Assuring Trust in a Converging Life Sciences Ecosystem: The Emerging Role of Quality Assurance

4 Feb 2019
by Chirajeet Sengupta, Nitish Mittal

The life sciences industry is facing an inflection point. While patients and consumers have a fundamental trust deficit for a variety of reasons (adverse events, pricing, drug recalls, slow drug development efforts, and GxP compliance), healthcare and life sciences entities are converging (payers and providers coming together, Pharmacy Benefit Managers (PBMs) being disintermediated, and pharmaceutical firms collaborating with payers and providers). The healthcare and life sciences ecosystem is evolving and simplifying around patients as the core constituent. This change has a number of implications for stakeholders, particularly life sciences firms, which now need to interact closely and work collaboratively with different parts of the ecosystem to drive enhanced value through care outcomes and cost efficiency.

The primary determinants of success in this journey are driving patient outcomes and building trust within the broader ecosystem. Therefore, the orientation has to be adjusted to focus on improving care outcomes for patients (both improved healthcare and a superior experience) and business outcomes for other ecosystem participants (streamlining healthcare costs and improving access to care).

Owing to these changes, the traditional QA function in life sciences is evolving. It has been characterized by a siloed approach built on disparate platforms, fragmented technology stacks, and varying value approaches. But as life sciences firms pivot to the B2C model and value-based care positioning, the QA function will have to change to support a leaner and more flexible approach. In this whitepaper, we focus on the Four Es of the new care business model and their impact on enterprise QA:

  • Enabling the data ecosystem
  • Elevating R&D and clinical trials
  • Engaging patient communities
  • Enhancing drug quality and safety

For the QA function to evolve, it essentially needs to progress from a siloed structure to an orchestrator. The whitepaper also explores what is needed to build this future model of QA with the help of a set of illustrative use cases within the life sciences industry focused on the data ecosystem, clinical trials, patient engagement, and drug quality and safety (pharmacovigilance). It also focuses on the characteristics of a best-in-class QA platform for life sciences and the evolving role of QA in the future of life sciences focused on the ecosystem, domain, and platform tenets.


Application Services

Life Sciences IT Services (ITS)


Page Count: 19