Laboratory information management systems assurance system

Every analytical laboratory, governmental, private, or university, has a standard set of procedures that provide both general and specific information to laboratory members. These fall into certain categories, including the laboratory s standard operating procedures (SOPs), quality assurance/quality control manuals (QA/QC manuals), procedural manuals, analytical method files, and laboratory information management systems... 

Nakagawa, A.S. LIMS Implementation and Management The Royal Society of Chemistry Cambridge, UK, 1994. Hinton, M.D. Laboratory Information Management Systems Development and Implementation for a Quality Assurance Laboratory Marcel Dekker, Inc. New York, USA, 1995. 

See alsa Blood and Plasma. Chemometrics and Statistics Multivariate Calibration Techniques. Chromatography Overview. Electrophoresis Clinical Applications. Enzymes Enzymes in Physiological Samples Enzyme-Based Assays. Quality Assurance Quality Control Primary Standards Laboratory Information Management Systems. Sample Handling Automated Sample Preparation. 

See QUALITY ASSURANCE Laboratory Information Management Systems... 

See also Quality Assurance Quality Control Instrument Calibration Interlaboratory Studies Reference Materials Production of Reference Materials Laboratory Information Management Systems. 

See also-. Liquid Chromatography Overview. Quality Assurance Laboratory Information Management Systems. Sample Handling Robotics. 

CAQ = computer aided quality assurance EDP = electronic data processing GLP = good laboratory practice LIMS = laboratory information management system QM = quality management. 

Hinton MD (1995) Laboratory Information Management Systems Development and Implementation for a Quality Assurance Laboratory. New York Marcel Dekker. 

In Fig. 42.9 we show the simulation results obtained by Janse [8] for a municipal laboratory for the quality assurance of drinking water. Simulated delays are in good agreement with the real delays in the laboratory. Unfortunately, the development of this simulation model took several man years which is prohibitive for a widespread application. Therefore one needs a simulator (or empty shell) with predefined objects and rules by which a laboratory manager would be capable to develop a specific model of his laboratory. Ideally such a simulator should be linked to or be integrated with the laboratory information management system in order to extract directly the attribute values. 

When the analytical laboratory is not responsible for sampling, the quality management system often does not even take these weak links in the analytical process into account. Furthermore, if sample preparation (extraction, cleanup, etc.) has not been carried out carefully, even the most advanced, quality-controlled analytical instruments and sophisticated computer techniques cannot prevent the results of the analysis from being called into question. Finally, unless the interpretation and evaluation of results are underpinned by solid statistical data, the significance of these results is unclear, which in turn greatly undermines their merit. We therefore believe that quality control and quality assurance should involve all the steps of chemical analysis as an integral process, of which the validation of the analytical methods is merely one step, albeit an important one. In laboratory practice, quality criteria should address the rationality of the sampling plan, validation of methods, instruments and laboratory procedures, the reliability of identifications, the accuracy and precision of measured concentrations, and the comparability of laboratory results with relevant information produced earlier or elsewhere. 

The first step is for someone in management to recognize the need for computer systems validation and to gather the other management expertise necessary to address the issue. This person is usually someone in the Quality Assurance Unit (QAU) or the computer operations, Management Information Systems - MIS, group. While these two departments need to be involved, computer systems users such as laboratory leaders, study directors, and other affected department managers need to be included in the development of a computer systems validation plan. 

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