Abstract

Management and research represent a binomial almost unknown, whose potentialities and requirements have not yet been fully exploited even if, recently, the scientific and social communities have felt the burden of producing results and data requiring at the same time reproducibility, reliability, safety and efficacy of the discoveries, as well as a profitable use of resources. A Quality Management System (QMS) could represent a valid tool for these purposes, improving the quality of the research. The research community could ask whether and how it is possible to apply this approach in a research laboratory without hindering their creativity, and what the possible benefits might be. On the other hand, an international standard for a quality management system appropriate for a research laboratory is yet to come. The choice, the design and the application of a QMS, inspired by the Good Laboratory Practices, in a research laboratory specialized on “omics” sciences, is fully described in this paper. Its application has already shown good outcomes as testified by specific metric of efficiency and effectiveness. The approach is innovative as there is no obvious requirement for research laboratories to develop and define quality objectives. The paper highlights how the QMS approach enhances the relationship with public and private sectors by increasing customer confidence and loyalty, as well as improving the overall performance of the laboratory in terms of throughput and value of research. These results encourage proposing it as a QMS model providing a new and scalable operational strategy to be applied in a research environment with the same target and even in a generic research laboratory.

Highlights

  • Generation Sequencing (NGS) technologies have dramatically changed the field of genomics and are routinely applied to a variety of functional genomics investigations including, but not restricted to, whole genome sequencing, global identification of genomic rearrangements, epigenetic modifications, single nucleotide polymorphism (SNP) discovery, transcriptome profiling and metagenomics

  • We describe the choice, the design and the application of a Quality Management System (QMS), called ReOmicS (Research Environment management system for Omics Sciences), at the Molecular Biodiversity Laboratory (MoBiLab), a Next Generation Sequencing (NGS) research infrastructure located in Bari (Italy) at the Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies of CNR (CNR-IBIOM)

  • Material and methods Considering the managerial aspects of the study, methods described are tools used in quality and organizational management, occasionally modified to be adopted for the specific use of a research laboratory, such as MoBiLab

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Summary

Introduction

Generation Sequencing (NGS) technologies have dramatically changed the field of genomics and are routinely applied to a variety of functional genomics investigations including, but not restricted to, whole genome sequencing, global identification of genomic rearrangements, epigenetic modifications, single nucleotide polymorphism (SNP) discovery, transcriptome profiling and metagenomics. Good data management, ensuring reliability and usability, needs a holistic approach tracking the process of data and metadata generation and all the different organizational aspect that, on the one hand may affect it, and on the other hand can keep it under control. This can be achieved by means of a management system focused on the quality of the results. The described experience could represent a scalable model to be applied to MoBiLab and to other research laboratories in order to ensure the highest levels of reliability, reproducibility and traceability of the results, a process that is expected to foster their potential exploitation

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