How technology is redefining pharmacovigilance
Big data, artificial intelligence (AI), and machine learning (ML) are driving a technological revolution in healthcare. But with such rapid progress, understanding what these advancements mean in practice and where their value lies can be challenging. uMed CEO Matt Wilson highlights how technology is reshaping pharmacovigilance (PV) and the future developments that will foster a more proactive and efficient safety monitoring approach.
Technological advancements are set to provide substantial efficiency savings to PV. This is particularly true in post-authorisation safety studies (PASS), where pharmaceutical companies seek to better understand the long-term risk profile of medicine in real-world settings. By expanding the breadth and improving the quality of data available, as well as by enabling closer contact with patients, these innovations will help PV teams to substantially enhance information gathering on adverse drug reactions (ADR).
Streamlining data processing and analysis
Two of the biggest factors shaping this sector are the availability of new sources of health information and the simultaneous advance of technology, giving the ability to manage increasing volumes of data. Enhanced processing power allows for swift and complex searches through large volumes of data in shorter times. This is especially beneficial for labour-intensive tasks such as scanning literature for safety signals.
By using AI and ML to recognise patterns in large data sources, analyses and recommendations can be delivered much faster – often instantaneously – allowing us to predict the likelihood of ADRs and be more proactive in mitigating and managing risk.
Enhanced efficiency through EHR outreach
Integrating EHRs into electronic data capture systems is already having a positive impact, reducing costs and resource use in the setup of PASS, while increasing efficacy and scalability.
In particular, it simplifies the challenge of re-engaging with patients to verify individual case study reports (ICSRs), where one or more of the four reporting criteria is missing (identifiable patient, identifiable reporter, suspect drug, and adverse event). Traditionally this has involved channelling a request via a physician who then contacts the patient to obtain the missing information, a time-consuming and often unreliable process. EHR integration streamlines and increases the accuracy of this laborious process by giving PV teams access to patient contact details, so they can directly collect missing information from pre-consented patients.
EHR-led outreach also helps to mitigate bias in PASS. Bias can creep into studies through numerous avenues – from physician influence to the type and location of the healthcare centre. While it may be impossible to completely eliminate bias, by analysing EHR data at the start of a study, PV teams can target and overrecruit underrepresented groups, creating more representative patient cohorts.
Improving patient engagement
Mobile technology has been transformative for many industries. In healthcare, it has facilitated the growth of decentralised studies and enabled the emergence of apps and portals that allow patients to engage in research remotely.
This not only makes participation more convenient, but also enhances data accuracy in PASS. Mobiles allow patients to self-report information instantly, from wherever they are located, minimising gaps in reporting. In-app prompts and notifications also provide useful reminders and further increase engagement.
Tackling data security concerns
Data security cannot be trivialised. Given the sensitivity of health data, it is absolutely critical that all technology use must be underpinned by strong data security and ethical oversight, with appropriate accreditations and safeguards in place – HIPAA compliance (for the US), ISO27001, and 9001:2015.
To allay physician and patient concerns, both should receive explicit information about how data will be used and absolute transparency regarding the level of identification risk.
Though total data anonymisation carries the lowest risk of reidentification, this option eliminates the ability to follow up on potential safety events, as all patient identifiers are deleted. As a result, pseudonymised data is often the preferred option for PASS and, as there is some level of identification risk, suitable mitigation measures must be in place.
The Future of Pharmacovigilance
Technology continues to evolve, offering further opportunities to improve PV practices and medicine safety. Several key trends that will impact the future are worth keeping an eye on.
AI driven data analytics will enable more prospective approaches in PASS, rapidly detecting and predicting adverse events, rather than having to rely on retrospective analyses.
Automation in case processing will reduce manual work and streamline current systems, giving PV teams more time to focus on complex cases and risk assessment.
Wearables and remote tech will offer additional data sources for health and fitness enthusiasts and the life sciences industry, enhancing accuracy and ensuring robust data for study insights.
Harmonising healthcare data across borders and health systems will facilitate data integration, reducing the time and money associated with data compilation.
The ongoing technological revolution represents a new era for PV studies, emphasising patient-centric benefits, accuracy, and efficiency. Embracing these advancements, while prioritising patient trust and data privacy, will pave the way for more significant PV practices and medicine safety.
