Technology to transform the capture and processing of drug safety data


The ultimate goal of pharmacovigilance is to prevent adverse drug reactions, thus maximising the benefit:risk ratio for as many patients as possible, reports Dr Andrew Rut, CEO and founder, MyMeds&Me

Prevention relies on detection followed by the determination of causal association and, finally, communication through updated labelling and other materials.

In an ideal world, pharma gets early sight of potential issues by collecting relevant data direct from the patient, their caregiver or healthcare professional (HCP) and routing it for immediate analysis.

In contrast, pharmacovigilance systems still often involve multiple intermediaries with numerous hand-offs and a focus on paper; as a result, processes remain slow, resource-intensive and complex.

The market authorisation holder (MAH) receives safety data in the form of adverse event reports in a variety of different ways, including call centres, emails or even faxes coming into the pharmacovigilance team or, alternatively, via regulatory authorities.

Inevitably the variation between processes across these different sources leads to inconsistencies in the data or, worse still, no data at all … given that most people have no understanding of how or where to report.

Consequently, the recording, processing and reconciliation of safety reports across different intake routes is a highly manual, laborious process, requiring extensive review and resource-intensive follow-up cycles to address issues with discrepancies and/or incomplete data.

Why does this matter?

Robust pharmacovigilance relies on a body of complete, structured and timely data. However, the siloed and protracted nature of traditional safety reporting systems leads to significant gaps in time and content from the occurrence of the adverse event to analysis and decision making.

All too frequently, the opportunity to collect data is lost for good and requests for follow-up are usually unsuccessful.

Imagine, instead, if data capture solutions were placed in the hands of patients or those HCPs working directly with patients, whether in a healthcare setting or as part of post-approval programmes.

Digital technology offers the opportunity to transform the end-to-end pharmacovigilance systems by automating the process from initial reporting of an adverse event through to data output for analysis.

Andrew Rut

Andrew Rut

With the volumes of data being captured, processes need to be in place to collect, structure and collate data across all sources in a standardised and intelligent way to provide meaningful insights and improve overall patient safety. This can be achieved through the following considerations:

Increase the proportion of reports from the source: Surveys demonstrate that as few as one in a thousand patients experiencing an adverse drug reaction (ADR) actually report it.1

Therefore, a clear and uncomplicated process is essential to simplify reporting and maximise the number of useful reports captured without the requirement for increasing human effort.

Eliminating delay from the time an adverse event occurs through to the time it takes to be reported and reside in the MAH’s safety database ensures analysis can take place immediately.

The ubiquitous nature of technology now means that providing a simple web interface can empower patients, their caregivers or HCPs to report adverse events as close as possible to the event occurrence.

Not only does this reduce the pressure on call centres, but every time a new step is introduced to the reporting process, the quality of that data is also eroded. Consequently, facilitating immediate, direct reporting can improve the robustness and reliability of the data collected.

Ensure data is right first time: Incomplete and unstructured data is a constant challenge for pharmacovigilance teams. Inconsistencies increase the need for manual review and follow-up to address critical gaps in information.

The introduction of a centralised solution to capture safety data across all intake routes enables all reporters — patients, HCPs, call centres or staff running post-approval programmes — to capture consistent, relevant and reliable information from the outset.

One of the benefits of digital technology is that it can guide users through the process in their local language to ensure that all key information is completed and coded.

Technology offers flexible interface design to encourage engagement and elicit required responses; for example, users could be presented with a simple form or, alternatively, could be offered a chat-bot experience to support them as they work through to completion.

Technology also simplifies the translation of local language reports into English, the “Lingua Franca” of pharmacovigilance.

In either situation, dynamic workflows prompt the user to provide additional information by triggering specific questions based on responses to ensure important data is collected on the first interaction.

This dramatically reduces the occurrence of missing data and, therefore, the need for resource-intensive and often unsuccessful follow-up.

Furthermore, digital solutions can be updated simply, quickly and globally in light of new requirements for data capture as new signals emerge, to investigate areas of particular medical interest or following updated risk management commitments.

Facilitate real-time analysis: The overarching purpose of streamlining the pharmacovigilance process is to provide high quality safety data, more consistently, more rapidly and with less manual effort.

Digital transformation reduces the reliance on human processing through the capture of relevant, structured/coded data at the point of contact.

Data is seamlessly transferred between systems, removing the need for the time-consuming and tedious manual reconciliation, and ensuring that information is available in real-time for analysis and insights.

Thus, digital technology is able to expedite decisions regarding potential risks and benefits associated with medicines.

Data-driven insights

Signal evaluation and causality assessments of events and their relationship to the drug in question rely on robust data. Such analyses are possible only if pharma captures sufficient data to determine which factors are linked to the drug product and those that are unlikely to be associated.

At the time of a market authorisation, the knowledge base concerning the safety profile of a new medicine is very narrow — given the limitations inherent in clinical trials.

Following product approval and launch into new markets, pharmacovigilance teams are tasked with proactively understanding the product risks (both known and unknown) in a real-world setting.

As the pool of data grows, insights regarding the impact of background disease, lifestyle, genetics, etc., are uncovered so that the prescribing and use of medicines can be refined accordingly and subsequently communicated to the healthcare community or patients.

As products mature, pharmacovigilance focus turns to three areas: product quality, including manufacturing issues; new drug interactions; use in as-yet-unapproved disease areas or groups (such as children).

Although the baseline profile has been set, it is imperative that data continues to flow — ensuring pharmacovigilance teams can spot new patterns easily and quickly.

Absence of evidence is not evidence of absence

To create a true picture of product safety, pharma has a responsibility to capture as much available data as possible. Technology is essential to achieve this goal by enabling the systematic capture of standardised information direct from source.

Reducing the burden on call centres, removing the need for translation and ensuring key information is captured first time so that arduous and often unsuccessful follow-up cycles can be avoided.

This provides pharma with more complete, accurate and timely data on which to base their assessments, so they can provide advice and guidance that helps HCPs and their patients to reduce any potential risks.

Ultimately, “First Do No Harm” applies across pharmacovigilance, so it is important that data is seen as a friend as opposed to a spectre to be feared.2

Good data drives good decisions that, in turn, ensures that patients have good information on their medicines. Only in this way do we drive trust in healthcare and adherence to medicines.

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