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Challenges in R&D Require Next Gen Tech in Life Sciences

Victoria Ebel, Appian
November 19, 2018

Research and Development (R&D) has always been a complex process, but it is only getting more complicated as government regulations across the globe change as well. Challenges such as rising costs, a new focus on patient centricity, and the appropriate procurement and use of real world evidence in the industry are impacting the efficiency and accuracy of R&D, and impeding innovation in life sciences.

Rising Costs: R&D costs are steadily rising due to process inefficiency. These costs are in turn diminishing potential revenues from the completed drug or medical device. To reduce costs in R&D, shorter and more cost efficient processes must be implemented. This can be done by integrating automation and information along the product development chain.

Patient Centricity: There is a new shift in life sciences toward greater patient influence. Patients are starting to influence everything from patient recruitment during clinical trials to postmarket safety management. Consumer habits are impacting the entire product lifecycle, and in turn, demanding technology that offers a more targeted and personalized experience for patients.

Real World Evidence: Using real world evidence efficiently and appropriately is crucial to engage with healthcare providers and payers throughout product development. Real world evidence supports everything from clinical trial data with actual outcomes of treatments, the development of clinical practice guidelines,confirmation of population size, and payment decisions. To improve speed and accuracy of evidence gathering, the aid of automation tools is critical.

Technology to Improve R&D

Life Sciences organizations are implementing next generation technology to innovate in the challenging new R&D environment, including:

    • Robotic Process Automation (RPA)

    • Artificial Intelligence (AI)

    • Cloud-Based Technologies and the Internet of Things (IoT)

The power of these technologies in transforming R&D are further explained in this whitepaper coauthored by Sandra Blumenrath, PhD of the Drug Information Association (DIA) and Appian's very own Stefan Prebil Industry Leader, Life Sciences.

To learn more about how Appian's offerings, such as machine learning, RPA, and cloud, can help with your R&D needs, visit our Life Sciences Resource Center.