The data landscape is evolving rapidly, and some pharmaceutical companies are taking strong positions to gain privileged and preferential access to data. Oncology is at the forefront of this movement and is heralding a wave of activity across other therapy areas. Looking forward, it will be increasingly important for pharma companies to employ ingenious strategies to access data already existing in the healthcare environment, moving away from solely building and owning data sets. These new approaches will bring significant new opportunities and help companies to further differentiate their medicines from competitors and accelerate their products to market.
The Data Landscape Is Evolving
Data is increasingly prevalent. Genomic, clinical, and behavioral data have all become progressively collected, codified, and digitized into electronic medical records (EMRs), driven by advances in technology and government policy (e.g., Meaningful Use Act in the U.S.).
Data analytics capabilities are advancing rapidly. Increased processing power means larger and more complex data sets can be analyzed and has enabled a shift from statistical to machine learning analytics, driving improvements in prediction and pattern recognition capabilities. On top of this, natural language processing is enabling codification of free-form clinical text for use in analysis.
External companies are innovating to provide new ways for pharma to access data. Data can now be accessed in an increasingly cost-effective way beyond traditional trials and registries, with external players employing innovative business models, such as data as a service and direct-to-consumer diagnostics. Additionally, companies such as Nebula Genomics are emerging, offering patient-owned blockchain genomic data, which, in the future, could change how patient data is accessed altogether.
Real-world evidence (RWE) from routine clinical care is increasingly being used in regulatory settings. Regulatory bodies are becoming more comfortable with innovative applications such as external and synthetic control arms to supplement placebo or current standard of care arms in randomized clinical trials.
Pharmaceutical companies are taking a stake in the data ecosystem and a lot of corporate activity is being seen in the space. The Roche and FlatIron acquisition and the strategic partnership between GSK and 23andMe are examples of activities creating more privileged access to data. Pharma’s influence could irreversibly change the direction that data holders take, meaning outsiders may lose the freedom to fully access the data they need (for example, GSK’s influence on 23andMe post Parkinson’s collaboration, leading to the latter’s partnership with the Michael J. Fox Foundation).
Forming A Successful Data Access Strategy
For pharmaceutical companies, it is important to consider multiple areas when designing a data access strategy. The key question to answer is what are our priority use cases? Answers can range from discovering new targets to differentiating in-line medicines, and these answers are vital to inform follow- on questions. Next, data types and analytics required need to be considered for each use case, i.e., “what are the right data types for our use cases?” and “how will we gain insights from this data?” Lastly, the current situation needs to be assessed, i.e., “what capabilities/data do we currently have?” and “how will we access this data and/or analytics capability?”
Our work analyzing recent developments and discussing them with industry partners has led us to identify four distinct approaches that forward-thinking companies are employing to enhance their development activities. Each of these approaches leverages valuable data already in the healthcare ecosystem, but in vastly different ways. The approach a company selects will greatly impact how it brings its drugs to market and, conceptually, can be used by ambitious companies as aspirational targets to base future strategies around.
Approaches Applied Across The Development Life Cycle
Whichever approach is taken, all of them can be successful, but in different ways. Moving through the development cycle, each approach has different benefits, and a company is not bound to one. In fact, companies can switch between approaches, depending on the development stage they are at, the market they are moving into, and the indication or type of medicine they have.
Drug Discovery And Early Development
Mid- To Late-Stage Clinical Development
Market Opportunity Optimization
We are in the middle of a paradigm shift in the access, management, and utilization of healthcare data across the pharmaceutical value chain. Keeping ahead will hinge upon being flexible but targeted in development activities, paying close attention to competitors’ moves, understanding the growing data marketplace, and identifying emerging trends. Achieving the maximum value from the opportunities presented will depend on rapidly selecting and executing the most relevant approach and proactively shaping the landscape through deals and partnerships.
Jamie Cartland and Philip Winkworth are life sciences experts at PA Consulting