The global Label-Free Detection market
is projected to reach US$1.3 billion by 2025, driven by growing drug R&D, rising
competitive pressure to reduce cost of drug development and the resulting need for
cost-effective and efficient screening technologies. Traditional label-based assays
are beset with drawbacks such as high cost associated with label preparation;
lower levels of sensitivity and accuracy as measurements are made indirectly
using a labeled reactant; risk of certain antigen/antibody reactions not being
detected; requires multiple steps and is time consuming; and tendency to modify
the physicochemical or binding properties making accurate drug characterization
difficult. In this regard, label-free assays for biochemical and cell-based
drug discovery is growing in importance due to the many benefits offered such
as ability to identify difficult target classes, better insights offered into
drug binding kinetics and drug residence time; highly sensitive detection of
small molecules, proteins and cells; simple assay procedure; less potential for
false positive/negatives; eliminates labelling & reagent costs; aids in
high-throughput, independent screening of whole cells; provides new insights
into compound action and helps devise better optimization strategies; increased
sensitivity and specificity; more
accurate quantification of biological responses, among others. All of these
benefits are helping replace traditional techniques like radioactive assays, enzyme-labelled
assays (ELISA assays), fluorescent labeled assays, luminescent labeled assays,
and Chemiluminescence immunoassay (CLIA) with label-free options. Read More…
The Global Market for Big Data Technologies and Services is Projected to Reach $60 Billion by 2022
GIA launches comprehensive analysis of industry segments, trends, growth drivers, market share, size and demand forecasts on the global Big Data market. The global market for Big Data Technologies and Services is projected to reach $60 billion by 2022 , driven by soaring digital data volumes in organizations and the resulting need to turn this data into valuable insights for enhancing operational efficiency, tapping new opportunities and gaining competitive edge. Defined as a natural result of mankind’s obsession with information technology and digitalization, “Big Data” refers to extremely large sets of structured, semi-structured and unstructured data of different types, including text, audio or video, generated from diverse data sources that has the potential to be mined for required information. While data supply associated with big data ecosystem has always been large and voluminous in most organizations, the ability to use these large datasets and convert them into meaningf
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