UMass Chan School of Medicine has licensed its bioinformatics data processing and analysis technology to Via Scientific Inc. for commercial development. Developed by UMass Chan researchers Alper Kucukural, Ph.D., and Manual Garber, Ph.D., and colleagues in the UMass Chan Bioinformatics Core, the software platform is a flexible and scalable web-based bioinformatics system that enables biomedical researchers to analyze bioinformatics to perform complex analyzes of very large data sets from multiple experimental samples. The software, called Foundry, lets researchers automate much of the intensive bioinformatics work, such as validating and organizing data or writing new code, so they can focus on interpreting scientific data and research.
“The advent of high-throughput technologies that generate large amounts of data, such as next-generation sequencing, has undoubtedly increased the volume and complexity of data available to researchers,” said Dr. Kucukural, Associate Professor of Molecular Medicine, Co-Director of the UMass Chan Bioinformatics Core, and Co-Founder of Via Scientific. “Access to scientific data is no longer the bottleneck. Instead, the limiting factor for scientific discovery has become the processing and interpretation of these fixed datasets that currently require extensive computational expertise. As database structures and data processing tools and algorithms continue to evolve, only data It takes analytical experts to keep up. Thus, the new bottleneck for scientific discovery is the shortage of such experts. Furthermore, since there are no fixed standards for data analysis and many data analysts use their own code, it is often difficult or impossible to fully replicate Any published analysis.”
The platform was built by Dr. Kucukural. Garber, a professor of molecular medicine, a member of the Bioinformatics and Integrative Biology Program, and director of the UMass Bioinformatics Core, and colleagues allow researchers to offload much of the data processing to a modular and customizable software platform that requires no familiarity. low-level programming language.
“There are labs all over the world that generate massive amounts of data. The current model, which involves dedicated staff to offload the bioinformatics work, simply doesn’t scale,” said Garber, co-founder of Via Scientific. “Bioinformaticians are in high demand, which means recruiting is difficult and expensive.
“Additionally, we’re talking about jobs that are very difficult, time-consuming, and both data- and code-intensive. Scientists and bioinformaticians would rather focus on interpreting data and advancing scientific discoveries than being code experts and developing operations. Our software platform automates this process for scientists and puts them back in the lab.”
“Via Scientific’s mission arose from the setbacks and delays common in the data-intensive world of multi-omics research,” said Jim Crowley, Via Scientific CEO and co-founder. “It is a simple fact that existing tools are insufficient to tackle the multi-omics field. Time that could be spent interrogating experimental results, analyzing data, forming insights and improving understanding is spent wrangling data, writing code, etc.” Foundry All of that is eliminated so researchers and labs can focus on accelerating their science. We couldn’t be more excited about Foundry and our partnership with UMass Chan.”
“We are excited to bring Foundry to market,” said Dr. Melissa Moore, co-founder of Via Scientific and chief scientific officer emeritus of Moderna. “As a Fellow and Chief Scientific Officer of Moderna, I have seen first-hand the need for a powerful and adaptable tool like Foundry. Scientists are constantly challenged to keep up with our ability to ask questions and imagine possibilities. Foundry will’ Process time’ turns into ‘science time’ so science teams can focus on unlocking underlying science that leads to new insights and breakthroughs.”
The Via Scientific partnership is facilitated by Bridge Innovation and Business Development at the UMass Chan School of Medicine.
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