July 17, 2023 PAO-07-23-CL-06
Christian Olsen (CO): We’re a scientific R&D software company that is working with our customers to connect science, data, and decision-making. We’re used by two million scientists and 10,000 customers, and we’re working with them through our cloud-based platform and applications to help make the world a healthier, cleaner, safer place to live.
We are firmly ensconced within the R&D world, with a focus on three primary domains: biology/biologics, chemistry / small molecule pharmaceuticals, and chemicals and materials. The scientific platform has three main components, including an electronic lab notebook (ELN), a data management system, a high-throughput screening solution, as well as instrument integration —all of which support these three domains.
On the biology side, we support companies who are deriving therapeutics from biologic materials, regardless of whether they are using bacteria, yeast, or mammalian cells for that discovery work. As a data-centric company, Dotmatics is also technology agnostic; it doesn’t matter what hardware companies use or which vendors they work with.
The Dotmatics scientific platform comprises a host of scientific tools that are tightly integrated with the core ELN, data management, and screening modules and are used for different dimensions of research. For biologics, they are sequence-based, flow cytometry (FC)-based, and mass spectrometry (MS)-based. Those three very distinct and unique data types inform decision-making at different points along the R&D process.
The “best of breed” scientific tools for each application include OMIQ and FCS Express for flow cytometry, Protein Metrics for mass spectrometry, GraphPad Prism for data analysis, and SnapeGene, Geneious Prime, and Geneious Biologics for sequence engineering and analysis. They all integrate with the core product, which is an open, interoperable, and flexible platform. It’s also extensible, meaning that users can build upon it as they see fit. In fact, the Dotmatics system is designed to facilitate how researchers actually work rather than imposing new demands on their workflows. For instance, the plug-and-play architecture allows for the use of new instruments as they reach the market without users having to reinvent the wheel.
Those users include academic labs, small startups, medium-sized specialty companies, and large, international organizations. Each has their own challenges that can be addressed using the Dotmatics platform.
CO: Our customers are happy with it because it is easy to use. Biostatisticians are used to advanced software packages like SPSS and R, but those solutions really aren’t user friendly for people who haven’t been trained in statistics and that type of software. GraphPad Prism makes it very easy to input and analyze data and then produce publication-quality figures. Users don’t have to be programmers, whether they are aligning sequence data, or plotting an iC50 dose-response curve.
I consider GraphPad Prism to be a very tactile piece of software. It includes very informative tutorials that help users get up and running quickly. GraphPad really steps on the learning curve to rapidly get people to a point where they are actually doing their work instead of just trying to understand how to use the software. It is very intuitive, and analysis results are easily reproducible.
This concept of user-centric solutions is a theme that cuts across all of the Dotmatics platform and integrated scientific tools. We are very close to our users, and we listen closely to their needs. Their feedback informs our development process, and as a result we design and tweak our software so that it addresses user pain points as they arise.
CO: A little of both. Many of the people that work at Dotmatics are scientists with advanced degrees. We’ve been in the wilds. We’ve had experiments crash and fail. We know what it’s like to be in these domains, which also means that we understand the process really well. But even though we have all of that experience informing how we come up with ideas and design solutions, we still need to keep our ears to the ground with respect to user needs. It is easy to fall into a herd mentality due to confirmation bias really, really quickly. Being tightly connected with our users prevents that from happening.
In this case, in addition to our own excitement about the idea, we were getting comments at almost every conference about integrating GraphPad Prism with Dotmatics. We already thought it would be a great idea, but the driver for making it happen was so many users saying that since all of these tools are under the same umbrella, they need to be interconnected.
CO: Integration is a part of unlocking value from the data. One key benefit is the ability to move assay data. For instance, quantitative data from several screening studies performed using Dotmatics’ Screening Ultra solutions can be transformed and sent directly into GraphPad Prism in a very smooth flow. There is no need to spend hours transforming data using Excel or other programs. The software already handles those actions, which frees up a lot of time. In addition, you can build templates for data analysis. That allows different people to use the same method for analyzing specific types of data, which contributes significantly to reproducibility.
CO: Currently, there are inherent artifacts of the R&D process that are hard to avoid. Data silos are one of the biggest issues. There are IT experts, scientific computing experts, and researchers that all have to work together but are focused on different aspects of a project. Data silos are a natural result of these different groups coming together.
