Poor quality data is an issue in many research fields — all too often, results carried out in one organisation cannot be replicated elsewhere, and it is not always clear why. In medical research, consequences include poor decision-making resulting in higher failure rates and longer drug development times.
Their goal was to deliver simple recommendations to facilitate data quality without impacting innovation. The field of preclinical cancer research, for instance, is particularly notorious for its difficulties in reproducing results, and this issue with robustness has a knock-on effect on the entire drug development pipeline.
The lack of rigour leads to wasted resources and finances, both public and private, including the wastage of animal life in non-reproducible studies both in vitro and in vivo , which raises ethical concerns.
Addressing the problem would lead to a reduction in the number of animals used in experiments and would possibly lower the extremely high failure rate of drug development trials. EQIPD was established to address this problem, with the goal of establishing a standardised quality system for preclinical research that could be rolled out across a wide range of laboratory settings.
While guidelines about reporting on preclinical studies exist, there was no existing guidance for researchers regarding preclinical research design, conduct or analysis. The project examined the variables that were most likely to cause issues with preclinical data quality in in vivo studies by combing through the scientific literature, and then set about creating a suite of guidelines — and an entire quality system — that laboratories should adhere to in order to ensure that they produce robust and reproducible results.
