Managing R&D Data in a Virtual World

Pharmaceutical and biotech companies are moving from centralized organizations to a virtual network of contract research organizations (CROs), academic partners, internal labs, and government agencies. Access to real-world patient data, supporting precision or stratified drug discovery, and the general trend to externalize services all require sophisticated data management that enables the right mix of access and security. This article will look at the different research and development (R&D) processes in life science organizations where data is central to collaboration, and how it needs to be consistently captured, integrated, managed, tracked, and analyzed. Technical considerations for supporting this changing environment will also be explored and, as pharmaceutical companies are already in this increasingly complex network of data and partners, this will be done in a pragmatic way.

In the past we were one …
The glory days of pharmaceutical double-digit growth and megamergers resulted in huge organizations spanning the globe with billion-dollar budgets dedicated to R&D. The majority of the work was carried out in-house to theoretically protect critical IP around lead compounds, driving innovation from an internal perspective and maintaining oversight and control via portfolio management. The concept of a pharmaceutical company’s data going outside its firewall was taboo to these security- and IP-conscious organizations. Departments were relatively siloed and were often following a best-of-breed or internal development approach to informatics that enabled them to optimize their departmental efficiency and results. However, this hampered technology transfer between groups, which was often based on documents, presentations, or high-level summary data with limited ability to share the context of data and higher-level “corporate knowledge.” Data management was primarily designed to support IP compliance and regulatory filing, with results reuse and collaboration a secondary task handled by adjunct knowledge management groups. Some external specialists, biotech partnering, and contract researchers were used, but the drug portfolio was essentially internally driven and owned.

Well-documented pressures on the life science industry have forced a major rethinking of the pharmaceutical model. The pace of change toward pharmaceutical outsourcing has been startling in the past few years, and the business is expected to grow to $65 billion by 2018, fueled by a compound annual growth rate of nearly 15 percent.1 This has transformed the internal focus of these organizations to be much more development-, clinical- and marketing-centric and has triggered significant reduction in discovery and research departments across the board. Many noncore capabilities have been outsourced, ranging from individual groups such as bioanalysis, pharmacokinetics, synthetic chemistry and pharmacology right up to entire functions such as “basic research” and preclinical development. The drive for innovation is increasingly coming from partnerships and shared risk models for new medically active entities (biologic, chemical, technology). Furthermore, the internal IT groups of life science organizations have also been hit by budget constraints and are having to support a very different environment in which data is shared between external partners as part of this outsourcing and externalization drive. This creates significant problems in how to manage and maintain different levels of compliance, audit, and security to support varying levels of interaction with third parties—all partners are not created equal. The types of collaboration are also evolving, but some real-world examples are given below:

  • Fee for Service—where compound pharmacology is assessed by an external lab or academic center and supplied back as simple files, but there is no flow of data from the company to the partner. These types of interactions have been commonplace for many years
  • Virtualized R&D— where minimal in-house labs exist and extensive collaboration is carried out with CROs and partners to provide the full spectrum of research, development, clinical, and manufacturing services. There are many examples where elements of the R&D process are outsourced, but a good example of a more “virtualized organization” is Shire plc.2
  • Hospital Collaborations—clinical, observational, and pharmacovigilance studies conducted via close hospital collaborations. These collaborations require more advanced systems for near real-time data sharing and to protect patient privacy and follow ethical review board procedures. Various large pharmaceutical companies are starting to “embed” themselves into frontline clinically driven organizations (hospitals, health institutes, etc.), such as Roche with its Translational Medicine Research Collaboration (TMRC) in New York3 and Pfizer with its centers for therapeutic innovation in various US cities.4 Here, the closeness of the R&D organization with the health care provider organizations is expected to provide much better “real-world exposure” and therefore the ability to innovate and develop new medicines faster.
  • Pre-competitive—where the sharing of data is done on a very large scale for the good of all potential interested parties. Typical examples are the sharing of clinical trials data across broad disease areas as supported by the Innovative Medicines Initiative (IMI).5 These aggregated studies include thousands of subjects and require industrialized data sharing and access addressed in projects such as eTRIKS.

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