The goal at Dotmatics is to reduce and ideally eliminate those data silos. The first step is getting people weaned off of Excel, which continues to be a challenge. The idea is to create one platform within which data flows to wherever it needs to go without any waiting. The platform is easily searchable and will grow in scale as needed. That is where artificial intelligence (AI) and machine learning (ML) come into play, which are effective at analyzing large volumes of high-quality, often complex data and helping with scaling, but without creating data silos.
To make use of AI and ML, however, the data must be structured effectively and certainly differently from the way it has been done in the past.
CO: There are countless interesting problems to work on, so we have to prioritize among them. We have to choose projects that will bring the most bang for the buck for our users. For GraphPad Prism, we will soon be releasing version 10, and we believe it will be a gamechanger for our users because, first and foremost, we have developed a new file format that embraces FAIR data principles.
The new file format is going to unlock the value of everybody’s Prism data. Users will be able to get human-readable, comma-separated values (CSV) data, JSON schema, and portable network graphic (PNG) images all bundled within that Prism file format. Those files can be parsed and shared through the more open file format, which reduces the barrier to collaboration.
We’re also introducing a beta for Prism Cloud, which simplifies collaboration by allowing users to share graphs and layouts with their colleagues within a shared workspace. Prism Cloud lets users quickly engage in discussions and acquire feedback, allowing them to work and iterate in a more agile manner, and without having to send files back and forth.
The Graph Inspector is another new part of the Prism 10 release. It enables real-time graphing, supporting a visual data exploration process that allows users to see how their graphs change as they are edited. Also included in version 10 are new data-wrangling controls, including new logic functions and support for text transformations, and two new data analysis options, including two-way ANOVA and new
Overall, with GraphPad Prism 10, Dotmatics is helping users unlock processes over which they have been tripping historically, enabling them to focus on the real questions they are trying to answer rather than the same pragmatic challenges.
CO: There are a couple of different layers to that question, and I’ll talk about it from two different perspectives. Biotechs have some choices to make between hiring database experts and software developers to build in-house hardware and software resources or relying on outside expertise. The footprint and cost to maintain such internal operations must be considered, in comparison to the cost and risk of relying on a service provider like AWS (Amazon) or Google. Oftentimes, the reality is somewhere in the middle, with companies having some in-house software developers for customizing programs.
At Dotmatics, we do a bit of co-development with partners willing to work with us on a very intimate level. There is a lot of back and forth about what needs to be done, how we can be force-multipliers for each other, ways to avoid reinventing the wheel, and so on. When pursuing projects internally on our own, we take a similar approach, leveraging wherever possible existing technology so that we can innovate faster.
CO: For the biopharma industry, the elephant in the room today is that data volumes are growing, and the interconnectedness of relationships needs to be a priority. As the proverbial haystack gets bigger, the needles get harder to find. Users need to be able to do more with less while having to process ever-increasing volumes of complex data. Empowering them in this area is a core focus for Dotmatics.
For smaller organizations, Dotmatics’ solutions help them achieve way more than they ever could have before given their limited resources. For larger organizations, we help streamline processes and increase efficiency so that drug candidates can fail faster, allowing better use of R&D dollars for new discoveries that will actually benefit patients.
CO: Incorporation of AI will definitely continue to be important — companies that aren’t applying advanced digital technologies during drug discovery today are already falling behind. The Internet of Things and Industry 4.0 are also intriguing for biopharma, given how expensive biopharmaceuticals are to produce. These tools help streamline manufacturing and processing and are really part of the evolution of the industry and this advanced technology continuum. AI will be important in this area as well. It can help with near real-time monitoring to gain insight into the ongoing performance of processes and equipment and thereby prevent batch failures due to out-of-spec processes or equipment malfunction.
CO: Throughput is always an issue. Computation speed is another one. Data compression to increase data storage is a third. Legacy processes, tools, and thinking comprise a fourth. We need to get users to think differently about how they work and specifically to move away from using spreadsheets. Achieving that goal is really difficult, however, because even though users likely hate spreadsheets, the technology is familiar, while change is scary. Our approach is an evolutionary one for the most part, with a few real innovative solutions added into the mix when they can really solve user problems in an obvious and highly beneficial way. A couple examples that we are really excited about should be coming early in 2024.
Christian Olsen is a Business Segment Lead at Dotmatics. Previously, he was a Solutions Architect for the Geneious Biologics Antibody Discovery Platform. His background includes infectious disease and public health, bioinformatics, drug target selection, and drug resistance surveillance.