When the Covid-19 vaccine appears, we'll all want to get it as soon as possible. A typical vaccine development and production process depends on how the vaccine is created, with the manufacturing process taking from several days to several weeks for one batch. As coronavirus is spreading worldwide, the urgent need to increase vaccine access is even more important. Delays in production can occur at any time, from the timely receipt and testing of raw materials, through the characterization of the drug substance, to quality tests. Automation technologies can help both speed up the production process and make the process safer and more efficient by reducing manual errors.
Digital tools can speed up the vaccine development and production process in several ways:
Digitization of data flow
Creating a vaccine or pharmaceutical therapy requires a huge amount of data. These data are combined into a report, which in the past was stored on paper and could contain several hundred pages. Today, thanks to digitization, all information from reports is automatically recorded in electronic form. Electronic records can help reduce the shelf life of vaccines and medicines before they are released.
Data control in the cloud
Configuring the control system in the cloud allows engineers around the world to use a common system regardless of geographical location. American engineers working on the vaccine can quickly provide information to a team of engineers in India. This team can work on exactly the same system and transfer it to another engineering team in Europe, and then transfer it back to the USA. In addition, many teams can simultaneously build different parts of the system, which further reduces the time needed to build the system and maintains the pace of work.
Optimization user experience
Marketing and technology teams watched operators struggling to run processes in existing control systems. The information obtained has allowed the creation of updated instructions visualization, which are more intuitive for the operator, giving insight not only to the step in which the operator is currently but also digitally allows insight into upcoming instructions. An example here may be an operation that scheduled 45 minutes exceeds this time, the operator is notified of corrective action. Traditional systems do not indicate to the operator how long the operation lasts, nor do they indicate that corrective action is necessary. This gives the operator time to perform other tasks, such as taking a sample and submitting it to the laboratory, preparing a component to be added later, etc. This allows operation with maximum efficiency almost from the beginning of the process.
source: roboticsandautomationnews
