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 have developed 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®.
What does PAASP do?
PAASP sees itself as the pioneer in evaluating research practices with the PAASPort® tool. However, our experts also aim to create awareness among researchers and our educational programs provide solutions on how to make research more robust.
Besides the PAASPort®, PAASP offers also other services, several of them in collaboration with specialists in their respective fields.
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