Current guidelines and norms
Contents
ISO9001
ISO9001 is an international quality management standard to certify a generic quality system. The aim is the standardization of all processes in a given work environment to achieve customer satisfaction. This standard was launched in 1987 and has become the most accepted standard world-wide. It provides a general approach to quality control and quality assurance by focusing on the processes applied in a given organisation. All processes have to be defined, put into context, evaluated and improved according to a standardized process. The ultimate goal is the customer satisfaction which must also be evaluated. This general approach for achieving high quality standards is suitable for organisations with standardized processes, defined customers and no special quality requirements for a given environment. In fact, for many organisations, for example producers of medical products or automotive suppliers, additional standards apply.
Background
ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member bodies). The work of preparing International Standards is normally carried out through ISO technical committees. Each member body interested in a subject for which a technical committee has been established has the right to be represented on that committee. International organizations, governmental and non-governmental, in liaison with ISO, also take part in the work. ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of electrotechnical standardization. Launched: 1987, 2915
Procuring organizations needed a basis of contractual arrangements with their suppliers (i.e., basic requirements for a supplier to assure product quality)
Target audience
All the requirements of ISO 9001:2015 are generic and are intended to be applicable to any organization, regardless of its type or size, or the products and services it provides.
A general QMS that can be applied to all aspects of organizations (not focused on biomedical research)
Function
Establishing the ISO9001 quality management system will standardize all processes in a given environment to achieve an output (product or service) with always the same quality. For this, the organizational overall performance is continuously improved to enhance customer satisfaction which is in the center of the norm. The improvement is achieved by a systematic use of the Denim-cycle, or PDCA-cycle which works in four steps: 1. Plan, 2. Do, 3. Check, 4. Act. The documentation of the processes and the improvement of them is a universal and powerful tool to achieve always the same output and learn from the mistakes.
The downside of this approach is the requirement for detailed documentation of all actions and events which can be a challenge and too labor intensive for some environments.
Conclusion
The ISO9001 quality management system is appropriate for organisations wanting to provide products and services for their customers on a constant high level and who have the resources or can at least charge extra for the additional workload. Also, it seems to be easier adaptable in environments with standardised processes. In contrast, the system does not seem to be appropriate for organisations with high degrees of freedom in their processes, who lack resources and have very specific needs in respect for quality that cannot be defined by requirements of a specific customer.
What can be taken from it?
The ISO9001 norm follows a “process approach” meaning that all actions in an organisation should be described as processes. In short, a process describes what is the input for an action, how the action is performed and what is the output and should be documented in a way that a naïve person would be able to perform this process just with the document. Adapting just this approach of this standard can be very helpful for CF, especially for larger ones with more staff to unify processes.
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Good Laboratory practice (GLP)
Background
The Good Laboratory Practice (GLP) was established by the FDA and OECD in 1976 and 1981, respectively. It was as a reaction to an incident in a laboratory in the 1970ties submitting contradictory data to the FDA. The aim is to make documentation of experiments transparent, have clear organizational structures and responsibilities.
Target audience
The focus is on labs who perform non-clinical health and environmental safety studies upon which hazard assessments are based.
Function
GLP aims to improve the organizational process and the conditions under which non-clinical health and environmental safety studies are planned, performed, monitored, recorded, archived and reported. Working under GLP should allow rigorous and detailed documentation of experiments to ensure the quality, integrity and reliability of data on the properties and/or safety of test items concerning human health and/or the environment.
Conclusion
GLP is appropriate for research labs having the requirement to work under GLP. The system increases documentation and transparency about research data and its creation. It does not make specific requirements in respect to robustness of data and is documentation intensive.
What can be taken from it?
Documentation tailored for research environment
Links
- https://www.who.int/tdr/publications/documents/glp-handbook.pdf
- https://www.ich.org/page/efficacy-guidelines (E6 section)
EQIPD Quality System
Background
The biomedical research community (industry and academia) recognized the negative impact of lacking research rigor on the development of novel therapeutics, and the need for a comprehensive practical solution to help enhance preclinical data quality. For that reason, a project under the umbrella of the Innovative Medicine Initiative was dedicated to research data quality and to establish a quality system (QS) for research.
Target audience
The focus was on non-regulated preclinical biomedical research, however, the system can also be applied to any other natural science field.
Function
The EQIPD QS sets a standard to facilitate the generation of robust and reliable research data and thereby boost innovation. It consists of Core Requirements setting the foundation for data integrity and requiring very little documentation, except for the experiment itself. It also makes specific requirements for experiments intending a formal knowledge-claim. The system has a tailored approach for core facilities which includes results from the Q-CoFa project.
