HomeNewsSpore.Bio Secures $23M for Machine Learning in Microbiology Testing

Spore.Bio Secures $23M for Machine Learning in Microbiology Testing

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Recalls in the food and beverage industry due to contamination incidents can lead to severe repercussions. Companies not only face financial penalties and damages but can also suffer long-term impacts on their brand reputation.

Spore.Bio, a deeptech startup based in Paris, is aiming to transform microbiology testing to help prevent the next public relations crisis in the food industry. Having raised €8 million in a pre-seed round (equivalent to approximately $8.3 million at current exchange rates) slightly over a year ago, the company has recently secured a $23 million Series A funding round.

The Series A round is led by Singular, with participation from Point 72 Ventures, 1st Kind Ventures (the family office of the Peugeot family), Station F, and Lord David Prior. Existing investors LocalGlobe, No Label Ventures, and Famille C have also increased their investment in the company.

Spore.Bio was able to raise additional funds quickly after its pre-seed round due to genuine customer interest. The startup has already secured several commercial contracts that cover up to 200 factories. Consequently, a waitlist was opened to manage the demand.

What distinguishes Spore.Bio’s technology is its ability to deliver rapid results in an industry where microbiological tests traditionally require several days. Normally, companies must collect samples and send them to specialized laboratories for testing.

As described by co-founder and CEO Amine Raji in an interview with TechCrunch, while most industries are highly optimized with processes measured in minutes, the food, pharmaceutical, and cosmetics industries often require lengthy incubation periods—five days in food and 14 days in pharmaceuticals and cosmetics—due to the need for bacteria to grow during testing.

Conventional testing must occur offsite to avoid contaminating other factory areas, given its reliance on multiplying potential bacteria in petri-dishes—a process that also prolongs the incubation time.

Spore.Bio employs a different approach by using specific wavelengths of light directed toward a sample and recording its spectral signature. A pre-trained deep learning algorithm then determines the presence of bacteria or pathogens in the sample.

Spore.Bio’s primary asset is its model, which benefits from a partnership with the Pasteur Institute, allowing access to its biobank of bacterial samples.

In the coming months, Spore.Bio plans to manufacture testing machines for customers to use directly at their facilities, enabling onsite microbiology testing. The company asserts that this could reduce the overall testing process from several days to mere minutes.

Before founding Spore.Bio, Raji was a food and beverage manufacturing engineer with Nestlé, naturally gravitating towards an industry he was familiar with. However, microbiology testing appears to be a broader field than initially expected.

Cosmetic product manufacturers have also shown interest in Spore.Bio’s technology. Raji noted that manufacturers face pressure to eliminate preservatives due to consumer demands and environmental concerns, although these preservatives are crucial for killing bacteria.

Similarly, the pharmaceutical sector has identified a use case for the technology in innovative therapies, such as gene and cell therapy. Raji explained that these treatments often have a very short shelf life, sometimes as little as seven days, preventing them from undergoing conventional testing procedures.

With the latest funding round, Spore.Bio intends to significantly expand its team, increasing from 30 employees currently to 50 by the end of 2025.

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