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Quality Governance in Biomedical Research.

¹Janssen Pharmaceutica NV, Beerse, Belgium. agillis@its.jnj.com.

Handbook of Experimental Pharmacology

|October 20, 2019

Summary

Implementing effective research data quality governance is crucial for innovation and addressing medical needs. This guidance offers a practical, sustainable approach for nonregulated preclinical research, independent of Good Laboratory Practice (GLP) standards.

Keywords:

Change management Fit for purpose approach Quality governance Research data quality Sustainability

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Area of Science:

Biomedical Research
Data Management
Quality Assurance

Background:

High-quality research data are fundamental for informed decision-making and driving innovation to meet medical needs.
Factors influencing data quality are multifaceted, encompassing technical and cultural aspects dependent on institution and experiment types.
A robust governance mechanism is vital for understanding, monitoring, and controlling research data quality within an institution.

Purpose of the Study:

To provide practical guidance for establishing simple, effective, and sustainable quality governance for research data.
To tailor governance strategies for organizations conducting nonregulated preclinical research.
To ensure stakeholder ownership and alignment in data quality management.

Main Methods:

Developing a governance framework independent of Good Laboratory Practice (GLP) regulations.
Focusing on practical, lean, and fit-for-purpose quality management strategies.
Incorporating principles such as transparency and clear roles and responsibilities, drawing parallels with valuable aspects of GLP.

Main Results:

The proposed governance model is designed to be adaptable and sustainable for nonregulated preclinical research settings.
It emphasizes stakeholder involvement and a shared responsibility for data quality.
The approach offers an alternative to potentially overly prescriptive GLP guidelines for studies outside safety testing.

Conclusions:

Effective research data quality governance is achievable through tailored, stakeholder-owned mechanisms.
A flexible approach, independent of rigid regulatory frameworks like GLP, can better serve diverse research needs.
Implementing clear governance structures enhances data reliability, supports innovation, and ultimately contributes to addressing unmet medical needs.