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Pharma Tech Outlook | Tuesday, March 24, 2020
In the future, the pharmacovigilance process will be automated using EDC, RPA, and AI.
FREMONT, CA: Certain unforeseen adverse effects may occur when a medication is on the market for an extended time. Pharmaceutical companies and regulators must monitor and report adverse events continuously. This is the essential idea underlying the process known as pharmacovigilance, which, according to the WHO, is "the science and actions concerned with the identification, assessment, understanding, and prevention of adverse effects or any other medicine/vaccine-related problem."
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Covid has presented a variety of obstacles and opportunities for providers of pharmacovigilance services. There was a reduction in ongoing clinical trials during Coronavirus lockdowns due to the limited availability of clinical resources and research staff. Patients were also restricted, which resulted in altered work methods, frequent audits, and safety inspections. Additionally, the increased use of medications has compelled the healthcare sector to work on product safety profiling around the clock. The pharmacovigilance business is increasingly responding to new trends resulting from more efficient data gathering and processing to capitalize on these potential opportunities. Below are some pharmacovigilance trends for 2022 as follows:
Scalability of Resources: A substantial increase in Adverse Effects (AEs) during the pandemic. The pharmaceutical sector had to expand its resources and employees to manage this workload properly. Additionally, there has been a rise in manual operations that can be outsourced, such as data collecting and entry. The scaling process has been enhanced by adjusting key performance indicators (KPIs) and creating dedicated teams, resulting in increased flexibility.
Pharmacovigilance Automation: Numerous areas of pharmacovigilance can benefit from automation. Automating pharmacovigilance offers numerous benefits, including eliminating human error, cost savings, and time savings. This enables the management of vast amounts of data and compliance.
Pharmacovigilance requires automation to ensure that tracking, task monitoring, and data gathering occur automatically. Automation has the potential to transform the way data is collected and evaluated, thereby accelerating clinical trials. The electronic data capture (EDC) system is a database used to record patient data collected during clinical studies. It is efficient to collect and analyze data using EDC-based tools during clinical trials and market observations. Cloud computing is suitable for establishing a wholly integrated database accessible to all stakeholders, critical for enhancing drug safety and pharmacovigilance. Robotic Process Automation (RPA) automates data entry, processing, and analysis, eliminating manual processes. Combining robotic process automation with cognitive automation via natural language processing can aid in decision-making. Machine learning and AI can assist data analysts, and data scientists make predictions based on data analysis. This has the potential to improve the quality of pharmacovigilance processes significantly.
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