The first full-service, independent consulting and auditing company focusing on the evaluation of data quality and practice in biomedical research.
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®.
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Research Companies
Buying research data of low quality results in tremendous waste of resources which can be avoided with a clear idea about their bias.
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Funders
Research quality assessment is a filter allowing to focus your funding on robust and high quality research with higher chances to be translatable.
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Investors
Your investment might be at risk due to biased research. At least 30% are! The PAASPort is a valuable supplement to your DD process.
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Contract researches
Having the PAASPort label identifies your research procedures as unbiased, of high quality and more valuable for your customers, giving you a competitive advantage.
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Academia
Having your research process evaluated by PAASP will show funders and industry that your research is according to industry standards.
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Biotech
Getting confirmation that your research projects are on the right track to get the next investment and working towards the next block buster.
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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Training
Creating awareness about the reproducibility crisis and training in Good Research Practice is currently the most critical aspect in research!
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Consultation
Preclinical data quality is critical to support translatability of findings and increasing the chances of successful drug candidates for clinical research.
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PAASPort®
PAASP scientist have developed a tool to identify risk factors in the research process leading to biased data. Our certificate can proof that your research is not at risk.
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Phinnex
A consortium for improving and advancing of preclinical projects by creating robust and trusted data from high-quality research labs.
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StuDySign
A helpful software tool developed by researchers at PAASP and written by experienced programmer at enso, supporting you to make your research robust.
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Statistical Analysis
With our experienced partner Arlenda, PAASP is able to provide the support in complex statistical questions for study design and analysis.
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