Pharmacovigilance as an industry has seen significant growth over the years and it’s expexted to keep rising. According to a market survey, pharmacovigilance will see upwards of $8 billion in the next 4 years. This however needs to be supported by improvement in technology.
Automation is the next big step to this industry that can speed up different processes within the industry. It is evident that with the increase in demand for better drugs, pharmacovigilance processes need to be more efficient. Speeding up the end to end pharmacovigilance process will ultimately make the industry more efficient.
Drug safety is experiencing increased focus on reforming its processes so that it can take a shorter time for drugs to get to the market. However, complying with regulatory standards is of major importance. The need for safety monitoring of drugs and minimizing risk while maximizing benefits remains a priority. Achieving all this with the active involvement of humans may be a big challenge and that is why automation needs to come into the picture.
Pharma companies need to process data from a variety of locations. With a manual process, a large pharmacological company may only manage to process about 700,000 cases a year. This means close to 50% of the other cases of adverse effects may not be processed until the next year. This can hardly be defined as efficient especially with other demands to reduce cost and take on more cases.
Automation presents the solution to this challenge. Integrating artificial intelligence into the data process can make use of cloud-based data management to connect the dots from a variety of data sources and then predict cases of adverse reactions to drugs.
Cloud-based capture of data is efficient. There is no human error to consider and that means you can trust that the right information is being captured even without verification. This is a process that can be completed as fast as the data comes in.
Saving time is not the only benefit of cloud-based automation. This process is also made secure by restricted access to data and yet for authorized individuals and teams, the access to data is immediate.
With the machines taking care of this process, human intelligence can be put to use in other processes that require human involvement. This will streamline processes and make the data processing move much faster.
Clinical trials need to be monitored and collected data needs to be shared with scientists and sponsors. Because of the importance of trials, a lot of manpower is employed here. This means the process is manual and collecting and recording data from trial sites takes up the bulk of time during the trial stage.
Introducing automation to this process can cut down the amount of time spent by 90 percent. Automation will achieve efficient collection of the data, processing, and presentation for analysis. Analysis is actually the most important process in trials and here’s where human input is needed the most.
More time and attention can be focused on analyzing data to come up with accurate trial reports to share with stakeholders. The sharing of this data is also achieved with automation. Reports can be sent to different sponsors instantaneously.
The regulations on drug safety need to be adhered to with precision and vigilance. This however should not affect the speed at which pharma companies are able to introduce new medication to the market. Adhering to the guidelines is a data-intensive process.
A lot of information has to be collected and analyzed to establish any adverse effects and effectiveness of drugs. AI can make all of this possible. It can be programmed to ensure a checklist and then collect the required data from the different sources.
When humans are in charge of data management, the process is slower and sometimes processes can be missed or data may be left out. Automation on the other hand will collect every relevant information including remote cases of adverse effects that may be reported online but not forwarded to the company.
Signal detection can be made instant when using AI to meet regulatory guidelines. This means that new medication can get to the market faster and yet still meet guidelines set by regulatory bodies.
Part of adhering to guidelines involves sharing information with the regulatory bodies. This pharmacovigilance reporting process would need to be compiled and arranged in a fashion that is clear and concise. This can take up a lot of time if it has to be done manually. Automation can remove the human element from this process.
Documents can be automated so that reports are compiled from the different data sources and all relevant data will be included in the report and sent to the concerned authorities. This is a process that can be scheduled so that even without prompting, reports will be sent on time.
The safety of these reports can be guaranteed with added encryption to ensure that they are only received by the intended recipients.
There is already active change in the way pharmacovigilance is carried out. Small transformations towards automation are being made to improve efficiency and ensure the safety of drugs that are released to the market.
It is obvious that the demands today will require better efficiency in the future. Pharmaceutical companies need to adopt new technologies which will make them perform their duties effectively. Automation will have to go a step higher and embrace machine learning so that technology can also make decisions based on set guidelines.
Automation offers the means to reduce human involvement in some key tasks of the industry. This will help humans focus on other areas that will speed up the amount of time spent trying to meet safety standards. With end to end automation, there would be continuous processes with safer drugs coming out much faster. With such technology at your fingertips, life-saving medication can be tested and approved much faster.
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