Many are probably already familiar with “Biomarkers”. This is a term usually used to describe a molecule or gene that indicates a change in a person’s health or risk of disease. As technology take’s its innovative course in healthcare, Biomarkers are going digital.
Digital tools, such as smartphones, wearables and fitness trackers, continually collect health data from users. This information can offer actionable insights into the biological state of the individual, potentially offering opportunities to change behaviours or initiate treatments that can improve outcomes.
I believe that Digital Biomarkers are the future of precision medicine and is offering real-world evidence of patient outcomes. This evolution is fuelled by the transition to value-based healthcare. Incentives are aligning to support continuous, proactive care across the healthcare industry.
To unlock the full potential of Digital Biomarkers, it is vital that we leverage digital medicine, genomics, data science, informatics, and artificial intelligence, while tracking symptoms of disease progression, and medication adherence. Transforming this data into actionable insights can drive measurable results, and accurately predict outcomes of treatment.
Regulators and payers are increasingly interested in the insights yielded by Digital Biomarkers. From their perspective, they can generate meaningful evidence of safety and efficacy, support marketing claims and inform reviews of clinical utility and value.
Through extensive research, I have seen critical advances in machine learning, artificial intelligence, algorithm development, and statistical data modelling, which can identify useful digital surrogates.
Specifically, a sub-field of machine learning has emerged with algorithms that have unprecedented representational power and the ability to discover patterns that humans are unable to find or describe. These techniques have the ability to monitor and predict personalized health outcomes for individual patients, as well as overall trends of health and disease states for patient populations.
As with traditional Biomarkers, my experience is that well-designed and validated Digital Biomarkers can generate significant advantages in clinical study design, making recruitment more efficient, predicting study outcomes, and delivering efficiencies in the size or length of trials. The potential of Real-World Evidence driven by Digital Biomarkers is enabling rapid product development for the benefit of patients and the entire healthcare ecosystem. The potential value of our technology continues to motivate us to participate in collaborative partnerships to advance our Digital Biomarker’s platform and transform clinical trials by creating digital endpoints and engage patients in their treatment journey.
I believe that Digital Biomarkers can demonstrate the value of innovative technology, while monitoring and predicting validated health outcomes. These unique techniques also help foster improved partnerships between manufacturers and payers, by using evidence-based research to support population health.
As we accelerate the shift towards a digitally-powered health system, Digital Biomarkers will play a significant role in the future of prevention and care, as well as product development and reimbursement.