At the leading edge of drug development, digital health is starting to make waves, bringing products and tools that offer patients a new level of personalized medicine. At the same time, these technologies give the biopharma industry, together with physicians, a way to optimize therapies in the clinic and the real world.
The most direct impact to patients will come from companies creating digital therapeutics, biomarkers or tools for disease management, though machine learning and AI will contribute beyond that through drug discovery, product development and manufacturing.
Digital therapeutics are making their first push in neurology, where they offer novel systems for addressing CNS diseases. Using digital technologies to monitor speech, movement and other behaviors, via interactive programs on apps or other forms of software, these products offer treatment options that supplement, and may one day replace, other forms of therapy.
Digital biomarkers are poised to create new endpoints that can be incorporated into clinical trials, and extend the spectrum of inputs from genetics and intermittent measurements of biochemical, physiologic and other readouts, to include continual collection in the real world of a broad range of measurements. These markers involve sensors, mobile devices or other systems that capture treatment benefit, and can use individual patient data to predict likely responders to a therapy.
Digital tools for disease management have made the biggest inroads of the three -- garnering more investment and FDA approvals. These tools empower patients to manage their health in near real-time through interactive feedback on whether a therapy is improving disease-specific symptoms or metrics. Examples include symptom tracking apps for cancer or arthritis patients that transmit data for remote monitoring, and either automatically via a remote exchange or through an in-person exchange with the physician, recommend dosing adjustments or treatment alternatives.
These tools and products all incorporate software in ways that receive patient data and use it towards a tailored treatment path.
The common thread is that these tools