PAASP Quality investment starts with data quality data

Operational Risk Management is needed by every business and basically every economic branch is covered by firms providing assessments of operational risks.

One of the very few exceptions – areas of drug discovery! For some historical reasons, preclinical discovery biology and pharmacology are largely exempt from quality control.

These areas of drug research and development are key for generating novel value in the pharmaceutical world. Insufficient quality control and associated risk assessment are among the main factors leading to financial losses in early-phase pharmaceutical investment sector and are seen as strongly contributing to declining productivity of pharma R&D over the last decades.

The PAASP GmbH -based in Heidelberg, Germany – is the first full-service consulting and auditing company that specializes in providing assessment of operational risks related to quality of research data in organizations which create value by conducting drug discovery research. PAASP (Partnership for Assessment and Accreditation of Scientific Practice) has developed a proprietary platform, called PAASPort, which is used to detect all potential sources of bias and violations of Good Research Practice during study design, conduct, data analysis, reporting and storage. PAASPort contains checklists for in vivo as well as in vitro pre-clinical studies and is designed to deliver an expert statement about the likelihood that a given set of preclinical data is robust enough to support a successful drug discovery project.

Good Research Practice certificates based on the PAASPort evaluation remain valid for three years during which PAASP provides continuous support, training and consultancy services.

Assessment of research quality by PAASP is sought-after by various stakeholders like pharmaceutical as well as biotechnology companies, contract research organizations (CROs), VCs and non-corporate investors, publishers and academic institutions, whose business model critically depends on the value of generated data in nonregulated areas of biomedical science.

For more information on PAASP and the discussion about data quality in preclinical drug discovery research, please write to, visit their website or join the LinkedIn group.

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