7 Industry Trends Shaping the Future of Pharmacovigilance – Part 2 of 2
March 8, 2017
Continuing from Part 1 of our study on the Industry Trends of this Life Sciences field, we discuss how access to data, data analytics, automation, and artificial intelligence come into play this 2017 for the field of Pharmacovigilance.
7 Key Industry Trends for Pharmacovigilance (Continued)
Cloud-Based Reporting to Bring a Robust Global Database of ADRs
The ability to store and analyze massive amounts of data in the cloud has brought together a robust global database for disease, medicines and their side effects. Cloud-based technology creates a fully integrated system for all parties – healthcare providers, physicians, users, research institutions – to store and access any registered drug and its potential side effects. Aside from increasing transparency, this global database is a means of learning cross-pollination between countries for ADR patterns and symptom occurrence insights. Cloud technology takes away the distance and time-lag barriers, and creates a real-time dynamic data set for all Pharmacovigilance markets.
Big Data to Protect and Assimilate Huge Amounts of Information
With Cloud technology increasing the threshold of data storage, big data is a field that comes to play in the capture, storage, processing, transfer and information security for large amounts of medical records. The Pharmacovigilance industry will become more and more dependent on big data technology for end-to-end assimilation of information as well as keeping the integrity and security of the data. With the sheer volume and variety of secondary data sources, big data becomes a powerful tool to swiftly organize, classify, and even profile the veracity of reported ADRs for pharmaceutical companies and regulatory agencies to analyze. At the end of the day, the output of big data are integrated and consolidated data that is ready for data science and subsequent decision-making. Through high capacity data utilization, many potentially fatal ADRs can be thwarted and pharmaceuticals can quickly take adverse drugs off the market.
Data Analytics to Mine Insights
Mining the data from the cloud and big data sets bring about impactful insights on the occurrence of ADRs across different countries and regions. Applying data analytics in Pharmacovigilance processes increases the speed of signal detection, which essentially seeks information that point to causal relationships between drugs and reported adverse or beneficial events.
By mining insights from the data, PVO companies are able to map patterns and historical trends in order to isolate the interaction or presence of drug components that can correlate with ADRs, leading to safer and more effective drugs with fewer side effects. Mapping data trends lessens the cost-intensive practice of clinical trial and error methods to test data. Instead, data analytics combined with increasingly powerful data visualization tools can verify datasets of reported ADRs to better recognize patterns, trends and correlations. When drug regulation protocol are shared and reapplied across different markets, this can influence the Pharmacovigilance industry towards adopting global standard guidelines.
Automation for Non-Value-Adding Tasks in the PVO Process
With pharmaceutical and medical talent becoming more scarce, it is pivotal to the success of any PVO provider to ensure that their time is invested in value-adding activities in the Pharmacovigilance platform. Automation enables increased labor efficiency by removing administrative and clerical tasks that can be relegated to computers and robots. These include manual drug filing, updates to drug label information and clinical overviews, drug active ingredients checks, and report generation.
Automation frees up labor capacity, hence reducing overall PVO costs while increasing accuracy and quality of ADR detection. Furthermore, automation tools improve the visibility and monitoring of all pharmacovigilance processes related to a single drug, while ensuring timely follow-ups and flags when safety-related activities arise. Some automation software can be further customized to reduce the time lag from signal detection to characterization to adjudication.
Artificial Intelligence to Turn PVO into a Predictive Science
Artificial intelligence (AI) is predicted to change the way humans work, communicate and learn, with applications spanning medicine, transportation, education and other industries. It is important to note that developments in this field may have significant impact on Pharmacovigilance, ultimately turning the field into a proactive science. AI has the potential to fill in what traditional Pharmacovigilance services currently lack: the ability to assimilate large amounts of cloud-based data, map patterns, and correlate with genetics and disease occurrences in order to effectively predict ADRs.
In the future, automated signal detection systems driven by Machine Learning can improve accuracy of medical reporting. There will be a tremendous amount of time, labor and system resource cost saved by mitigating the trial and error procedures of Pharmacovigilance and clinical trials. Through AI, Pharmacovigilance would be able to take a more proactive stance on drug safety regulation.
The market for Pharmacovigilance is rapidly evolving to meet the increased demand of medicines, driven by the growing disease burden and aging geriatric population. What does this mean for pharmaceuticals? There is a need to reassess and qualify the best Pharmacovigilance delivery model, which includes vetting the right PVO partners who are able to deliver efficient reports while minimizing risks of ADRs. What does this mean for PVO providers? The ability to compete and thrive in the changing drug safety landscape is directly correlated to their investment in harnessing and utilizing technology trends.
After all, Pharmacovigilance is a field that at its core has a simple mission: to safeguard public health and promote the safe use of medicine. Thanks to advancements in technology, we are brought closer to a future with less and less deaths from preventable ADRs.
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