There's a pattern that anyone who works in pharma R&D will recognize within the Make-Test-Decide-Analyze cycle. A scientist runs an experiment, looks at the results, and makes a decision. Maybe a certain molecule gets deprioritized or a process parameter gets changed. The program moves on, and six months later another scientist working on a related molecule runs into the same problem. They search the system, and they may even find the original experiment, but what they often can't find is why the first scientist made the decision they did. So what do they do? They rerun the experiment.
Dotmatics is working to change that.
It's an important part of why Siemens has been named a Leader in the 2026 IDC MarketScape for worldwide Life Sciences Lab of the Future Technology Solutions and Consulting Services. Dotmatics plays a central role in connecting scientific R&D to what happens downstream.
The Full Stack, Finally
IDC’s MarketScape looks at how vendors are helping life sciences organizations build the Lab of the Future: that includes the entire digital thread from connecting R&D to tech transfer to manufacturing.
Siemens is able to bring those pieces together in a governed workflow for life sciences companies. Dotmatics provides the scientific intelligence layer, connecting the work happening in discovery and development with the processes that ultimately support manufacturing.
Scientific data is every life sciences organization's currency. There is no lack of data, and in many cases the data volume and diversity are what become challenges. That's because most organizations have a shortage of accessible context for the massive data. The reason a compound was dropped might be buried in an ELN entry, or the rationale for a process parameter might live in a presentation from a project meeting. Someone's explanation of what they tried three years ago might be sitting in an email thread, or simply in the memory of the lead scientist.
Traditional LIMS and ELN systems have been essential for capturing experimental results and maintaining the required records, but capturing a result isn't the same as capturing the conclusion a scientist drew from it.
Dotmatics Luma, the AI-native Scientific Intelligence Platform, connects lab instruments and scientific applications into a structured, centralized layer for R&D, serving as the first step in Siemens' ability to connect the entire digital thread from molecule discovery to manufacturing. Luma is designed to capture the data and the context around it so that scientific conclusions can be found and used later, especially with AI systems that need more autonomy to build on it. That scientific backbone carries meaning across every stage—from discovery and development through tech transfer and into manufacturing—so the reasoning behind a result doesn't stop when it reaches the next team. Luma supports multimodal drug development, team collaboration, and connected data across research and production. It's built to be open, integrating with third-party systems so data moves wherever teams need it.
A Real Example
Process development capabilities support interactive, real-time data capture during experiment design and execution, helping organizations establish FAIR data practices from the beginning of the workflow. The result is a different kind of scientific record: one that can tell you not only what happened, but provide the context needed to understand the who, what, when, why that went into it.
Novonesis used Riffyn X (now part of Luma) to break down data silos and integrate experimental data capture across different workflows. The result was a reduction in experimental data acquisition and processing time from hours to minutes, an estimated 50% reduction in employee time spent on those activities, and, for some market segments, a halving of time to market. Most importantly, it meant that Novonesis created an infrastructure that made contextual information easier to capture, connect, and use to expedite future growth and breakthroughs.
Connecting the Lab to Manufacturing
The sheer number of specialized systems involved in life sciences is challenging, where a tool that works well for scientific exploration isn't designed for process control or a system built around regulatory traceability isn't where a scientist wants to search for an insight from an experiment conducted two years ago.
The answer is making the systems work together. Dotmatics anchors the scientific R&D and intelligence layer, while Siemens brings its expertise in automation and manufacturing, including Enterprise Recipe Management aligned to ISA-88. Tech transfer is the stage where process knowledge has to survive translation from lab scale to commercial scale, and it’s where most digital threads break. Luma's scientific backbone keeps it intact.
The objective is to allow process knowledge to seamlessly move from lab-scale development through tech transfer and manufacturing.
There's Still Work to Do
Connecting a broad technology portfolio across a large life sciences organization is immensely difficult. But the long-term opportunity is crystal clear: the first time a scientific decision takes three months, the organization should learn something from it. The second time, it shouldn't have to start over. That's the promise of a connected Lab of the Future, and Dotmatics is thrilled to play a critical role.
Interested in how Dotmatics approaches structured data capture across R&D and process workflows? See how the Luma platform is built for AI from the ground up.