Drug safety and wearables
Impact of wearable technology in pharmacovigilance
In our current health care environment, where we have greater access to technology and information than ever before, there's an endless amount of data at our fingertips. This data spans a medicine's lifecycle and can lead to a better understanding of the benefits and risks for patients. How can life sciences organizations use technology like wearable devices to help unlock drug safety information?
- Wearables-generated patient information
- Harnessing the power of wearable technology
- Delivering actionable insights
- Standardizing drug safety information from wearables
- Get in touch
Wearables-generated patient information
Biopharmaceutical manufacturers already collect information from patients taking medicines through clinical trials, spontaneous adverse event reports, and—increasingly—through real-world evidence (RWE) data collection and observational studies.
Wearable technology (wearables) can allow collection of additional information such as physical functioning, activity level, and vital signs. Wearable devices on patients and/or consumers can measure biometrics, biotelemetry, performance, and general well-being.
Wearables include a broad spectrum of technologies, ranging from insulin pumps to applications to devices with motion sensors designed to take photos and synchronize with mobile devices. One of the most significant features of wearables is the ability to connect to the internet, thus facilitating data exchange between the source and the network.
Wearables can address the scarcity of data that exists in between health care provider visits to drive new insights and outcomes. This data could offer a broader view of the patient experience before, during, and after closing—or as a more general study of disease.
Harnessing the power of wearable technology
The growth of digital device use and interoperability of resulting data provides vast opportunities for harnessing information from wearables for pharmacovigilance (PV) purposes. These opportunities are matched by methodological and analytic challenges to manage and interpret the data—challenges that can be met, in part, by building a framework for representation, analysis, and inference from incongruent, multi-source, and multi-scale biomedical data.
For the pharmacovigilance and medical community to leverage meaningful information from wearable devices, stakeholders need to consider how to 1) encode these diverse, multi-modal, often unstructured data; 2) aggregate, harmonize, and fuse encoded data into a structured format that will facilitate analytics; 3) formulate efficient methods of extraction; and 4) develop appropriate analysis methods.
The existing PV ecosystem has relied largely on structured, spontaneous, and clinical trial datasets housed in databases with controlled dictionaries for safety signal detection and analytics. The emergence of innovative health care data sources such as wearables and mobile health (mHealth) technologies has posed some challenges in terms of characterizing multi-modal, multi-scale, heterogeneous data that could be structured or unstructured.
There is a need to develop data standards, controlled vocabularies, and ontologies for structural or semantic representations of data and metadata from wearable devices and fuse them into existing PV dictionaries. Foreseeably, a new representation platform to harmonize these data standards and ontologies would be developed to assist extraction and analyses.
How we harness the power of data from wearable and mHealth technologies will depend on the degree to which we successfully manage the raw data, extract valuable information, transform that information to knowledge, and enable clinical decision making and action that are evidence-based; not just for PV but for the entire medical community.
Delivering actionable insights
Wearable technology enables the collection of additional patient information and offers a broader view of the patient experience throughout the study of a disease, thus promoting actionable patient insights. It empowers patients and health care providers alike with accurate and timely data to promote understanding of disease states and the use of medicinal products.
However, as we look to the future, the topic of how wearables data should be evaluated in the PV context must be addressed. In controlled clinical trial settings, the answer to this challenge is straightforward from a PV perspective: medical-grade wearables are effective in supplying data, and relevant information provided by the investigator should be reported in accordance with established regulations.
A more challenging aspect to address is how wearables data should be captured and evaluated in a spontaneous setting. The key tenet to keep in mind for PV is reasonableness: Remember that an information hierarchy exists—not all data is equally informative, more data is not necessarily better data, and increased volume does not equal quality. Wearable applications must be better understood to best leverage the data and avoid information overload.
Wearables data can enhance established PV technology by acting as an additional data source to identify potentially new or underreported safety risks. However, linking wearables to other systems (e.g., EHRs) may be a challenge in terms of patient representativeness, data reliability, data privacy, and lack of standard ontologies.
Standardizing drug safety information from wearables
Data and classifications need to be standardized across real-world data to deliver actionable insights for PV stakeholders. Looking ahead, machine learning and other technologies could provide valuable opportunities to improve data processing efficiency and to link disparate data from wearables.
PV organizations should monitor wearables data for value rather than assuming that value already exists. As technology and analysis methods are nascent in this arena, suggestions on how to capture, evaluate, and report information generated from wearable technologies will continue to evolve.
To learn more about the impact of wearable technology in drug safety, download the full report.
In development of this report, Deloitte collaborated with several pharmacovigilance industry leaders to open the dialogue on the potential impact of wearable technology in pharmacovigilance. This report focuses on wearables used in the clinical study setting in the United States to capture measures for specific purposes.
Examples include electrocardiography (EGC) devices and apps to monitor heart-related conditions and insulin monitors, such as special contact lenses to measure for HbA1C diabetes. It doesn't include general activity monitors, such as step counters, that are linked to cell phone apps.