Building Better Insights: Enabling Real-World Data-Driven Drug Development

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Art Brown and Real-World Data
Read more about author Art Brown.

By 2025, the drug discovery market is expected to reach $71 billion. While recent growth in the market was largely influenced by the COVID-19 pandemic and the need for vaccinations, a need for more robust data and analytics has also contributed to the industry’s rapid development.

Developing new drugs involves substantial money and time – and uncertainty too. The average journey to bring a new drug to market takes a minimum of 10 years, with the research and development (R&D) behind each successful drug costing an average of $2.5 billion. Life sciences organizations can use existing data sources like real-world data (RWD) to decrease time spent in the R&D stage, bringing drugs to market faster. Yet, despite RWD’s benefits, my company’s recent report found that nearly 50% of life sciences organizations remain unconnected to RWD sources.

RWD and real-world evidence (RWE) enable life sciences organizations to build better insights and achieve better drug outcomes, lower risk, and reduced costs. Organizations continuing to opt out risk being left behind in a highly competitive, fast-growing space.

Real-World Data and Real-World Evidence Adoption

Regulators have already begun to recognize the value of RWD sources. The FDA has a long history of using RWD and RWE to monitor and evaluate the post-market safety of approved drugs. 

Like the FDA, life science organizations must prioritize intelligent analytics to stay on the cutting edge of the life sciences industry. Currently, just over 30% of life sciences organizations connect with RWD to power drug development, according to the above-mentioned report. Midsize to enterprise organizations tend to use RWD the most because they have more mature internal processes. Smaller companies are less likely to leverage RWD because of leaner operations, fewer products in the market, and lower case volumes. However, smaller pharma companies must consider these data sources to scale in the future.

Importance of Real-World Data and Real-World Evidence

RWD connects research and practice in healthcare by allowing drug developers to more effectively study how a broad group of patients use and respond to an approved drug to understand how patient characteristics and behaviors affect health outcomes. That data informs decisions for care. RWD also helps drug developers:

  • Uncover crucial similarities – like side effects – across a selection of drugs
  • Design and conduct better clinical trials and studies
  • Add another data layer supporting faster risk detection and reduced signal noise
  • Understand how different patient characteristics and behaviors affect health outcomes
  • Find additional uses for existing drugs

Drug developers collect RWD from a variety of sources:      

  • Claims and billing activities: Information about patient prescribing patterns, healthcare services, and population coverage
  • Electronic health records: Digital patient charts including data about diagnoses, treatment plans, immunization dates, and more
  • Patient-generated data: Real-time information provided by patients from mobile devices and wearables
  • Product and disease registries: Data collections defined by a specific condition, disease, or exposure
  • Social media: Patient posts on forums or social media platforms featuring unsolicited, first-hand data about a treatment or drug

When they apply analytic techniques to RWD sources, drug developers generate RWE – the clinical evidence about the usage and potential benefits or risks of a drug. RWE assists drug developers in investigating clinical research and creating more comprehensive hypotheses from patient patterns. 

RWE also offers life science organizations a financial boost, with its analytics generating more than $300 million YOY for the world’s top 20 pharma companies over the next two to four years. Imagine that value across the entire life sciences ecosystem. 


The RWD and RWE market will be worth $2.3 billion by 2026. Life sciences organizations – regardless of size – cannot afford to ignore the value of enriching their data with RWE. When organizations recognize and adopt RWD and RWE, they gain access to a rich existing data source that strengthens drug discovery and development efforts.