The pharmaceutical industry, as well as the advance of biomedical science, depend on robust data and scientific rigor for efficient decision making, patent strength and reduced time-to-market, which in turn determines knowledge gain and availability of new treatments to patients. Increasing awareness of shortcomings in the robustness, rigor, and validity of research data reduce confidence in decisions on further preclinical or clinical testing and for the predictability of preclinical models.
We set out to propose simple, sustainable solutions to facilitate data quality without impacting innovation and freedom of research. We pooled resources from academia and industry to develop this action in Neuroscience and Safety, but with an ambition to have broader applicability.
We have used complementary approaches to [1] identify those factors associated with increased robustness, rigour and validity of in vivo research; [2] develop a quality framework for individual studies and for research groups; [3] pilot that framework; [4] refine the quality framework based on these pilot studies; and [5] put in place arrangements for the sustainability of the framework.
Conclusions of the Action: The project management WP1 guided the consortium in the timely completion of Milestones and Deliverables in fulfilment of the consortium’s contractual duties and effective dissemination and communication activities. In WP2, the evaluation of published and consortium data across three common paradigms (Irwin, EEG, OFT) was challenging due to limited reporting and study compatibility, but we highlighted specific areas for improvement, such as reporting of measures to reduce the risk of bias and specific aspects of experimental design within each paradigm. In WP3 we developed guidance for researchers working with animal experiments to increase rigour in design, conduct and analysis, based on a systematic review of existing guidelines and prospectively tested for feasibility by project partners. In WP4 we conducted multicentre studies and showed that standardisation and heterogenisation of protocols (open field), detailed definition of qualitative endpoints (Irwin), and centralized data analysis (EEG) could each reduce between lab variation. Drawing from this experience, WP5 developed a Quality System (QS) and associated tools to support scientists conducting non-regulated preclinical research. These have been released for public use and serve as a basis for building a sustainable post-funding future. WP6 have articulated governance elements for the EQIPD QS. We have gone beyond simply exploring sustainability options by creating a non-profit follow up organisation, the Guarantors of EQIPD, which will provide oversight to organisations wishing to provide EQIPD QS assessments. We developed a web-based learning environment in WP7 to learning opportunities tailored to early career researchers working in industry or academia with formal learning provided in an E-learning course and summer school. In WP8 we developed a new ontology for metadata of in vivo preclinical neuroscience experiments and have secured arrangements for data availability beyond the project. WP9 provided ethical insights to and oversight of our activities.
