Building data analytics skills for clinical drug development quality professionals - the Data Analytics University training program

Abstract

Clinical drug development is a complex and extensive process that entails multiple stakeholders alongside patients, requires large capital expenditures and takes nearly a decade on average to complete. To ensure the correct development of this process, rigorous quality activities must be conducted to assess and guarantee the Good Clinical and Pharmacovigilance Practices (GxP) for study compliance. For about 25 years, most of these activities have been performed in the form of audits, which implies a high volume of manual work and resources in addition to being reactive by nature. Due to the limitations of this approach, together with intent to leverage new technologies in the data analytics field, a more holistic, proactive and data-driven approach needed to take place. For this to happen, quality assurance expertise needed to be complemented by the data literacy skillset. To achieve this, the Data Analytics University (DAU) was created. An in-house training program composed by two pathways that provided a framework for clinical quality staff to develop their data analytics capabilities. The first pathway covers the basics of statistics, probability and data-related terminology, while the second deepens further into the topics covered in the former followed by hands-on activities to put the knowledge to test. After successful completion of 15 DAU sessions, over 310 trained staff were able to apply their learning on data analytics and solve potential issues that might arise with a given dataset. In the near future, the DAU will be made available externally as an e-learning training program.

Advanced analytics for clinical trial quality: Commentary on ‘Can quality management drive evidence generation?’

“…Finally, an effort should be made to develop data literacy skills for QA staff, to ensure they can fully leverage data analytics tools. 7…”