Conclusion
The EQIPD QS is appropriate for research units with a focus on data quality and integrity. It requires little documentation and due to its specific focus on research cannot be applied to any environment.
What can be taken from it?
The EQIPD quality system describes aspects to protect against research biases that is not covered by any other systematic approach and could be seen helpful for most CFs. The tools and resources provided by this approach can be adapted on an “as-you-need-basis” for specific gaps within a research unit.
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Premier
Background
PREMIER stands for Predictiveness and Robustness through Modular Improvement of Experimental Research and was developed at the Institute for Experimental Pharmacology at the Charité – University Clinic Berlin. The group by Prof. Dirnagl is experienced in establishing quality procedures within academic research units and found that ISO9001 is not appropriate for such research units. Therefore, the research unit created their own quality system.
Target audience
Design, conduct, analysis and reporting of experiments in biomedical research.
Function
PREMIER is a conceptual framework of a modular QM system with low implementation threshold for research groups, departments or even institutions. It helps them to systematically improve the quality of their academic preclinical biomedical research. PREMIER provides modules (12 in total) with minimum requirements that can be adapted to the needs and resources of any organization / laboratory.
PREMIER is designed both as a modular quality tool with four main building blocks: 1) Managing (Governance), 2) Planning and Implementing (Key Processes), 3) Supporting (Support Processes), 4) Measuring and Improving (Continuous Improvement). The implementation of all four building blocks renders the PREMIER a QM system.
Conclusion
PREMIER is a comprehensive quality system dedicated for research units. It describes the different aspects and focuses on data quality.
What can be taken from it?
The modular approach of the Premier System allows the easy and specific retrieval of information to tackle issues within a research lab. The PREMIER “House” provides an overview and easy access to the different topics.
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The FAIR Guiding Principles
Background
The FAIR Data Principles were drafted at a Lorentz Center workshop in Leiden in the Netherlands in 2015. These principles for data management and stewardship guidance to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. Their emphasis is on the meta data accompanying the experimental data for computational systems with none or minimal human intervention.
Target audience
The FAIR Data Principles apply to any scholarly data.
Function
The application of these four foundational principles—Findability, Accessibility, Interoperability, and Reusability— shall ensure that research data are useable for their lifetime by any person having access to the data. The four principles are subdivided into additional requirements describing several features applying to any data set.
Conclusion
The FAIR data principles provide an easy and important guidance on how to describe research data. They are important for any research lab and solely focus on the reusability of research data.
What can be taken from it?
Any of the guiding principles to make research data usable in the future. However, due to the specialisation of CF, it might be possible to see the “Interoperability” and “Accessibility” of research data as a focus for CF. For example, if the raw data are stored in a special data format that requires a unique software from a manufacturer, the CF could take over the responsibility to keep the different software versions available. This will allow accessibility of raw data in the future even if the program is not available anymore in the research unit or from the manufacturer.
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TOP-guidelines
Background
The Guidelines for Transparency and Openness Promotion (TOP) in Journal Policies and Practices which are published by the Center for Open Science (COS) to promote openness in science, thereby improving reproducibility.
Target audience
Research data aimed to be published.
Function
The guidelines have a focus on the publication of research data by requesting full transparency about the research data and the standards that were applied to it. The important elements are the correct and comprehensiveness of the citations, a detailed description of the technical protocols as well as preregistration of the experiments. Especially the latter is in the focus of the Center for Open Science since the preregistration is often considered an effective and important tool to prevent selective publishing. Three levels are described for each of the eight points of these guidelines. This provides a good idea on what is considered as best practice when reporting research data in the sense of these principles.
Conclusion
The TOP guidelines are relevant for academic research institutions wanting to publish their work. These guidelines are less relevant for groups performing applied research and consider to claim an intellectual property on their research finding.
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ALCOAplus
Background
ALCOAplus is considered the industry standard for Good Documentation Practice (GDocP) in research laboratories. Originated from FDA regulations and well established by the WHO, who described it in their guiding principles in 2016.
Target audience
Any researcher who is performing experiments.
Function
Personnel should follow these principles for both paper records and electronic records in order to assure data integrity. These principles require that documentation has the characteristics of being Attributable, Legible, Contemporaneously recorded, Original and Accurate (referred to as ALCOA). These five attributes are often supplemented with Complete, Consistent, Endurable and Available.
Conclusion
The nine attributes of ALCOAplus provide general guidance for researchers which should be used for every experiment, hence, they build the foundation for any research data record.
What can be taken from it?
Any of the guiding principles to make research transparent is useful. Depending on the technical preconditions, it could be seen a responsibility of the CF to ensure that all raw data files are time stamped. But there will also be many occasions, were this is given by the software or maybe this is the full responsibility of the user of the CF in which case all these guiding principles should be communicated.
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