Cellino’s unique blend of lasers and machine learning is transforming the manufacture of autologous stem cell therapies from an inconsistent hand-crafted endeavor to a scalable, efficient, closed-loop, modern process.
Cellino Biotech’s unique blend of lasers and machine learning is transforming the manufacture of autologous stem cell therapies from an inconsistent hand-crafted endeavor to a scalable, efficient, closed-loop, modern process.
“We live at the convergence of three distinct disciplines – laser physics, artificial intelligence (AI), and stem cell biology,” Nabiha Saklayen, Ph.D., CEO of Cellino Biotech, told BioSpace. “We’re the only company taking this convergent approach, and that convergence lets us produce stem cells in a scalable way for the first time.”
Cellino uses image-guided machine learning to characterize the highest quality stem cells. This delivers more consistent results than the traditional method in which scientists select cells by direct observation, she explained.
“Then we use an AI-driven laser system we trained to recognize the best cells and to edit away the unwanted cells,” Saklayen said. “We generate bubbles around the cells, and open and lyse them. Lasers are extremely precise...so we can remove individual cells.”
Altogether, this combination of consistency, selective cell removal and automation makes the system very compelling.
“We are building the technology so it operates in a fully-closed format,” she added.
That advance reduces the risk of contamination because cell containers needn’t be opened multiple times during processing. Closed manufacturing also means that high-grade clean rooms aren’t needed, thus reducing manufacturing costs.
The manufacturing platform is still being perfected, Saklayen pointed out.
“So far, we have trained the AI algorithm and automated the laser editing process for manufacturing. Our goal for this year is to show that our platform can produce high-quality, research-grade stem cells with no human handling,” she said. When that occurs, “We will be the first in the world to demonstrate a fully-automated, closed loop process to manufacture autologous iPSC-derived cell therapies at scale.”
The idea for AI-enabled approach to stem cell manufacturing was, itself, the result of convergence.
“I completed my Ph.D. in laser physics at Harvard University, and was interested in biological problems, too. I had the opportunity to collaborate with some incredible biologists at Harvard Medical School and Harvard Stem Cell Institute,” Saklayen said. “That was when I first started to understand that having a very precise way to edit cells could be transformative for stem cell technology. My collaborators were very enthusiastic and encouraged me to explore the idea further.”
With that encouragement, Saklayen launched Cellino with two co-founders and engaged with leaders in the world of regenerative medicine to better understand the challenges they were facing.
“Most groups have one or two scientists who trained (to select optimal stem cells) their whole careers, using pipettes to manually scrape away unwanted cells. When they were ready for clinical production, the scientists would move to a clean room and make 10 to 20 doses of autologous stem cells by hand,” she recounted.
With that model, the lack of scalability made large, global trials of autologous stem cell therapies virtually impossible.
Bringing a multi-disciplinary approach to the manufacturing challenge made Cellino’s scalable, automated solution possible.
“There’s a theme of convergence throughout the industry, as experts are starting to build relationships and collaborate (with others outside their fields).” Consequently, she said, “You build unexpected solutions. The (necessary) technologies are ready to be used and merged.
“We want to live in a world where it’s possible to make therapies derived from our own stem cells and tissues, because they don’t require immunosuppression,” Saklayen continued.
To realize this goal, Cellino is pursuing collaborations with cell therapy developers to help the entire industry move programs through the clinic very quickly.
In the process, she said, “We are coming across very interesting cell types that are perfect for autologous applications – skin and hair, for example – but that haven’t been commercialized because developers were concerned about manufacturing challenges.” Cellino is evaluating some of these cell types and finding creative ways to bring them forward so they may be of value in the regenerative medicine space.
Last month, the company’s first peer-reviewed paper was published in Current Protocols. It was, Saklayen said, the first review of cell therapies derived from autologous induced pluripotent stem cells (iPSCs). As it concluded, iPSCs are a standardized starting material for the development autologous cell therapies that could enable the therapy “to be used to treat all patients – not just those covered by HLA haplobanks…proving relief to the many individuals suffering from incurable degenerative diseases.”
Cellino will be integral in bringing that goal to fruition. It has raised $16 million in seed financing in February.
The young Cambridge, MA company is hiring, too. Saklayen is looking to bring on exceptional candidates in many areas, including biology, AI, regulatory affairs and software engineering to grow a diverse, multi-disciplinary team of stem cell biologists, optical engineers, physicists, automation engineers, and machine learning engineers to automate the future of cell therapy manufacturing.
