A bioprocess startup that uses fly larvae as mini-bioreactors is hoping to speed up its protein engineering pipelines by spreading its expert workforce across two continents.

Proteinea, which joined San Francisco’s IndieBio accelerator in February 2021, has based 15 of their 20-strong team in Cairo to take advantage of lower costs to build a talented team.

“We have a bigger team in Egypt than [we could hire] with the same budget in the United States,” explains Mahmoud Eljendy, co-founder and CEO of Proteinea. “Having a big team at this early stage, we can run more experiments, and iterate our products and business model faster.”

Team members also have diverse backgrounds ranging from aerospace engineering to bioinformatics and insect genetics, he says.

Eljendy likens the benefits of the larger, more diverse team to playing Grandmaster Chess—where the winning strategy is to make two moves while another player only has one. “Speed is everything,” he says, especially in the fast-moving biotech market. Among the benefits is running more experiments at the same time—a traditionally time-consuming part of biotech development.

The company, which has its IndieBio demo day in mid-July, is using the IndieBio lab space to get technology advice, along with running experiments, mentoring, and business coaching from the IndieBio team. Their business model is based on using insect larvae as mini-bioreactors, which they hope will cut the costs of protein manufacturing by up to 90%.

As Eljendy explains, fly larvae are easier to scale up than using single-use or stainless bioreactors, as processes in a single larva should occur similarly in millions of others. Unlike cells cultured in a bioreactor, larvae also need minimal protection from contamination and don’t require culture media to grow.

The fly larvae are Proteinea’s production platform for five protein engineering projects with pharmaceutical and academic partners. These projects focus on antibody and vaccine production for human and animal use.

“Starting with an antibody, we’re using our proprietary deep learning model as a very cheap, fast method to make better candidates in silico, before lab testing and producing the final candidates in our larvae system,” Eljendy says.

The company expects to move its first product, an animal vaccine, into clinical trials in the near future.

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