Danish startup is looking to help R&D teams automate lab experiments that require visual inspections, raising $20 million in a Series A funding round to scale its technology in the US
Recast, founded in Copenhagen in 2018, has developed a robotic imaging system full of software and artificial intelligence models to help scientists track visual changes — such as color or cell growth rates — from Petri dishes and similar dish formats. Its machines have a built-in incubator that can be set to specific temperatures, with corresponding data recorded to ensure experiments can be easily repeated.
The advantage is that these experiments can be performed 24/7 without direct supervision, freeing up technicians for other critical tasks.
The Reshape machine in action Image credits: Reformation
“Decoding nature”
The concept of ‘decoding nature’ is at the heart of what Reshape aims to achieve, building on a wider trend that has seen the lines blur between the natural and the built world. These opportunities have not been lost on Silicon Valley, as evidenced by the countless amounts of money being poured into technologies that seek to “engineer” biology..
“Biology as a whole is moving from a science to an engineering science, and I think one of the biggest things we want to do is do some of the very ‘intangibles’ – how does an object grow, how does it behave?” — easier to describe,” CEO of Reshape Carl-Emil Grøn he told TechCrunch. “Ideally, we want to understand how we make that translation layer between what’s happening in the real world and what’s happening in your DNA.”
The genesis for Reshape came when Grøn, who has an engineering background, started dating someone who worked in the biotech industry, giving him an insight into the amount of manual effort required in laboratory experiments.
“I just assumed that biotechnology was massively automated, but every eighth hour, every day, for five months straight, he had to go into the lab and take a picture of a Petri dish,” Grøn said. “When you’re from the tech world, it just seemed crazy.”
After speaking to a bunch of biotech companies at the Copenhagen site, Grøn realized his initial experience wasn’t some weird anomaly: The way labs sequence DNA, measure chemical compositions, and all the rest was happening more or less. the same way it has been done for more than a century.
So Grøn recruited two co-founders, Daniel Storgard and Magnus Madsenand begin building a full-stack platform, replete with high-resolution cameras and lighting, to capture visual data points and timing errors and record how different components in a given experiment react to the conditions they are subjected to.
Under the hood
Reshape develops its own AI models, trained on internal data in its own lab, and these can work from scratch for some of the most common types of experiments, such as those involving fungal or bacterial hosts or seeds and insects. But the company can also help its customers train models for specific use cases, such as tracking how specific microbes behave under certain conditions.
“The Reshape data science team, using our custom build MLOps architecture, handles this end-to-end, starting with understanding the desired outcome and quantifying, annotating the required datasets at scale, developing and benchmarking models, and then deploying them into our product for our customers,” Grøn said.
An agricultural company, for example, might use Reshape to control seed germination rates or the severity of a particular disease. Or a food company might perform ingredient labeling to check quality, freshness, or how ingredients have matured over time—anything that typically requires visual assessment.
Growth was detected in the analysis. Image credits: Reformation
Some of Reshape’s customers are using the platform’s technology to transition from chemical to biological pesticides — basically, figuring out which new compounds work best and documenting how to make them. And speed is ultimately the main appeal for customers.
“They’re going to be doing four to ten times more experiments than they could before, which just means they’re getting products to market much, much faster,” Grøn said.
Reshape makes results available for viewing in a cloud-based interface, but the platform also supports data exports in formats such as LIMS or CSV, allowing users to transfer their data to other biotech software such as Benchling or even just in Excel.
Results are presented through a cloud-based interface. Image credits: Reformation
In terms of accuracy, Grøn says he compares the underlying models to a human’s performance in the same experiment, covering metrics like false negatives. This helps avoid scenarios where an experiment might otherwise have been stopped because the scientist deemed the experiment ineffective.
“We help with about an 80% reduction in false negatives,” said Grøn. “We also help our customers reduce the time it takes to get a result. And instead of relying on remembering how you did an experiment a few years ago, we track it perfectly. So every time you run an experiment on the platform, we track it. Repeatability is extremely important.”
In terms of business model, Reshape sells the complete platform as a subscription, which includes the hardware, machine learning and underlying software. Pricing is charged on a “value-based” pricing model, which may differ for each customer.
Currently, Reshape only ships one machine size, which means that if a customer has multiple experiments, then they must purchase multiple machines. So to scale this up to giant, industrial-grade experiments, Reshape might need bigger machines. Grøn remained somewhat coy on the matter, but suggested that they might “port” to larger devices in the future.
Reshape rendering engine. Image credits: Reformation
Development
A graduate of the Winter 2021 batch of Y Combinator (YC), Reshape has amassed a pretty impressive list of clients, including the Swiss agritech giant Syngenta and the University of Oxford. With another $20 million in the bank, next one $8.1 million seed round last yearReshape says it plans to use the fresh cash injection to scale its US operations, where it says about two-thirds of its revenue already comes, albeit mostly from its European customers’ US facilities.
“We’ve proven our technology works – now it’s about scaling it up and helping as many labs as possible accelerate the biological transition,” Grøn said.
Others are also bringing automation to science labs, including London’s Automata, which raised $40 million last year to target the broader lab workflow. And some companies offer something similar to what Reshape is trying to do, such as PhenoBooth by Singer Instruments and Interscience’s ScanStation.
However, by providing a full-stack platform with end-to-end data management that’s good right off the bat, Grøn believes that’s what sets Reshape apart.
“This is an expensive problem that many companies have been trying to solve for a long time,” Grøn said. “We provide incubation, imaging and analysis in a closed-loop system. Our pre-trained models are ready out of the box and require no time-consuming training.”
Reshape’s Series A round was led by the European VC firm Astanor Ventureswith participation from YC, R7, ACNE, 21st Bio and Unity co-founder Nicholas Francis.
