Last year, Nature surveyed life sciences researchers who had published in Nature journals, and of the 480 who responded, 86 percent said poor reproducibility is a crisis in their field. An analysis of this crisis published in PLOS Biology in 2015 determined that in the United States, about $28 billion per year is spent on irreproducible preclinical research.
A study may be irreproducible due to a number of factors – human bias, poor sample management, and insufficient documentation, for example. Researchers in the field of drug discovery must take a critical look at their processes to ensure their work is reproducible.
Reproducibility applies not to results but to methodology – it means that another research team is able to reproduce a study. If researchers follow the same steps and processes, or use the same data, but cannot replicate a study, that means information is missing or corrupted in some way.
Common Deficiencies in Research Environments
When researchers are working with thousands of data points, various software, and a system of interconnected devices, opportunities for error are plentiful. Irreproducibility may be due to:
- Sample quality – Inefficient chain-of-custody procedures, inconsistent/insufficient labeling, and poor sample storage conditions can cause contamination or degradation of samples.
- Data provenance – All data points should have an audit trail that includes point of origin, methodology of collection/input, user interactions with data, and timestamps for data transfers/manipulations.
- Software information – Researchers must document all software used in their work, including versions.
- Manual manipulation – All laboratory processes and workflows should be automated, to reduce the opportunity for error. “Workarounds” that necessitate workflow stoppages or interventions are not conducive to reproducible research.
Improving Workflows and Sample Management
Simplicis has extensive experience improving processes for researchers in pharma, biopharma, agriscience, and biobanking. Our proprietary laboratory information management system, Ledger, ensures sample and data integrity throughout the workflow, and our integration experts can create customized software-to-software interfaces that allow individual components to communicate effectively.
Make sure your research is reproducible. Contact Simplicis to schedule an evaluation of your workflow.