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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Pharma-production.jpg|160px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Karaattuthazhathu NatJLabMed23 12-2.png|260px]]</div>
'''[[Good Automated Manufacturing Practice]]''' ('''GAMP''') is both a technical subcommittee of the International Society for Pharmaceutical Engineering (ISPE) and a set of guidelines for manufacturers and users of automated systems in the pharmaceutical industry. One of the core principles of GAMP is that quality cannot be tested into a batch of product but must be built into each stage of the manufacturing process. As a result, GAMP covers all aspects of production; from the raw materials, facility and equipment to the training and hygiene of staff.
'''"[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]"'''


GAMP is largely about automated system validation. In October 2014, Irish tech company Dataworks Ltd. described it as such:
For the release of precise and accurate reports of [[Medical test|routine tests]], its necessary to follow a proper [[quality management system]] (QMS) in the [[clinical laboratory]]. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the [[laboratory]] testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory [[analyte]] by Six Sigma analysis and to plan and chart out a better, customized [[quality control]] (QC) plan for each analyte, according to its own sigma value ... ('''[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Full article...]]''')<br />
 
''Recently featured'':
"It is a formal process of thorough documentation, testing, and logical process steps that validate clients' required specifications. The process begins with a user requirements specification for the machine, from which a functional requirement and a design specification are created. These documents then form the basis for the traceability matrix and for the formal testing of internal acceptance, factory acceptance, and site acceptance. Categorising software is used to support the approach to validation based on the difficulty and individuality of the computerised system." ('''[[Good Automated Manufacturing Practice|Full article...]]''')<br />
{{flowlist |
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* [[Journal:Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems|Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems]]
''Recently featured'': [[End-stage renal disease facility]], [[Genome informatics]], [[Cancer informatics]]
* [[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Data management challenges for artificial intelligence in plant and agricultural research]]
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}}

Revision as of 16:52, 29 April 2024

Fig1 Karaattuthazhathu NatJLabMed23 12-2.png

"Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study"

For the release of precise and accurate reports of routine tests, its necessary to follow a proper quality management system (QMS) in the clinical laboratory. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the laboratory testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory analyte by Six Sigma analysis and to plan and chart out a better, customized quality control (QC) plan for each analyte, according to its own sigma value ... (Full article...)
Recently featured: