Closely held Dotmatics is transforming the therapeutic research and development landscape with Luma, a groundbreaking solution in multimodal data management with the potential to address long-standing scientific challenges, including data silos, inflexible workflows, increasing costs, and inefficiencies.
“As leaders in the scientific software space, we leveraged Dotmatics’ best-of-breed scientific tools to create Luma, a new paradigm platform specifically designed to tackle the pain points and bottlenecks scientists face in the lab,” Mr. Christian Olsen, Associate VP at Dotmatics says in an interview with BioTuesdays.
Mr. Olsen explains that the company, comprised of talented scientists, originally focused on the scientific process behind small molecule drug discovery, has expanded under the Dotmatics umbrella to offer a suite of widely used scientific software tools. These tools enable researchers to analyze and visualize data throughout the drug discovery process. “Scientists love these tools, but as new technologies emerged, we saw an opportunity to bridge critical gaps and create a new paradigm—Luma— empowering users to be more agile, efficient, and capable of achieving more than ever before.”
Launched in June 2025, the Luma platform offers multimodal registration, adaptive workflows, unified results and configurable dashboards, a custom app builder, and AI and machine learning (ML) capabilities. “Luma can represent virtually any scientific entity with high precision, adapt to diverse workflows, and facilitate seamless data transfer,” Mr. Olsen says.
“Since COVID-19, therapeutic research has undergone a dramatic shift from traditional small-molecule approaches to a diverse array of modalities, including multi-specific antibodies, RNA-based medicines, cell and gene therapies, and combination treatments,” he adds.
Mr. Olsen notes that historically, bringing a new drug to market takes up to ten years and costs approximately $2.5 billion. AI is revolutionizing that process by shortening the drug discovery pipeline and dramatically reducing costs.
“This evolution has introduced unprecedented complexity in data management, as researchers must now navigate an expanding universe of therapeutic modalities and increasingly data-dense testing capabilities. As a result, long-standing productivity challenges have been exacerbated.”
Highlighting the challenges that research scientists face today, Mr. Olsen points to several persistent issues, including: siloed data that hinders cross-functional collaboration, integration challenges that prevent a unified data ecosystem, scalability limitations due to growing data volumes, data standardization issues that complicate sharing and analysis, rigid legacy systems that struggle to adapt to evolving methodologies, high maintenance costs associated with multiple legacy platforms, limited AI/ML capabilities in older systems, and the lack of an advanced digital infrastructure.
“The Luma platform addresses all these challenges with low-code configuration, ontology-driven architecture, AI-assisted analysis, and a user-friendly interface, enabling scientists to rapidly evolve the system—reducing implementation times from months to mere days or weeks.”
“By solving core challenges in data integration and workflow flexibility within multimodal therapeutics research, Luma has the potential to significantly accelerate the pace of drug discovery and development,” he adds.
Beyond drug discovery and disease treatment, the Luma paradigm extends into chemicals, materials, and agriculture. Mr. Olsen emphasizes that Luma is designed for any research problem, including global health challenges such as food security and water quality. “Imagine the impact on global health if we could dramatically accelerate the breeding cycle of a critical crop,” he suggests. “For example, cassava in Africa has a five year breeding cycle—if we could shrink that down to one year, we would potentially change the game in terms of feeding the world.”
He adds that Luma mirrors scientific research and development workflows, ensuring researchers have access to the right data at the right time, structured precisely to fuel innovation. By reducing costs and increasing efficiency through adaptive workflows, Luma enhances accuracy with real-time data integration, eliminating hours of manual data transfers between systems via automated instrument integration. It also boosts ROI, scales technology investments, and delivers faster insights throug AI.
“AI excels at detecting patterns in vast data sets that we would never find on our own. Luma not only enables this but also allows retrospective searches—helping researchers reanalyze past data, unlocking new opportunities,” Mr. Olsen contends.
“We call Luma a ‘Lab-in-a-loop’ because it powers the entire process—design, make, test, and decide. Every time a scientist sees it for the first time, you can see the light bulb go off. They tell us that this is exactly what they’ve been searching for,” he adds.
With millions of scientists and thousands of companies already using Dotmatics’ software for scientific research, Mr. Olsen believes Luma will scale rapidly.
Looking ahead, he says, “This is a very exciting time for us. I anticipate we’ll gain a lot of very interesting customers very quickly—user groups across organizations and institutions that are deeply embedded in the research process for patients, large and small pharma, biotech, and agritech—all engaged in advancing science. Wherever research is happening, you’re going to find Luna.”
Reflecting on the company’s momentum, he quips, “I can already see the tidal wave coming at us—and I’m thinking we need a bigger surf board.”
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