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Cellino, a company developing a platform to automate stem cell production, presented today at TechCrunch Disrupt 2021s Startup Battlefield to detail how its system, which combines AI technology, machine learning, hardware, software and yes, lasers! could eventually democratize access to cell therapies. It aims to bring down costs associated with the manufacturing of human cells, while also increasing yields.

Founded by a team whose backgrounds include physics, stem cell biology and machine learning, Cellino operates in the regenerative medicine industry. This space is currently undergoing a revolution, where new developments in gene and cell therapies could lead to breakthrough cures for a number of leading diseases. For example, the use of personalized human retinal cells could be transplanted to halt or reverse age-related macular degeneration, which can cause blindness. But today, such cell therapies are out of reach for most people because the process of cell production hasnt been automated or made scalable and efficient.

Instead, human cells being used now in these clinical trials are mostly being made by hand by scientists who are looking at cells and evaluating using their many years of training and expertise which cells are low quality and need to be removed. They then scrape away those unwanted cells with a pipette tip. The process, as you can imagine, is time-consuming and produces only a small yield. In this manual process, youd see a yield of about 10% to 20% of cells that would be able to pass the final quality assurance tests required for human transplant.

Cellino is working to improve this process in order to produce more cells of higher quality. Its goal is to push the yield to at least 80% over the next three years.

To do so, Cellinos system is automating all the human steps in the production process using machine learning techniques.

To identify which cells are high quality or low quality, the company is collecting large training data sets where its teaching algorithms to make determinations about cell quality based on a variety of factors. This includes the cell morphology meaning, the shape, size and density of cells. Fluorescence-based surface markers can also be used to identify other factors of importance to the line of cells being produced, like the location of proteins on the cell, for example.

By using machine learning and AI to do the identification based on standard and well-accepted biological assays used by the FDA, the system could move away from human annotation and the variability that introduces into the process of human cell production.

After Cellinos software has identified which low-quality cells need to be removed, it then uses a laser to target them. The laser creates large enough cavitation bubbles to kill the cell, but its done in a highly localized way where youre not harming the neighboring cells, as thermal heat does not dissipate to the nearby cells. This is also a more precise technique than the manual method. (Cellinos system has a 5-micron resolution, while cells are 10-15 microns in size). This results in a throughput of about 5,000 cells per minute, which is highly efficient compared with manual techniques.

Over time, this automation and efficiency could bring the cost down from nearly a million dollars per patient, which is what clinicians have to pay today to run a clinical trial, when outsourcing cell production. Cellino aims to get the cost down into the tens of thousands of dollars over time.

By scaling cell production, personalized cell therapies could also help a broader range of patients compared with other techniques relying on banks of stem cells. These arent always genetically diverse samples, leaving smaller ethnic groups out of the progress being made in this space. Banked cells also require recipients to take immunosuppressants, as the cells arent your own and the body may reject them.

The use of lasers is an idea developed by Cellino co-founder and CEO Nabiha Saklayen, who patented an invention in cellular laser editing while at Harvard earning her PhD in Physics. She was encouraged to turn the technology into a startup by her collaborators, who included had leading biologists like George Church and David Scadden.

Not all scientists become entrepreneurs, and I became an entrepreneur because I had an amazing support network around me, notes Saklayen, of the push to join the startup space. She immediately recruited Marinna Madrid, an applied physicist she had worked with for years on the co-invention of laser-based intracellular delivery techniques, as her other co-founder. To gain more mentorship about growing a startup, Saklayen turned to the Boston area startup ecosystem.

I didnt know anything about startups. I wanted to work with people who knew how to build companies, how to commercialize technology, how to build instruments and the Boston ecosystem is fantastic in that way. So I started connecting with lots of people in those early weeks anybody that was in the biotech realm or Harvard Business School, Saklayen explains.

This led her to Cellino co-founder and CTO Mattias Wagner, who had built companies before in the optics and instrumentation space.

Thats how the founding team came together. It was very complementary because Marina and I were co-inventors of the original technology that inspired the platform and Mattias brought this tremendous background in semiconductors and optical instrumentation, says Saklayen.

Since its 2017 founding, Cellino has gone on to raise $16 million in seed funding in a round co-led byThe Engine and Khosla Ventures, with participation from Humboldt Fund and 8VC.

The company is now collaborating with the NIH on compatibility studies. Currently, that means Cellino is making stem cells on its system which its then comparing with the ones made at the NIH that are already being tested in humans for personalized cell therapies for retinal diseases. Cellino later hopes to use its system to address areas like Parkinsons, muscle disorders and skin grafts, among others.

The company wanted to present at TechCrunch Disrupt to share more about what its building and to source new talent.

For me, its about talking about this idea around democratization and industrialization of cell therapies. I really want to get that message out because that is the movement we need to drive over the next decade for all of these cell therapies to be accessible to all patients, says Saklayen.

Cellinos angle is also very unique in the sense that, because we have this automated system to manufacture human cells, our system could make cells for every human being in this country, in the world, she continues. And there are a lot of cell therapy approaches that are looking to use off-the-shelf cells and off-the-shelf therapies, which will only work for certain parts of the population. As the U.S. becomes more diverse, ethnically, we need personalized solutions for everybody.

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Cellino is using AI and machine learning to scale production of stem cell therapies - TechCrunch