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Are You AI-Ready for Drug Discovery?
To Our Customers,
Data has long been hailed as the way forward—the way to overcome declining returns and long innovation cycles. We have decades of R&D data available to guide data-driven research. Technology advances have delivered new data and insights around disease processes, drug targets, and novel treatment entities. Ever-increasing computational power has made it possible to apply all this knowledge and data to build and inform advanced technologies like AI. We have everything we need to make the next great breakthroughs faster. There is just one immense problem—the data. Sometimes it feels like it is everywhere and nowhere at the same time. Sometimes it feels like 1s and 0s, bites and bits, and cells and atoms get jumbled into a veritable bowl of scientific data soup.
As technology has advanced, we’ve heard from many of you, our customers, that this has created more pains associated with the vast amounts of data now in your labs. Specifically, in my conversations with you, I’ve heard you share some of the following:
Varied data producers – Data typically floods into labs from a wide range of sources, such as instruments, animal and clinical studies, material registries, different scientific systems, and even ELNs including our own. While having that data is good, all that data must be collected, organized, modeled, analyzed, and rendered before scientists can use it to advance their research. When teams don’t have an easy way to automate as many of these steps as possible, time that could be spent exploring is instead lost to data handling. Breakthrough connections that could be made are lost in the noise.
Isolated instruments – Data acquisition from all the various instruments used across labs can be particularly challenging because outputs are often encrypted, in vendor-specific formats, or non-file based; as a result, lab IT gets stuck managing various scripts for parsing out descriptive metadata and experiment results, aligning data outputs from different instruments, and creating models to make data useable.
Diverse scientific applications - Different disciplines working across an organization need speciality applications to support their work, but those applications generally employ their own unique design patterns and data models, making them difficult to integrate. This creates a huge barrier to sharing data and advancing research through collaboration.
High data volumes and data silos - With technology advances, scientific data has been increasing at an exponential scale for years. Your goal and ours is for the increasing volume of data to translate into even more opportunities for innovation. Unfortunately, too often you’ve told us that this simply isn’t the case when data are too abundant and disparate to actually use. Many teams struggle with data that are trapped in silos, inaccessible for wider use, and not machine-ready for advanced analytics like AI. And as the data silos fill, the costs are growing.
No self-service, ready-to-use data - In many labs, scientists don’t have easy access to the data they need. They may have to request datasets from already overburdened data scientists or lab support. Or, they might resort to cumbersome workarounds, manually piecing together data from different sources. And even when they have their desired data, they often face more work preparing it for use because it isn’t properly standardized, formatted, or otherwise ready for advanced processing or enrichment activities.
It’s time that we do something about these challenges. You’ve succeeded quite frankly in spite of the ongoing data wrangling challenges you face. But I believe there is more that Dotmatics can be doing to help you address what might feel at times like a disconnected data technology infrastructure and inefficient data management process. Data management is now, more than ever, a huge obstacle. And until this obstacle is overcome, everything suffers—efficiency, collaboration, ROI, and, ultimately, innovation. But I believe Dotmatics can help with an entirely new platform built to address these issues.
Introducing Dotmatics Luma—a revolutionary scientific-data platform
Today we are excited to announce Dotmatics Luma, our new scientific data platform that helps scientists and administrators unify and analyze large volumes of diverse scientific data for better decision-making. Luma ™️ provides an out-of-the-box, low-code, SaaS platform that flexibly aggregates all relevant data into intelligent data structures. This enables clean, reliable data analysis and paves the way for meta-analysis and AI- and ML-based algorithms. Luma helps companies circumvent all the most common obstacles they might face when trying to digitize their labs and attain better access to all their data. With Luma, companies can create technology infrastructures and data processes that optimize R&D efficiency and support collaborative, data-driven innovation.
Luma delivers:
Luma Lab Connect instrument integration (built off the former BioBright technology)
Centralized and standardized data repository
Self-service data access
Low-code application building
Flexible data modeling and governance framework
API-first data access
Our first component of Luma is focused on addressing the instrument-specific challenges that labs are dealing with today. Using Luma Lab Connect, customers can ingest files from any file-based instrument into the Dotmatics cloud. The Luma Lab Connect parsing engine automatically parses files to extract and wrangle embedded descriptive metadata and scientific data with minimal configuration. Agents are remotely managed, monitored by Dotmatics for stability, and require no configuration beyond instructions on which directories to watch for new data. The data is then automatically made available for modeling and enrichment within the broader Luma Platform.
During the coming months, our ongoing development of Luma will expand with the creation of many scientific tooling extensions—created with many of our Dotmatics family of applications— that will address specific use-cases for our customers’ benefit.
To learn more about Dotmatics Luma visit Dotmatics.com or contact your account representative.
I can’t wait to show you more of what we have planned in the months and years ahead! Thank you for letting us be your partners in innovation.
Thomas Swalla
CEO, Dotmatics
Cautionary Note Regarding Forward-Looking Statements
This post contains forward-looking statements that are intended to outline our general product strategy. It is intended for informational purposes only and speaks only as of the date they are made. It is not a commitment to deliver any functionality and should not be relied upon for making purchase decisions. You should not put any reliance on these statements.The development, release, and timing of any products or capabilities remains at the sole discretion of Dotmatics. No representation or warranty, express or implied, is provided in relation to the fairness, accuracy, correctness, completeness or reliability of the information, opinions or conclusions expressed herein.
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