There has been increasing evidence in recent years that research in life sciences is lacking in reproducibility and data quality. This raises the need for effective systems to improve data integrity in the evolving non-GxP research environment. Reproducibility is a defining principle of scientific research, and broadly refers to the ability of researchers, other than the original researchers, to achieve the same findings using the same data and analysis data reproducibility is key to the reinforcement and credibility of scientific evidence. All results should be replicable by different investigators in varied geographical settings, using independent data, instruments, and analytical methods.
Some examples:
- In 2022 there were 11 Federal Register notices with ORI findings of research misconduct that involved Public Health Service support or funding. These cases included falsified data submitted in National Institutes of Health grant applications and PHS-supported publications. These cases resulted debarment periods of up to four years and supervision periods of up to 12 years.
- Novartis “data manipulation” involving its Zolgensma gene therapy
- Leen Kawas Resigned as CEO of Athira in 2021 following an investigation into her doctoral work.
Without a doubt it is critical to build a quality culture within our research organizations. Through educating our scientific staff we can continue to innovate and discover new pathways, new drugs and new treatments. Efficient processes enhance research effectiveness and lead to scientific discoveries. Data integrity supports good science, drug safety, products and treatment development for patients and customers. While this looks similar in research as in later phases there are 4 primary pillars:
- Train researchers on basic documentation processes and good scientific practices to ensure data integrity and quality. Targeted training should be added on new guidelines, processes and regulations applied to their specific activities.
- Empower for change and to speak up
- Incentives for Behaviours Which Support Research Quality
- Promote a Positive Error Culture
I’m a huge fan of the EQIPD approach:
- Bespalov, A., Bernard, R., Gilis, A., Gerlach, B., Guillén, J., Castagné, V., Lefevre, I. A., Ducrey, F., Monk, L., Bongiovanni, S., Altevogt, B., Arroyo-Araujo, M., Bikovski, L., Bruin, N. de, Castaños-Vélez, E., Dityatev, A., Emmerich, C. H., Fares, R., Ferland-Beckham, C., … Steckler, T. (2021, May 24). Introduction to the EQIPD Quality System. eLife. https://elifesciences.org/articles/63294
Investigations of a Dog 