Clinical Data and Integration Management: Discussing the Evolving Role of Data Managers

30th August 2016 (Last Updated July 18th, 2018 09:50)

Kevin Douglass, Associate Director, Daiichi Sankyo, draws a spotlight on a roundtable he chaired at Arena's 2016 Clinical Data and Integration Management conference

Clinical Data and Integration Management: Discussing the Evolving Role of Data Managers

The conference was designed to “offer different perspectives on the current key challenges of the industry – data capture, utilization, integration and visualization as well as to provide insight into innovative and alternative solutions by rethinking your current tools”.

The presentations, case studies, panel discussions, roundtables, and informal discussions demonstrated how radically our industry is being transformed by innovative technological advancements and cross-industry collaboration.  Innovative approaches for Data Analytics/Visualizations, eSource, Data Standardization/Integration were just a few of the many interesting topics - as well as a couple of topics on the regulatory compliance challenges associated with the changing Drug Development landscape.           

The transformation is enabling dramatic improvements in Clinical Trial Processes and consequently changing many of the roles, especially the Data Manager.  Patrick Zbyszewski’s presentation titled, “Analyzing Current Responsibilities and Skill Sets of Data Managers to Unravel Future Requirements to Ensure your Team is Prepared for Evolving Market Needs” was thought-provoking and focused specifically on the transition from Data Manager to Data Scientist.

Our roundtable was designed to look more closely at the changing Data Manager role and to share perspectives.  We brainstormed the new role and captured the responses to the following three questions on a flip chart.

  • What’s driving the changes?
  • What are the new capabilities/skill sets?
  • How do we enable the transition for Data Managers?

Listed below are the results:

What are the drivers?

  1. Evolving Technology (e.g., EDC, eSource, data integration)
  2. Complexity of Studies (e.g., Adaptive Designs &Immuno-Oncology)
  3. Time and Cost Pressures
  4. Industry Collaboration (e.g., CTTI, TransCelerate, FDA/NIH)
  5. Evolving Standards (e.g., CDISC)
  6. Risk-based Approaches (e.g., RBM)
  7. Regulatory Guidance/Oversight
  8. Increased Outsourcing

What are the new capabilities?

  1. Technical Skills
  2. Drug Development Process (holistic view)
  3. Data Integration and Standardization
  4. Therapeutic Area Expertise
  5. Strategic Thinking
  6. Interpersonal Skills (e.g., listening, influencing, relationship management)
  7. Analytical Skills & Problem Solving
  8. Project & Vendor Management
  9. Collaboration & Teamwork
  10. Continuous Improvement & Change Management
  11. Quality/Inspection Readiness
  12. Risk Management

How can we build the new capabilities?

  1. Set Clear Expectations (from Top -> Down)
  2. Hold People Accountable, but Provide Support (e.g., training, coaching, tools)
  3. Develop/Update Competency Model (CM)
  4. Leverage CM for Recruiting, Training, & Performance Management
  5. Attend Conferences, Webinars, and White Papers
  6. Participate in Conferences, Committees, & Working Groups
  7. Lead/Participate in Process Improvement Efforts
  8. Implement Job Shadowing & Rotations
  9. Participate in Audits and Inspections

As we all know, change is inevitable – and being able to react quickly, or even better - to leverage opportunities associated with innovative technology provides competitive advantage.

If you are a Team Leader in Data Management (e.g., Department Head) who needs to transition your team members to new roles/capabilities (so you can initiate change rather than react to it), you can get started immediately.  Listed below is one approach.

  1. Define the “Future State” – create a Competency Model by defining the experience and skills that are essential for future success (you can use the capabilities listed above as a starting point).
  2. Conduct a Gap Analysis - assess the experience and skills of your team members relative to the Future State (this is the “Current State”)
  3. Define and Implement Strategies to get from the Current State to the Future State (this is obviously more easy to say than do, but you can use some of the ideas listed above as a starting point).

If you're a Data Manager, you can follow a similar process – to identify and build the skills that will promote future success.

 

 

Many thanks to Charles Bunn, Charles Johnson, Rob Altman, and Yuan Chen for an interesting and enlightening discussion – and a number of ideas I can take back to my team.