The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics. In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC–MS) in untargeted metabolomics. All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach. For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%). Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners.

Despite the great efforts to assure quality in higher education institutions, the ambiguity of its related concepts and requirements constitute a big challenge when trying to implement it as an automated information system. The present work introduces a framework for an automated information system that manages the quality assurance in higher educations institutions. The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions. In addition, the proposed system helps all higher education stockholders to handle and monitor their tasks. Moreover, it aims to help the quality assurance center in a higher education institution to apply its qualitys standards, and to make sure that they are being maintained and enhanced. This information system contains a core module and 17 sub-modules, which are described in this paper.

An automated information system to ensure quality in higher education institutions

Quality assurance in reverse logistics supply chain of demolition waste: A systematic literature review.

Despite great efforts to assure quality in higher education institutions, the ambiguity of its related concepts and requirements constitute a big challenge when trying to implement it as an intelligent information system. The present work introduces a framework for an intelligent information system that manages the quality assurance in higher education's institutions. The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions. In addition, the proposed system helps all higher education stockholders to handle and monitor their tasks. Moreover, it aims to help the quality assurance units in a higher education institution to apply their quality's standards and to make sure that they are being maintained and enhanced. This information system contains a core module and 18 sub-modules, which are described in detail. Finally, the characteristics and components of each of these sub-modules are also discussed.

Intelligent information system to ensure quality in higher education institutions, towards an automated e-university

Standardization is defined as an activity that gives rise to solutions for repetitive application to problems in various disciplines Generally, the activity constitudes the process of estab‐ lishing (determining, formulating, and issuing) and implementing standards Thus, stand‐ ards are the perfect result of a standardization activity and inside the context of quality systems consist of quality documents or documents related to the quality system High lev‐ els of quality are important to accomplish Company business objectives Quality, a source of competitive benefit, should stay a symbol of Company products and services High quality is not an additional value; it is an important elemantary necessity Each employee in all or‐ ganizational units is responsible for guaranteeing that their work processes are effective and continually getting better Top management should provide the training and an appropriate motivating environment to support teamwork both inside and across organizational units for employees to advance processes Ultimately, everyone in an institution is responsible for the quality of its products and services An institution in the role of a sponsor of clinical tri‐ als can best achieve its business objectives by establishing and managing robust quality sys‐ tems with their integral quality documents including standard operating procedures (SOPs) (Manghani, K 2011) The Quality Management system must evolve by trial and error, with enlarging experience, by group discussions and with changing understanding In the begin‐ ning, attention will be focused on basic operational SOPs, afterwards moving to record keeping (as more and more SOPs are issued) and filling gaps as practice admits missing links in the chain of Quality Assurance Essentially problems will turn up One way to react to them is to talk with people in other laboratories who have faced similar problems It

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Standard Operating Procedures (What Are They Good For

It is mandatory for sponsors of clinical trials and contract research organizations alike to establish, manage and monitor their quality control and quality assurance systems and their integral standard operating procedures and other quality documents to provide high-quality products and services to fully satisfy customer needs and expectations. Quality control and quality assurance systems together constitute the key quality systems. Quality control and quality assurance are parts of quality management. Quality control is focused on fulfilling quality requirements, whereas quality assurance is focused on providing confidence that quality requirements are fulfilled. The quality systems must be commensurate with the Company business objectives and business model. Top management commitment and its active involvement are critical in order to ensure at all times the adequacy, suitability, effectiveness and efficiency of the quality systems. Effective and efficient quality systems can promote timely registration of drugs by eliminating waste and the need for rework with overall financial and social benefits to the Company.

Kishu Manghani

Papers

Quality assurance: Importance of systems and standard operating procedures