How robust are preclinical data and how biased is research?
Recent publications showed some worrying results about the quality in research and point towards a major issue in the scientific field: The lack of being able to reproduce research data. This issue seems to be so prominent that the phrase “Reproducibility Crisis” came up because 50 -90% of data could not be reproduced. Interestingly, according to a survey published in Nature shows that researchers are aware!
In summary, it looks like there is a huge problem of biased research in different scientific areas. Various solutions are discussed to improve data quality and integrity, but unlike in many other professions and private life, a comprehensive evaluation of bias in research is missing.
PAASPort: It is possible to judge bias in research!
Scientists at PAASP US can apply a unique evaluation protocol which was named PAASPort to identify potential bias in research.
This tool allows the identification of many -if not all- risk factors leading to biased research data. However, also protection mechanisms are identified which are used by the researchers to prevent such bias. Like this it is possible to create a comprehensive picture about the quality of research data by a particular lab.
Therefore, The PAASPort consists of a three step process which is shown in the image below: 1. Planning, 2. On-site Visit and 3. Feedback. During all these phases the PAASPort requires to maintain close discussions with researchers about the processes
Who profits when using the PAASPort?
The PAASPort is optimised for preclinical research and many institutions can profit by using the PAASPort.
Besides the PAASPort, PAASP US offers also other services, several of them in collaboration with specialists in their respective fields.
contact us at
Global PAASP network
The PAASP US, LLC is part of the global PAASP network with several partners in Europe.
For more information regarding data quality, good research practices and other resources, visit the central web page: