India Laboratory Information Management System Market Trends 2013
News May 21, 2013
The Laboratory Information Management System (LIMS) forms a niche market segment in India presently. The growing systemization of laboratories will gradually steer forth the market. The simultaneous rapid development of Indian healthcare sector that is seeing rise in number of various types of laboratories will propel the future of LIMS adoption in Indian healthcare sector as well.
The report begins with macro economic indicators whereby the basic economic indicators have been depicted.The introduction section provides a broad overview of Indian healthcare sector and how IT adoption in healthcare is having a valued impact on performance of the sector. The report progresses to describe the sectors where LIMS has applications along with the benefits of the software. The section also describes the historical development pathway of LIMS.
The next section highlights the value wise market size and growth of LIMS software and also the adoption of LIMS specifically in the Indian healthcare sector.The report then describes the LIMS structure encapsulating common modules and the step wise workflow of the LIMS from requisition to information deliver and LIMS in terms of application. In the next section, the distribution channel has been elaborated from designing of software to final installation of software.
The report then focuses on the healthcare applications of LIMS with description of methodical solutions LIMS provides in life sciences, pharmaceutical and biotechnology and in contract service laboratories.
The next section elaborates the drivers and challenges that the market is currently facing. Drivers include growing clinical laboratories, growing pharmaceutical industry, growing clinical trials market, rising biotechnology industry and factor such as significance laid on laboratory accreditation. Challenges in the market include disparity in ‘quality’ standards and high cost of installation.
Though the LIMS market is still in a nascent stage, yet the software developers are trying to make the software user friendly and cost effective for which it has come up with the concept of LIMS on Cloud.The competitive landscape section begins with the Porter’s Five Forces Analysis, illustrating the competitive rivalry, bargaining power of suppliers and buyers and threat of new entrants and substitutes.
The section includes competitive benchmarking of the top players operating in the Indian LIMS market. The report also features brief profiles of major domestic and foreign players in the market and a snapshot of their corporation, financial performance along with the key financial ratios, business highlights, their product portfolio and SWOT analysis, thus providing an insight into the existing competitive scenario.
The final section of the report contains strategic recommendations which will be instrumental for the companies to garner a larger market share in the Indian market.
Algorithm Speeds Up Medical Image Analysis 1000 TimesNews
Medical image registration is a common technique that involves overlaying two images, such as magnetic resonance imaging (MRI) scans, to compare and analyze anatomical differences in great detail. Researchers have described a machine-learning algorithm that can register brain scans and other 3-D images more than 1,000 times more quickly using novel learning techniques.
Antarctic Worm and Machine Learning Help Identify Cerebral Palsy EarlierNews
A research team has released a study in the peer-reviewed journal BMC Bioinformatics showing that DNA methylation patterns in circulating blood cells can be used to help identify spastic cerebral palsy (CP) patients. The technique which makes use of machine learning, data science and even analysis of Antarctic worms, raises hopes for earlier targeted CP therapies.
Towards Personalized Medicine: One Type of Data is Not EnoughNews
To understand the biology of diseased organs researchers use different types of molecular data. One of the biggest computational challenges at the moment is integrating these multiple data types. A new computational method jointly analyses different types of molecular data and disentangles the sources of disease variability to guide personalized treatment.READ MORE