Advances in DNA sequencing and the vast amounts of genomic data being generated by next-generation sequencing (NGS) technologies have created opportunities for startups to build software to make it easier for biologists to analyze this big data and take it to the next level. Yes. It could help develop new vaccines, cancer treatments, and more.
For the past four years, MiLaboratories, a San Francisco-based startup with R&D facilities in Bilbao, Spain, has been building a computational biology platform to make it easier for biologists to process, analyze, and aggregate data. Increase usability by incorporating features such as data visualization and generative AI.
The platform is also designed as a marketplace for other scientists to distribute more specialized computational tools in app form, continuing to expand their usefulness to the genomics research community. MiLaboratories targets so-called bioinformaticians, whose skills span biology, computer science and mathematics.
“It’s a ‘no-code’ style approach for biologists. and We are also releasing an (open source) software development kit (SDK) to enable bioinformaticians to build real-world applications,” CEO Stan Poslavsky told TechCrunch.
“During my scientific career and that of my founders, we have seen enormous inefficiencies. . . It explains modern treatments, how modern drugs are developed,” he explains. “It’s because of the friction between the data (big data, sequencing data generated by biologists) and data analysis that they can’t use.”
There are thousands of software programs and tools that can perform NGS data analysis, but most have been developed within academia, which tends to focus on utility rather than usability, he says.
Biologists also need to synthesize and integrate results from multiple analyses, he said. “An integrated picture allows us to understand what is happening. And this is where our platform helps dramatically,” he suggests.
The startup says its platform frees bioinformaticians from having to deal with the tedious task of processing genomic data, allowing these interdisciplinary scientists to apply their skills to more complex tasks building algorithms that can help advance cutting-edge science. I hope I can do it.
“Bioinformaticians actually spend a lot of time doing the monkey-like job of running software for biologists,” says Poslavsky. “Processing this data requires having a Linux system and running complex software tools over SSH to complete analysis and gain insights from the data.”
“(Doctors) don’t have the skills to do this on Linux, HPC (high-performance computing) clusters because they have other things to do. And this is what most bioinformaticians in business and academia are actually doing. “It’s actually about running the tool every month.”
On Thursday, MiLaboratories officially released Platforma.bio, an SDK that allows third-party developers to contribute apps. Although it has been in alpha and beta testing for several years. (Poslavsky says “about 300 labs” are using the beta version and “about 20” apps have been made available through the platform so far.)
“The first applications available on the platform are built on very popular biology and bioinformatics applications. . . (Together) Companies and people involved in immunotherapy development. But we already have . . . “There are a variety of collaborations and people willing to bring applications to the platform, both in academia and industry,” he added.
The startup, founded in 2021, also announced a $10 million Series A funding round to continue development with a focus on investing in community building.
“The main reason for raising funds is to involve more people in the development of our platform. We’re hiring more engineers. Because most bioinformatics software is developed in academia, we hire developer advocates who spread the technology primarily around academia.”
“The upcoming year will be focused on spreading the technology around the community and engaging the community to build apps, wrapping existing software and delivering it through our platform,” he added.
MiLaboratories’ Series A is led by Madrid-based Kfund, with participation from Acrobator Ventures, EGB Capital, Courtyard Ventures, Somersault Ventures, Speedinvest and Ten13.
Miguel Arias, general partner at Kfund, said in a statement: “Investing in platforms that bridge the gap between developers (in this case bioinformaticians) and business users (in this case biologists) is at the core of what we want to do. From our fund. “There is tremendous potential in democratizing access to complex data to provide immunological insights.”
MiLaboratories provides its software for free to academics, but also monetizes commercial users through a paid model. According to Poslavsky, the startup is approaching 100 paying customers at this stage.
“Many large pharmaceutical companies such as Moderna and Bristol-Myers Squibb are our customers,” he adds. “We are profitable. We generate good returns so we don’t have to rely too much on venture capital.”
In early 2022, the startup raised a seed round of $2.5 million. We also previously took a small pre-seed from some angels.
Speaking about the challenges of developing a computational biology platform, Poslavsky said the sheer volume of data generated by NGS means startups must pay very close attention to ensuring processing efficiency to avoid incurring “enormous costs.”
“The amount of data being generated in space is actually enormous,” he emphasizes. “Big pharmaceutical companies, our customers. . . They have petabytes of genetic data ever generated. So the scale is enormous.”
MiLaboratories has developed “highly sophisticated” and “mathematically proven” technology that allows Poslavsky to perform many different kinds of calculations in a “highly optimized way.” He suggests that this patented technology allows the platform to achieve ten times the efficiency of other types of computing workflows.
“That is very important. Hidden from the biologist’s eyes. For a biologist, a valuable proposition is ‘I want to click a button and get insight.’ “But it’s very important for business owners.”
In terms of competition, Poslavsky cites Seqera (and Nextflow software) as its closest competitors in terms of popularity and value proposition. There are also open source tools for NGS processing, such as Galaxy, but MiLaboratories believes its platform provides researchers with a more accessible path to data insights.
