Connecting the Dots: Real-World Data’s Role in Transforming Healthcare

Discussion with David Urban

David Urban, a veteran in life sciences and health technology, has dedicated over two decades to leveraging real-world data (RWD) to drive innovation in healthcare. From launching vaccines at Merck to advising health tech companies, Urban has been at the forefront of integrating RWD into clinical research, drug development, and patient care. As a life sciences leader, he has also played a pivotal role in strategic partnerships and go-to-market strategies across the life sciences sector. In this article, he shares insights on how RWD has evolved, its role in addressing unmet healthcare needs, and the technologies shaping the future of the industry.

The Transformation of Real-World Data

Real-world data (RWD) has come a long way from its early days as a supplementary tool in healthcare. According to Urban, the shift from using basic data insights to integrating comprehensive, actionable information is revolutionary. “When I started at Merck 22 years ago, we were using RWD primarily to support product launches. Today, it’s a core component of understanding patient care, improving outcomes, and driving innovation”, he shared.

In its current state, RWD draws from diverse sources, including electronic health records (EHRs), patient registries, wearable devices, and even social media platforms. These data points provide insights into patient responses and treatment effectiveness in real-world settings, outside the controlled environment of clinical trials. “We’re pulling in data from mobile devices, claims, and billing records – essentially any source that helps us paint a clearer picture of how patients respond to treatments in real life”, Urban explained.

The integration of RWD into healthcare practices is no longer optional but essential. However, the challenge lies in making this data actionable. “The key is not just collecting information but connecting it into a seamless narrative that healthcare providers and researchers can use to make real-time decisions”, Urban emphasized. This transformation requires significant technological advancements and collaborative efforts across the healthcare ecosystem.

AI and Blockchain: The Future of Health Tech

Artificial intelligence (AI) and blockchain technologies are rapidly gaining traction in health tech, though Urban Urban offers a balanced view of their current and potential impact. “AI is the buzzword everyone’s excited about, but to be honest, I haven’t seen that ‘wow’ moment yet”, he remarked. The potential of AI lies in its ability to analyze vast datasets and provide actionable insights, but there’s still room for improvement in its application within the healthcare sector.

Urban highlighted how AI is being used to connect disparate data sources and predict patient outcomes. “For example, AI platforms are trying to autopopulate clinical trial data by pulling from multiple metrics, but there are gaps when it comes to integrating data from diverse sources”, he noted. Additionally, AI’s role in patient safety is gaining prominence, especially in monitoring potential drug interactions and adverse events during clinical trials.

Blockchain, on the other hand, offers a solution to one of the biggest challenges in health tech: maintaining data integrity and traceability. “We’ve overlooked the potential of blockchain”, Urban said. “It ensures that data remains tamperproof and connected across its lifecycle, which is crucial when dealing with sensitive health information”. By combining blockchain’s transparency with AI’s analytical capabilities, health tech companies can create a robust framework for innovation.

Metrics for Success in a Crowded Market

In a competitive health tech landscape, identifying and focusing on the right metrics is critical for success. Urban Urban emphasized the importance of obtaining a comprehensive, longitudinal view of patient data. “What we need is the full patient picture – starting from symptom onset, through diagnosis, treatment, and post-treatment outcomes”, he explained.

The challenge, however, lies in maintaining this longitudinal data. “I’ve worked with datasets covering over 300 million patient lives, but when it comes to long-term data – five years or more – the number drops to just 5 to 7 million”. When working with rare diseases or rare tumor types, longitudinal figures can drop to less than 100 patients, Urban revealed. This highlights the need for systems that can not only collect but also preserve long-term patient information to inform cost-benefit analyses, regulatory decisions, and treatment strategies.

Urban also pointed to the growing emphasis on patient diversity. Regulatory authorities, including the FDA, now require diversity in clinical trials to ensure treatments are effective across different demographics. “We’re finally gaining access to patients in underserved areas, but there’s still more work to be done”, he said. By prioritizing diversity and inclusion, companies can gain a competitive edge while driving meaningful healthcare advancements.

Addressing Challenges in Real-World Data Utilization

Despite its transformative potential, utilizing real-world data is not without its challenges. Urban highlighted the issue of data silos within organizations, where different departments collect and analyze data independently. “Medical affairs teams, for instance, touch almost every process in an organization, yet their data often remains isolated”, he said.

Breaking down these silos requires transparent communication and integrated platforms that provide a holistic view of the data. Urban also emphasized the importance of regulatory and ethical compliance. “Regulatory authorities recognize the value of RWD, but companies need to ensure they’re adhering to regulatory standards to maintain data integrity and patient trust”, he noted.

Furthermore, companies must invest in technologies and frameworks that streamline data analysis and reduce redundancies. “It’s not just about having the data; it’s about ensuring its accuracy, relevance, and usability across the organization”, Urban explained.

Emerging Trends and the Road Ahead

Looking ahead, Urban Urban identified precision medicine and decentralized healthcare as key trends shaping the future of health tech. “Precision medicine, particularly in oncology, is becoming the norm. We’re seeing a lot of innovation in cell and gene therapies, which require highly specific patient data to be effective”, he said.

Decentralized healthcare models, enabled by remote monitoring and digital platforms, are also gaining traction. “Patients are increasingly participating in trials and treatments from the comfort of their homes, which adds layers of complexity but also opens up new opportunities”, Urban explained.

As the industry evolves, the role of patient engagement will become even more critical. “Patients are more willing to share their data when they understand how it’s being used to improve care. Education and transparency are key to building this trust”, Urban emphasized. By fostering collaboration, leveraging technology, and maintaining a patient-centric approach, health tech companies can navigate the challenges and opportunities of this rapidly changing landscape.