Science, at its core, is collaborative.
The essence of scientific work is building on other sciences – think of all the research and discovery that would never have happened otherwise.
However, scientists, like other professionals, can work in silos. Their jobs are complex, cyclical, time consuming, often messy, often repetitive. And while the value of AI and machine learning (ML) is undeniable so far, the accumulated data is probably more than human can analyze.
Code Ocean seeks to help scientists return to the basics – for themselves and for humanity. The company has developed its first-of-its-kind, computational-research laboratory SaaS platform for scientific collaboration and discovery. This technology enables scientists across all disciplines to standardize workflows and track and reproduce calculations and discoveries.
Simon Adare, CEO and co-founder of Cornell Tech-Incubated, said the project was a collaborative initiative, announcing a $ 16.5 million Series B funding round today.
Accelerate the search for biomarkers
The “essential trinity” of any computational research work is the code, data, and results. According to Adar, the core of Code Ocean is its trademarked compute capsule, a container technology that incorporates reproducible, archival and executable versions of experiments, thus combining the essential trilogy.
Easy-to-use automated lab allows researchers to reproduce, reuse, and share computational experiments. The capsule also helps ensure that experiments can be preserved and reused in current and future research, the agency explained.
“It democratizes computational science, giving researchers the freedom to explore a wide variety of scientific questions,” he said.
In the case of the Princess Margaret Cancer Center in Toronto, that permanent question has been around biomarkers.
Princess Margaret Senior Scientist Benjamin Hebe-Caines explains that these biological molecules are important in drug discovery. But there are many ways to suppress genes, so delicate balance is looking for chemical ingredients that kill cancer without negatively affecting normal cells. And the largest number of people possible.
Because both cancer and the human body are extremely complex, it is rare for a single chemical to help treat cancer in everyone. For example, certain chemicals can work in only 10% of the population. Researchers are constantly analyzing it to find the best home remedies, Hebe-Keynes explained.
“There’s a lot of heterogeneity,” said Haibe-Keynes, an associate professor in the Department of Medical Biophysics at the University of Toronto. “Every cancer is very unique.”
Increasingly, researchers are using AI, algorithms and deep neural networks to help make connections. But just like an enterprise where cloud computing has become a commodity – and processes like DNA sequencing have become infinitely faster – that means pileups into unsolicited data.
With platforms like Code Oceans, Heibe-Keynes pointed out, scientists can now focus more on that discovery, and work collaboratively to develop and share teaching and industry research and methods.
A parallel challenge in industry and academia, he said, is the struggle to run projects in departments or even individual labs, as scientists need a platform so they can reuse each other’s research instead of constantly rebuilding it. Each iteration.
“Every piece of code that has value should be transferable,” said Heibe-Cannes. “You can free each other’s work.”
Princess Margaret was one of the first users of the Code Ocean platform and was described by Haibe-Keynes as a “field agnostic”. “It addresses the basic needs of any researcher, whatever the topic.”
He added, “The hope is that not only will each paper be reproduced, but it will also increase the way people communicate internally before the paper is published.” You can accept fertility even before publication.
Adar agrees that a consistent, automated virtual lab is “completely complex” for today’s science. Recipients of the Runway Postdoc Award at the Jacobs Technion-Cornell Institute began working on Code Ocean at Cornell, and previously collaborated with DLR – Environmental modification from airborne and spaceborne sensors to the European FP7-funded EO-MINERS project.
“Computing has given us a much wider range of motion and, at the same time, dramatically increased complexity,” he said. “In order to advance computational science at a faster pace, access to high-performance computing must be made easier for scientists to maximize security, seamless collaboration, and advance in the marketplace.”
Code Os started its first project in 2017 and released its enterprise version two years ago. Its platform is used in emerging fields of biology, biopharma, chemistry, genomics and computational science, such as AI-powered medicine R&D. The company has customers in SEMA4, Champions Oncology, Cytorizion and Dragonfly Therapeutics as well as startups.
The platform is built on the concept of open science, which allows for easy migration of code and data across the platform, and it automates the work of Docker, Git repositories, Nextflow and other open-source technologies, Adar explained. The language is agnostic and includes cloud workstations for RStudio, Jupyter, Terminal, MATLAB, Shiny, Git and others. It is available in both the Enterprise Edition and the free public platform for scientific developers and authors.
The funding round has been led by Battery Ventures and M12, Microsoft’s Venture Fund, and will be used to build a team of Code Oceans, Adar said.
The funding is based on a significant partnership with Lantern Pharma. The Code Ocean platform will power AI-powered computational research for the discovery of oncology-focused medicine in clinical-stage biopharmaceutical companies. As Panna Sharma, President and CEO of Lantern Pharma, explains, the company’s scientists, researchers and data engineers need a highly secure, collaborative environment to make reproducible science. “Code Ocean’s digital lab has been an ideal environment for our scientists and engineers to design and scale our proprietary AI for drug discovery,” said Sharma, “because it allows them to develop, document and share ideas faster and more efficiently.” Giving.”
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