Thailand struggles with its worst coronavirus yet , researchers in the country have developed a machine to draw out Covid-19 vaccine doses more efficiently and optimise lower than expected supplies.
According to researchers at Chulalongkorn University, who made the machine that has been used at the university’s vaccination centre since Monday. Using a robotic arm, the “AutoVacc” system can draw 12 doses of the AstraZeneca vaccine in four minutes from a vial.
They said, that is up 20% from the standard 10 doses drawn manually. The machine only works on AstraZeneca multi-dose vials currently and labels show each vial can provide 10 to 11 doses.
Juthamas Ratanavaraporn, the lead researcher of the team at the university’s Biomedical Engineering Research Center said , “The machine guarantees with accuracy that we can gain an extra 20% from each vaccine vial – from 10 to 12 doses,”
Juthamas said, “The extra 20% that we get means that if we have AstraZeneca for 1 million people, this machine can increase the number of doses to 1.2 million people” .
Thailand had kept Covid-19 pandemic largely under control for much of the pandemic, but more virulent variants like Delta have sent cases and deaths soaring since April, ramping up pressure on authorities to increase the pace of vaccinations. “This could drain a lot of the health workers’ energy. They would have to do this every day for many months,” Juthamas said.
Around 9% of Thailand’s population of more than 66 million have been fully vaccinated, with the rollout hindered by lower-than-anticipated vaccine supplies.
She added,The prototype machine costs 2.5 million baht ($76,243), including other materials like syringes, said Juthamas, adding that while they were open to export opportunities, that was something for the future.They also plan to make similar machines to use with the Pfizer-BioNTech and Moderna vaccine.
Juthamas said the machine was aimed at removing burdens on health workers. Thailand has reported around 1.1 million Covid-19 infections and 10,085 deaths in total, pushing parts of the health system to the brink.
She said, “When the health workers are too tired, there are also chances of human error, so we should let the machines work on this” .