Maintaining regulatory compliance in a global marketplace is increasingly challenging as wellestablished regulators and regional local regulators increase their digital capabilities and expectations of Marketing Authorization Holders (MAHs). Oracle has a regulatory intelligence team that tracks global regulations and shares updates within our Safety Consortium, Regulations, and Audits Working Group. Compliance updates are released regularly, with adoption eased by the move from on-premise installations to SaaS cloud.
Over time, pharmacovigilance has become more intense – data about adverse events are collected more quickly, more cases are filed, and more questions are being asked about the data that is collected. In fact, according to market intelligence provider IDC, safety caseloads are increasing by an average of 30 to 50 per cent a year1, so pharmacovigilance teams are looking for ways to process cases more quickly and efficiently. Automation and AI are key in this endeavor.
One recent successful automation deployment was seen in the rapid development of the COVID-19 vaccines and therapeutics. With more than 10.4 million verified users and 150 million anonymous health records, the v-safeSM health checker created by Oracle and the CDC helps healthcare professionals better understand how people respond to different vaccines—including common adverse effects—and make recommendations based on people’s responses.
The wide-scale adoption of the v-safe platform makes it one of the largest real-world patient data- gathering platforms in the world for a single therapeutic area. The data captured through v-safeSM has been instrumental in building the evidence base to support the safety and efficacy of the mRNA COVID-19 vaccine in pregnant women (who were not part of the original clinical trials) and other vulnerable populations. The data was also critical in securing formal FDA approval for the Pfizer-BioNTech COVID-19 vaccine and subsequent booster shots.
Monitoring for new safety signals, which is information on a new or known side effect that may be caused by a medicine, is also challenging for these rapidly adopted new therapies and vaccines. We recently published new research on signal detection of the mRNA COVID-19 vaccine data which demonstrates the capabilities of Oracle Empirica Signal to identify potential signals earlier than historical methods.
Argus is a leading SaaS solution for processing, analysing, and reporting adverse event cases originating from pre/post-market drugs, biologics, vaccines, devices, and combination products. Its built-in automation, integration, and usability capabilities reduce manual tasks and maximise efficiency.
Argus can scale from supporting start-up companies with a handful of clinical candidates up through the largest biopharma companies with thousands of products marketed in a hundred or more countries. We are constantly monitoring for changes in global PV regulations and issuing compliance updates as needed.
No. In fact, with so many new ways to report adverse events, companies today have access to more data on drug safety than ever before. As adverse events arise, it’s critical to have a system in place that can provide fast, high-quality insights at scale to drive the company—and industry—forward. An automated approach allows human experts to focus on the critical cases, so existing resources are used most effectively even as the overall volume of data increases.
Historically, the pharmaceutical industry has been slow to adopt new innovations, but the pandemic necessitated an acceleration of the adoption of digital technology, including new tools for automating safety case processing.
Key to this transformation understands how tools can be more efficient and effective, both in crunching data and enabling staff to focus on different areas of their jobs that allow them to be more creative and innovative. By applying machine learning and data science approaches, companies can automate mundane, repetitive tasks and quickly gain new information and insights about patients and therapies from the abundance of data.
Focusing on adverse event case intake, AI can be applied to a wide range of data types such as forms with a defined structure to images. It is also possible to extract and analyse data from unstructured sources like journal articles or emails. Once the documents have been automatically structured and processed, they can be separated into ‘routine’ cases that can be handled entirely by software, and ‘high-priority’ cases that require a closer review by safety specialists.
The insights provided by AI also enable safety evaluators to make more informed observations, for example, with new techniques such as neural signal detection, multimodal signal detection, and predictive signal detection.
Oracle Empirica is a leading solution for detecting, analysing, and managing safety signals originating in pre- and post-market drugs, biologics, vaccines, devices, and combination products. The platform provides users with a powerful data-mining engine with algorithms that offer flexible signal-management analytics with rich visualisations. With Empirica, pharmaceutical companies can help ensure they are always in compliance with EU GVP Module IX and CIOMS VII. Oracle continually researches, develops, and advances state-of-the-art data-mining algorithms and statistical techniques used in Empirica solutions.
Today, medicinal product safety teams are under enormous pressure to control ever-increasing caseloads, new sources of signal detection data, and changing regulations—all with flat budgets and resources. Cloud-based platforms such as Oracle Argus and Oracle Empirica, coupled with standardisation, have helped lower costs through faster and easier implementations and upgrades. Through the delivery of technology solutions, we are an enabler to allow our customers to process and convert data into information and insights to drive improved patient safety.
One of the biggest challenges pharma faces is managing the massive amounts of patient data – and sources of data -- that are available today. There is more data available now than could have ever been imagined nearly a century ago when the first safety protocols were put into effect. Data can show us which patients should be prescribed certain drugs, which drugs are helping people, and which are not.
To process this vast and growing amount of data we will soon see technology used to move beyond augmenting human work to touchless case processing. Oracle Argus can help in this process, including assisting with automating all aspects of the safety process, from intake to report generation. While the touchless approach has not been fully adopted yet, there are certain aspects of safety case processing that are currently more suitable for greater degrees of touchless automation. For example, products that have been in the market for a considerable amount of time and are well understood naturally require less human intervention because the safety profiles are well-known.
As various system capabilities improve over time, more widespread use of touchless processing will become more feasible. Given that, companies can begin to plan for a touchless case processing system. The key is to adopt a stepwise approach, implementing and validating each automation area one at a time, to eventually build an end-to-end automated process with confidence.
As we look forward to a new era of pharmacovigilance, cloud and AI technology have provided an opportunity for continued innovation and a way to bring new drug treatments to market faster and serve more people – safely. With so much data – and the technology to analyse it available today – there is no doubt we are evolving from the manual processes used in the early days of drug safety to an era of precision pharmacovigilance – a personalised approach to drug safety that will help maximise the reach of new drugs and minimise the number of adverse events people experience.
While the pharmacovigilance process has traditionally been seen as a cost center, it’s now become a foundational component for any organisation. The information that is gleaned from safety processes is used to achieve the fundamental goal of drug safety–to reduce the risk of adverse events by informing doctors of potential side effects that were previously unknown so they can protect their patients who need the drugs.
1 * IDC MarketScape: Worldwide Life Science Drug Safety Services 2019–2020 Vendor Assessment — Building for Innovation