About 15 years ago, our English teacher asked us to write a topic about our predictions for the world in 2020. The majority of us expected great innovations and technological developments, which would make life easier.
Once you imagine the future, technology usually plays a part, and it’s the same when we discuss and expect the future of pharmacovigilance. Innovations, automation, and artificial intelligence can have a great impact on the future of pharmacovigilance.
And because technology is usually used to fill gaps and solve current problems, identifying the on-going obstacles in Pharmacovigilance is necessary to guarantee a brilliant Pharmacovigilance future.
Read Also: Historical Overview of Pharmacovigilance
Regulatory Harmonization for a Better Future
Although the ICH guidelines provide international standards for reporting, some countries use different formats. Consequently, the same safety information may be presented in different ways, which increases the pressure on regulators.
In this way, regulators may have different opinions regarding the same safety information, and this will have a negative impact on data evaluation and final decisions. Therefore, regulatory harmonization is crucial for a better pharmacovigilance future in which data is presented in a unified format. 
Unified Database: The Start of Innovation in Pharmacovigilance
Collecting Adverse drug events in multiple databases creates a kind of confusion and work stress in pharmaceutical companies. Clinical trial data and post-market observational studies are directed to the clinical database, whereas the spontaneous adverse drug events are sent to the drug safety database.
The presence of a unified drug safety database, which contains all kinds of adverse drug events, whatever their sources, types, or seriousness, will help pharmaceutical companies and pave the way to other technological advancements. 
Automation Leads the Future of Pharmacovigilance
Currently, the majority of data is collected manually; however, automation can enhance the process of data collection and data analysis. During clinical trials, data collection and data validation can be automated, which would increase the speed of clinical trials.
In the post-marketing observational studies, automation can improve data capture by using electronic health records and mobile applications. And after reaching a critical mass of data, clinical trial tools can be subsequently used in the post-market data collection. 
Electronic data capture systems – Web-Based Solutions
Electronic data capture (EDC) is an example of clinical trial tools. It is a software that is used to store the patient data during clinical trials.  Using EDC-based tools in collecting and analyzing data during clinical trials and post-market observational studies are efficient.
However, the clinical trial data and post-market data vary in quality and quantity, so how can we distinguish between them?
Implementing the Electronic Data Capture systems will be followed by performing separate sub-databases, which will be under the umbrella of a single aggregate database. 
Impact of Cloud Technology: Innovation in Pharmacovigilance
The presence of cloud technology will provide a fully integrated database for healthcare providers, research institutions, and users, which is crucial for advancing drug safety and pharmacovigilance.  And this isn’t applicable nowadays; every company has its separate database and own access, which can have a negative impact on the development of pharmacovigilance. 
By allowing continuous access to all types of data: clinical trial data, post-market observational studies data, and spontaneous report data, we guarantee appropriate signal detection, validation, and continuous evaluation of data. 
Different Levels of Automation: Innovation in Pharmacovigilance
There are different levels of automation, and as soon as we reach higher levels of automation, human interaction and manual efforts dwindle. 
Basic Automation in Pharmacovigilance
It provides automatic tracking, task monitoring, and collection of continuous metrics.  Nevertheless, manual intervention is required during data entry, data processing, and data analysis. 
Robotic Process Automation in Pharmacovigilance
Robotic Process Automation (RPA) provides automatic entry, processing, and analysis of data, which can eliminate the previously manual tasks.  Moreover, by combining the RPA with cognitive automation, Natural Language Processing can help humans make decisions. 
Artificial Intelligence in Pharmacovigilance
Once we reach the level of Artificial Intelligence automation (AI), human intervention is almost diminished. With the help of Machine Learning, which is a branch of AI, data analysts and data scientists can make predictions, which is based on large volumes of data.  The main aim of artificial intelligence in pharmacovigilance is enhancing the current processes, without replacing it. 
Why Automation is Necessary for Better Pharmacovigilance Future?
Pharmacovigilance automation has several advantages, which can enhance the future of phamacovigilance: 
- It improves the accuracy and quality of data.
- It saves time, decreases human errors, and reduces costs.
- It guarantees complete adherence to the regulatory guidelines.
In addition, with the continuous development of new products and increasing the sources of information, the data volume increases.
Consequently, manpower alone will be insufficient to manage this massive amount of data. Pharmacovigilance technology, including automation, would help humans to perform their roles effectively. 
To sum up, innovation in pharmacovigilance never ends; many advanced technological solutions are available, and it will increase over time. The smart pill is one of these innovations in which the drug adverse events can be tracked inside the human body.  And definitely, the future is full of more advancements in pharmacovigilance.
As soon as you’re eager to learn more about pharmacovigilance and to gain new skills, join our pharmacovigilance course with Dr. Omar Aimer on RxCourse: https://www.innovigilance.com/
Written By: Sara Ahmed Zaki