Solving real-world problems with real-world data (RWD)

How RWD and technology can help the life sciences industry re-invent clinical development

The move from fee-for-service reimbursement models to value-based pricing and access is changing the way the healthcare industry does business. To succeed, organizations must harness the power of real-world data (RWD), data sciences and artificial intelligence (AI) to deliver actionable insights at the point of decision-making. In life sciences, there are some early signs of how RWD and AI can help improve efficiency, lower costs and ultimately result in better outcomes for patients.

Shortening timelines, reducing costs in clinical trials
Failure to inform eligibility criteria with RWD during study design often delays study completion and may ultimately result in a product label that is too narrowly defined. This mismatch can negatively affect recruitment and can cause costly amendments and delays. One study found that 57% of protocols had at least one amendment, and nearly half of these amendments were avoidable. The median cost to implement an amendment could be as much as $535,000 for a phase III protocol.  At a portfolio level this is not sustainable.  
Enabling and scaling the utilization of RWD and the analytical tools to unlock relevant insights offers the potential to identify risk and improve performance at the study level, the clinical program level and product level across the lifecycle of development and commercialization. 
Bringing medications to market more efficiently
The industry and governments are beginning to embrace the potential of using Real World Evidence to bring medications to market. The 21st Century Cures Act, signed into law in 2016, requires the Food and Drug Administration (FDA) to establish a program to evaluate RWE as a means of evaluating new indications for approved medicines and fulfilling post-licensing commitments. The FDA is just beginning to realize the potential of using RWE to make this process more efficient.  
For example, in 2019, the FDA approved Pfizer’s Ibrance® (palbociclib) in combination with endocrine therapy for hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative advanced or metastatic breast cancer in men. The FDA used real-world tumor response and safety data from electronic health records to support a labelling claim without conducting a randomized controlled trial in that setting. This is just one example of how RWD has the potential to revolutionize how medications come to market more efficiently.
Unlocking the potential of decentralized trials
It can be difficult to recruit and engage patients in clinical trials. Fewer than 5% of American adults with cancer participate in a clinical trial. 
As patient demand and technology drive the democratization of healthcare, it is likely this trend will also drive changes to the clinical trial process. Decentralized trials can potentially reduce the complexity of data collection for patients and caregivers. For example, not all data collection requires an on-site visit; remote data collection through mobile devices and sensor-ware hold the promise to both reduce patient burden and assess novel endpoints that better describe a patient’s burden of illness.
It’s an exciting time to be part of the intersection of healthcare, life sciences and technology, as RWD, AI and other innovations offer new and better ways to conduct clinical trials. We can expect financial pressures and stakeholder demand to continue to drive improvements, which will help enable better throughput of important medicines.
By Rob DiCicco, PharmD
Deputy Chief Health Officer, IBM Watson Health

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