Research Report : Global Automated Plate Handlers Market | Page 2

The Global Automated Plate Handlers market is valued at USD XX . XX billion in 2016 and is expected to reach a value of USD XX . XX billion by the end of 2022 , growing at a projected CAGR of XX . XX % during the forecast period of 2017 – 2022 . Automation is used in a wide variety of life science applications ranging from proteomics to systems biology . Automation is a dominant feature in the diagnostics market followed by the discovery and research labs . In clinical diagnostics , where profits are based on the number of samples , high throughput is the core driving factor . Total automation is generally preferred in such labs and manufacturing setups . Research labs and academic institutions are generally opting for modular automation , wherein they reduce the human intervention in tedious and repetitive tasks .
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The significant increase in sample throughput and the resulting decrease in the time to produce experimental results have made micro plate automation instrumentation a commonplace in many laboratories . Micro plate automation instruments are used in laboratories for increased throughput and greater scale in various protocols like high throughput screening , next generation sequencing , cellular analysis , PCR set-up , serial dilution , toxicology , plate labeling , etc . They are generally segregated on the basis of accepted capacity , dispensing volume and fluid delivery rates .
Automation of routine laboratory procedures , by the use of dedicated work stations and software to program instruments , allows associate scientists and technicians to think creatively about the implications of their experiments and to design effective follow-up projects or develop alternative approaches to their work instead of spending their days repeating tedious tasks .
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Apart from reducing mundane tasks , the market for laboratory automation is also driven by the need for consistency in quality . Because the cost of an error is very high in a scientific paper or developing a drug , even fairly low error rates can have a profound impact on the conclusions you make downstream .
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