The strong foundation of credibility leads to incredible scientific advancements. However, today’s scientific community is still struggling with data reproducibility, contamination, and availability of good resources required for their biomedical research. As a matter of fact, different self-correcting mechanisms can be implemented for good data reproducibility, which is entirely dependent upon the ability of a researcher to reproduce the findings that are comparable to already published reports. This can further be helpful to authenticate existing data, further leading to better advancements. One such recognized scientist from Stanford Medical Research has pinpointed further that the importance of data reproducibility cannot be ensured with data correctness but it is very crucial to gain complete transparency about the method and conclusion.
So in general, scientists should be able to repeat the experiment to get the same data reproducibility at any point in time; in order to arrive at a similar conclusion. And that should be the motif of data validation. However, in reality, all the scientific findings in medical research cannot be really reproduced as well as compared; further putting a larger burden in the context of time, money and other resources. Further to which, the need of an hour is to spread awareness about the latest research, data reproducibility and certain precautions that need to be undertaken to improve data reproducibility and innovation in life sciences.
In this regard, we have come up with some predominant factors that are required to be reviewed; in order to increase outcome in the form of data reproducibility.
What exactly is data reproducibility?
Although the term “lack of reproducibility” is being commonly used in the scientific world, it is rather an umbrella term that accommodates several factors. Accordingly, the American Society for Cell Biology has attempted to elaborate the term more intrinsically through the identification of different facets. The discussion involved following terms, like
Direct replication of data: – When the data obtained are an exact duplication of previously published reports, using similar experimental design and conditions.
Analytic Replication of data: – This has been designed to reproduce a number of scientific investigations through the reanalysis of the original data set.
Systemic Replication: – This can be noted as the attempt to reproduce multiple published data during variable experimental conditions.
Conceptual Replications: – In this case, the data validity is estimated using a variable set of experimental conditions.
Factors contributing to lack of reproducibility
Since the failure of reproducing the data requires a lot of troubleshooting as well as back calculation; there are multiple issues that are required to be overcome to minimize a problem. These shortcomings can be noted as:
- Absence of methodological data, published work as well as research material: – To be able to understand and authenticate data it is important to have access to some reference material as a key.
- Use of cross-contaminated, as well as over-passaged cell lines: – Reproducibility, can further be complicated or made invalid through the use of substantial quality of primary cell lines. For example, if the supplier of cell lines is not authorized to offer cells so as per guidelines proposed by ISO as well as GMP guidelines; then further research and advancements is greatly affected.
- Poor research practice and experimental design
Among many practices and published data; poorly available scientific data and non-manageable experimental design is the pre-requisite.
Thus, data accuracy, as well as result reproducibility, is some of the essential components of robust as well as credible research output. The predominant factors that have been contributed in the current write up are to be nurtured through a number of recommendations and guidelines; in order to overcome the challenges that can be faced in their practical implementations. The team Kosheeka, being India’s premier primary cell supplier is entitled to offer the better quality of cells that can be helpful in improving research practices and better credibility of scientific data.