Empowering drug development: Leveraging insights from imaging technologies to enable the advancement of digital heath technologies.
Elena S IzmailovaRalph Paul MaguireTimothy J McCarthyMartijn L T M MüllerPhilip MurphyDiane StephensonPublished in: Clinical and translational science (2022)
The US Food and Drug Administration (FDA) has publicly recognized the importance of improving drug development efficiency, deeming translational biomarkers a top priority. The use of imaging biomarkers has been associated with increased rates of drug approvals. An appropriate level of validation provides a pragmatic way to choose and implement these biomarkers. Standardizing imaging modality selection, data acquisition protocols, and image analysis (in ways that are agnostic to equipment and algorithms) have been key to imaging biomarker deployment. The best known examples come from studies done via precompetitive collaboration efforts, which enable input from multiple stakeholders and data sharing. Digital health technologies (DHTs) provide an opportunity to measure meaningful aspects of patient health, including patient function, for extended periods of time outside of the hospital walls, with objective, sensor-based measures. We identified the areas where learnings from the imaging biomarker field can accelerate the adoption and widespread use of DHTs to develop novel treatments. As with imaging, technical validation parameters and performance acceptance thresholds need to be established. Approaches amenable to multiple hardware options and data processing algorithms can be enabled by sharing DHT data and by cross-validating algorithms. Data standardization and creation of shared databases will be vital. Pre-competitive consortia (public-private partnerships and professional societies that bring together all stakeholders, including patient organizations, industry, academic experts, and regulators) will advance the regulatory maturity of DHTs in clinical trials.
Keyphrases
- high resolution
- healthcare
- electronic health record
- machine learning
- big data
- public health
- mental health
- health information
- randomized controlled trial
- social media
- case report
- emergency department
- transcription factor
- fluorescence imaging
- health insurance
- human health
- adverse drug
- climate change
- artificial intelligence
- acute care