*Michael Kremliovsky, Executive Director, Digital Health and Real-World Science, Bayer

Digital health is ginormous and amorphous. Thankfully, the FDA has had a go at a definition: “Digital health technologies use computing platforms, connectivity, software, and sensors for health care and related uses [...] They include technologies intended for use as a medical product, in a medical product, as companion diagnostics, or as an adjunct to other medical products (devices, drugs, and biologics). They may also be used to develop or study medical products.” Admittedly, that is a pretty wide definition. However, there is one delineation in there that is worth focusing on: technologies used internally in the development of products (by pharmaceutical companies etc) vs technologies used by healthcare professionals and end-users like patients. The first group is relatively straightforward i.e. if there is a case for using digital aids, be that advanced algorithms or simulations, to save time or improve quality during R&D, bingo. When it comes to using digital health as a complement or substitute to medicine etc., it’s a different story according to a group of pharmaceutical and medtech professionals we spoke with.

Challenge 1: Regulatory and Evidence Validation Challenges

One of the most significant barriers to the adoption of digital health solutions is the challenge of gathering compelling evidence of effectiveness. While regulatory bodies like the FDA offer risk-based and expedited pathways, the process of collecting rigorous data and demonstrating clinical value remains expensive and time-consuming. "Studies and getting approval for your digital health solution can take 2 to 6 years. That timeline is often a surprise" explains Spencer Jones, digital health consultant. 

What could be done: Digital health innovators face a critical challenge in generating compelling evidence of solution effectiveness. Successfully navigating the regulatory landscape requires meticulously designed studies, proactive engagement with regulatory bodies, and robust quality management systems that can comprehensively demonstrate a solution's clinical value and safety. This process demands a multifaceted approach that goes beyond traditional medical device validation, incorporating real-world evidence, patient-reported outcomes, and advanced data analytics to substantiate clinical efficacy.

Challenge 2: Integration with Traditional Healthcare Systems

Integrating digital health tools into existing healthcare systems presents another major challenge. Healthcare providers often face significant difficulties incorporating new technologies into their workflows, leading to resistance and underutilization. How would you feel if, as Arndt Schmitz, Medical Software Product Lead at Bayer put it: “you are a nurse that already has to remember 50 passwords”?

What could be done: Suppliers and customers should ensure there is change management expertise involved from the start. In addition, healthcare institutions should demand that any providers of new solutions also give comprehensive training and develop user-friendly systems that simplify the integration process. Implementing single sign-on solutions and intuitive interfaces can reduce the cognitive load on healthcare workers, making it easier for them to adopt and effectively use new digital tools.  

Challenge 3: Understanding and Modifying Patient Behavior

Digital health tools often fall short in one critical area: influencing patient behaviour. “90% of harm is done by our unhealthy habits. Lifestyle has the single largest impact on healthcare.  On the other hand, consumer health technology is not universally trusted. It took me two years to accept continuous blood pressure monitor readings, and I work in the field!”. Michael Kremliovsky, Executive Director, Digital Health and Real-World Science, Bayer. New treatments, traditional or digital, rarely sufficiently address challenges like poor diet or treatment adherence.  

What could be done: Developers of digital health solutions must collaborate with behavioural change experts to design more effective patient engagement strategies. Personalised and adaptive technologies that provide tailored interventions can improve patient adherence and health outcomes. By understanding the behavioural science behind patient actions, digital health tools can become more effective companions in the healthcare journey.

Challenge 4: Mismatch Between Expectations and Reality

The expectations surrounding digital health have often been unrealistic, promising rapid advancements and significant improvements in healthcare that are not always immediately achievable. In many pharmaceutical companies, management is supportive but the directive is clear: "show me the money". This demand puts pressure on digital health innovations to demonstrate immediate financial value. "Digital health has not yet closed the gap in R&D. Clinical research remains time-intensive. Digital health solutions support patients and health systems but they do not replace medications. Naturally, pharma companies are cautious about large-scale investments," Kremliovsky notes. However, the perspective is far from pessimistic. The challenge lies in strategic approach: digital health isn't just about digitizing existing processes, but actively pushing innovative methodologies that can reshape how we develop medicines and deliver care. Jones highlights this tension: "In many cases, digital health is navigating between boardroom expectations of short-term wins and the necessity of a long-term, visionary strategy". The key may be in finding a balanced approach that demonstrates tangible value while maintaining a forward-looking perspective.

There’s also a reputational aspect. When a €250k digital health project fails, people don't want to be associated with it, whereas if a $50m clinical trial doesn't meet endpoints, that’s accepted as business as usual. “The risk tolerance for digital health is too low and this needs to change if pharmaceutical companies want to deliver value-added services to our patients” says Rafael Lira-Carrillo, Digital Innovation Hub Manager, Merz Therapeutics.

What could be done: Companies and investors need to align their expectations with the realistic timelines of digital health advancements. Long-term investment in research and development is crucial, and stakeholders must prepare for incremental progress rather than expecting quick wins. Recognizing that digital health is not a panacea but a gradual evolution can help set more achievable goals and sustain commitment over the long term. Being thoughtful about the right group of stakeholders to guide exploration, implementation, and continual learning from digital health initiatives is key; there needs to be diversity in domain knowledge, from both the life sciences and technology side. Christy Cheung, former Lead, Digital Health, Insights, and Learning Capabilities at Sanofi has seen first hand how investing in centres of excellence and creative partnerships with technology developers can accelerate a pharma company's advancements in digital health.

To conclude, on the one hand you have the view, represented by Kremliovsky, that the path to widespread digital health investment hinges on pharma companies seeing clear return on investment for their specific business and operational needs. Currently, companies are hesitant to fully commit to digital health initiatives, and they're still developing the workforce and infrastructure needed to support these innovations. To accelerate adoption, we need to demonstrate ROI that directly speaks to pharma's strategic and economic interests. On the other hand is Schmitz’s position that digital health has a much better stance than five years ago. The EU, governments etc are waking up and the field is maturing. You no longer need to be a believer in digital health as the evidence is mounting and, as Carrillo warns, big pharma better get their game together because the tech giants are coming to healthcare, their pockets run very deep and they won’t play by the old rules. 

Contributors: Spencer Jones, Christy Cheung, Michael Kremliovsky, Arndt Schmitz and Rafael Lira-Carrillo.