Effects of the Emerging Pharmaceutical R & D Model on Informatics

Industry Insider

The pharmaceutical industry’s R&D process has reached a tipping point. Over the next three to five years a number of irreversible changes will force the current R&D model to undergo a dramatic transformation. To remain competitive, organizations will be forced to evolve significantly or abandon traditional approaches in favor of new R&D models.

The primary forces behind this transformation are the pressure to reduce R&D costs, higher market barriers based on payer needs for product differentiation, patent expirations, a need to balance larger trials with personalized medicine, and the growing availability of product and patient data.

Together, these and other drivers are giving rise to a number of business attributes that must be considered when reshaping the R&D model. Based on Accenture research findings, ongoing discussions with R&D chief information officers, and informatics leads from pharmaceutical companies the world over, Accenture believes that the pharmaceutical industry will need to remove existing organizational barriers in favor of a networked, virtual, and flexible approach to the R&D model. They will also need to expand their focus from solely generating products and information to delivering bundles of health care services to improve patient outcomes.

Further, Accenture emphasizes that to realize the full potential of this new networked, virtual, and flexible R&D model, R&D organizations will need to cope with ever-expanding volumes of relevant data crucial to the business. This imperative will require R&D and R&D informatics organizations to continue changing or radically evolve their focus and approach.

Implications for informatics
While change in the R&D model is inevitable, success in deploying it is not. In order for R&D organizations to successfully address these business imperatives, the R&D informatics organization must play a key enabling role. For R&D organizations to work effectively using the new networked approach, R&D informatics organizations need to:

• Strengthen their capabilities to support enhanced collaboration and integration, encompassing both internal and external stakeholders.
• Develop a flexible infrastructure—one that is highly secure, yet also elastic, globally present and cost-effective.
• Facilitate the incorporation of new sources of data—from partners, providers, clinical research organizations, patients and third-party sources–into an improved decision making mode.
• Enhance their capabilities to assimilate and interpret a wide array of inputs, ranging from sentiment monitoring and social networks to fully digital operational data that is integrated and accessible.

In addition to the evolutionary steps highlighted above, a set of revolutionary approaches are destined to emerge as companies face the reality that the historic methodology of focusing holistically on drug discovery through development, supported by internal processes, networks, platforms, and infrastructures will no longer be sustainable.

A crucial capability
The capacity to deal effectively with massive amounts of data is central to realizing the promise of the new R&D model. Enter the argument for data into insights, or D2i: the ability to convert data into decision-making, product-shaping, market/customer-influencing insights.

In the area of R&D, pharmaceutical companies face an accelerating need to compete on the basis of analytic excellence. There is a competitive advantage for companies that can rapidly harness analytical capabilities to collaborate in new ways, like generating new insights on disease progression in order to find novel therapies or connecting disparate patient information in order to refine existing studies through adaptive trial design.

In enabling this kind of insight, D2i approaches provide pharmaceutical R&D functional groups with unprecedented power to cope with today’s torrent of information. Such power, until now, has been sorely lacking. Over the course of a product’s lifecycle, pharmaceutical companies generate terabytes of discovery and clinical data. The industry as a whole, including pharmaceutical and medical device companies, spends $3 billion to $4 billion a year on external health care data for decision support around discovery, product development, clinical trial design, safety, product launch, and sales and marketing. Yet the value generated by this expenditure has not been maximized. Companies in the industry currently lack true business-driven, extensible analytics capabilities that bring value to data.

Issue of disparity
Despite the clear value to be gained from D2i, very few of companies are aggressively exploring D2i capabilities. There are multiple reasons for this disparity in companies’ investment strategies. The business case for making this investment, and the value to be realized, are not yet well understood. Cost pressures also pose challenges to expand beyond the current capability base, particularly if the new capabilities required are considered speculative in nature. Meanwhile, current capabilities will continue to require real work and focus, as well as continued funding. In some cases, such as the integration of two organizations after a merger, this traditional work will take on a sense of urgency—and potential precedence as area for investment.

Over the next three to five years, a clear set of industry leaders will emerge. Leading pharmaceutical companies will be the ones that have acquired the D2i capabilities necessary to successfully execute the strategy of the transformed R&D model. Today, only a few large players are investing at a level commensurate with the potential value. Those who continue to lag behind—as most of the industry does today—will struggle to keep up with the fast pace of the future and with the requirements necessary to be successful.

About the Author
Arjun Bedi specializes in leading major strategic business transformation initiatives for large pharmaceutical companies.