Written by Saar Yoskovitz, Co-Founder & CEO at Augury
As vaccination rates rise, some parts of the world are slowly starting to return to normal life. But vaccine makers are still working overtime to manufacture billions more doses for those who need it. There are currently 93 Covid-19 vaccines in clinical trials and eight vaccines approved for use. Vaccine manufacturing is a complex process even for well-established vaccines. Making a slew of new vaccines, including mRNA vaccines (made by Pfizer and Moderna) which use a vaccine technology that had never previously been mass produced, as well as distributing them, was an unprecedented challenge.
As part of my work with some of the world’s top vaccine makers. Here are five technologies I’ve seen that can make a difference in the global vaccine race:
Manufacturers have been using ERP (Enterprise Resource Planning) systems for production planning for decades, and vaccine production is an incredibly complex process. An ERP can help streamline the entire development and manufacturing process, from a vaccine’s development to commercialization. ERPs from companies such as Batchmaster can manage a vaccine formula, ensure quality control, help companies stay compliant with regulations, manage inventory and the supply chain, automate operational work and much more.
Using data analytics from companies such as Sartorius is another way to accelerate the process of a vaccine’s testing, regulatory approval and production by enabling a more efficient design of experiments (DOE) and a rapid production rollout. DOE is a branch of applied statistics that employs a systematic approach to process development studies. By using DOE, pharma companies can reduce the number of experiments needed to develop a new vaccine and the overall cost of experimentation. COVID-19 vaccines had to scale up to mass manufacturing within six to 12 months, an unprecedented speed in the industry. Data analytics tools like MVDA (multivariate data analysis) can help cut the number of total batches needed to prove production process robustness and scale up manufacturing.
Research and development for a vaccine can take years, but the vaccine process for Covid-19 was sped along from the lab to the market with help from Siemens’ digital twin. A digital twin is a way to replicate a production process through simulation; it allows scientists to test changes before they are actually implemented on a manufacturing line. In research and development, continual simulation at each step makes it possible to test and optimize new processes without losing time or having to make expensive investments. Siemens’ Business with Process Systems Enterprise (PSE) enables plants to optimize their productivity and performance using predictive models that reflect the real thing.
Augury’s Machine Health solution uses the Internet of Things (IOT) and Artificial Intelligence to predict and prevent manufacturing machine failures. A critical machine failure can bring an entire production line to a halt, a condition called unplanned downtime. Every hour of unplanned downtime is a lost hour of production time. For example, early in 2020 a production problem at a single factory in Belgium delayed tens of millions of doses of AstraZeneca’s COVID-19 vaccine scheduled for shipment to the European Union, slowing down the European vaccination program. Predictive maintenance of the type enabled by Machine Health can reduce unplanned machine downtime between 30-50% according to research from McKinsey, meaning that many more doses can be manufactured in the same facility.
Vaccine makers must ensure the safety and efficacy of every dose. In one case, Pfizer had to lower 2020 production targets after early batches of raw materials failed to meet quality standards, an unfortunate mishap that wasn’t prevented from the numerous quality checks conducted by the company.
Computer vision scanning software recognizes barcodes and QR codes enabling workers to identify a labeled package or vial and match it with a patient ID. If a batch of vaccines proves faulty, the batch can easily be recalled and individuals who received doses can be re-vaccinated. Scandit’s computer vision technology, for example, was used in U.S. vaccination centers to connect patients seeking vaccinations to their vaccination appointments, improving traceability.
These are only just a handful of ways that technology can be used to help manufacture and distribute vaccines. In the future, I expect that technology will continue improving the efficiency, safety and speed at which new vaccines are developed, even after the peak of the pandemic has passed.