood collection needles and sets). The diagnostic industry has implemented strict criteria to assure that the quality of their products throughout their life cycle meets the needs of their customers. This is accomplished through established processes to develop products that meet customer needs, as well as regulatory requirements needed to assure their safety and efficacy while adhering to good clinical practices and maintaining high level of safety of human subjects that participate in clinical trials. At the same time, the commercial companies follow good manufacturing practices to reduce variability within their manufacturing processes and deliver products that are within established specifications. However, the highest level of quality can only be achieved when instrument/assay manufacturers work closely with specimen containment manufacturers to assure total system performance

Bioeconomic fiction between narrative dynamics and a fixed imaginary: evidence from India and Germany

Bioeconomic ideas and visions have received increasing attention from scientists and policy makers to address socioecological challenges. However, the role of imagined futures in the design of bioeconomic innovations and transitions has hitherto been widely neglected. In this study, we therefore explore the role of imaginaries of the future to understand how they shape bioeconomic innovations and transitions. We thereby build on insights from economic sociology and compare two distinct case studies from Germany and India. Based on our results, we inductively develop an analytic model that describes the co-constitution of imaginaries, fictional expectations, narratives, and innovation dynamics. Our results show that narrative dynamics are caused by irritations in the political and discursive landscape; these irritations prompt economic actors to stabilize, adapt, or reject their own bioeconomic conceptions, while the underlying imaginary of a technological fix remains fixed. We discuss this reductionist imaginary and instead plead for an imaginary of a socioecological fix that reintertwines technologies with their underlying societal, cultural, and ecological factors. We conclude that this will support sustainability scholars and policy makers in remaining vigilant against premature mental and institutional lock-ins that could lead to a colonization of the future with severe negative implications for society's ability to mitigate and adapt to global environmental change in the future

LambdaLoss: Metric-Driven Loss for Learning-to Rank

How to directly optimize ranking metrics such as Normalized Dis­counted Cumulative Gain (NDCG) is an interesting but challenging problem, because ranking metrics are either flat or discontinuous ev­erywhere. Among existing approaches, LambdaRank is a novel algo­rithm that incorporates metrics into its learning procedure. Though empirically effective, it still lacks theoretical justification. For ex­ample, what is the underlying loss that LambdaRank optimizes for? Due to this, it is unclear whether LambdaRank will always converge. In this paper, we present a well-defined loss for LambdaRank in a probabilistic framework and show that LambdaRank is a special configuration in our framework. This framework, which we call LambdaLoss, provides theoretical justification for Lamb-daRank. Furthermore, we propose a few more metric-driven loss functions in our LambdaLoss framework. Our loss functions have clear connection to ranking metrics and can be optimized in our framework efficiently. Experiments on three publicly available data sets show that our methods significantly outperform the state-of-the-art learning-to-rank algorithms. This confirms both the theo­retical soundness and the practical effectiveness of the LambdaLoss framework

Total quality in laboratory diagnostics: the role of commercial companies

Quality is a key focus for clinical laboratories, since it is viewed as a prerequisite for patient safety. It permeates all three phases of the total testing process (preanalytical, analytical and postanalytical), and relies heavily on the quality of diagnostic products, such as in vitro (IVD) devices (instruments, assays, reagents and specimen collection tubes) and medical devices (blood collection needles and sets). The diagnostic industry has implemented strict criteria to assure that the quality of their products throughout their life cycle meets the needs of their customers. This is accomplished through established processes to develop products that meet customer needs, as well as regulatory requirements needed to assure their safety and efficacy while adhering to good clinical practices and maintaining high level of safety of human subjects that participate in clinical trials. At the same time, the commercial companies follow good manufacturing practices to reduce variability within their manufacturing processes and deliver products that are within established specifications. However, the highest level of quality can only be achieved when instrument/assay manufacturers work closely with specimen containment manufacturers to assure total system performance