GEN Interview: Andrew LeBeau, PhD, Dotmatics

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GEN: What software solutions does Dotmatics provide to help companies manage the flow of scientific information?

Andrew LeBeau
Andrew LeBeau, PhD
Associate Vice President for Biologics Marketing

Dr LeBeau: Dotmatics’ software is built in-house by a single team. It’s mostly on a web-based platform with 17 different modules at present. The key is that the modules are not disparate products that the customer needs to tie together. This one platform supports both chemical and biologic drug discovery and increasingly formulated products and fine materials. I’m going to talk about a few of the key modules.

Dotmatics was formed around a product called Browser, which is a window into all the data from every different place within an organization. Over time, the sources of data have become even broader. A lot of data is now coming in from outside the organization such as through a CRO.

Browser allows scientists to gather all the data they need to make informed decisions and to view the data in the way they want. Capturing data is all well and good, but it’s only a means to an end, the end being able to present the data to scientists in a way that they can use it and make well-informed decisions.

The second module is called Studies, a primary data capture module that works in two different configurations. One is as an electronic lab notebook (ELN) that captures and manages the highest quality data within the experiments that are running while guiding users through protocols or workflows.

The other configuration is used for assay data management. When you set up your experiment and then run an assay, you want to capture the data that’s originally coming from whatever instrument you’re using and send it back into the informatics system so that you can manage, organize, and analyze it.

Then we have two modules for entity registration. One is Register, and the other is Bioregister. Register is for chemical registration (small molecule). Bioregister is nominally for registering biological entities (biological sequences, antibodies, peptides, DNA, RNA, chemically modified biologics, etc.), but it’s actually more of a general-purpose registration product. Both are critically important because these are where you capture and store your intellectual property.

Another module is Vortex, a desktop application that integrates with the rest of our platform. Due to the demands of working with the analytical and visualization capabilities that you need for advanced data analysis, Vortex runs as a local application. It fully understands chemistry and biology.

GEN: What do you think makes Dotmatics unique regarding what you are offering to help companies deal with the flow of data?

Dr LeBeau: Three factors. Right from the beginning, the company’s focus has been on getting meaningful information out from its products instead of simply collecting data. It’s about supporting scientists and giving them access to their data.

A second factor has to do with the fact that when the company first started, drug discovery was all about small molecules. During the past ten years or so, natural biologics, e.g., antibodies and small peptides, have become more important. Over the last five years, we began to see engineered biologics or chemically modified biologics instead of pure small molecules or natural biologics. One of Dotmatics’ unique capabilities is the breadth of science we support, i.e., both chemistry and biology, in a single platform.

The third factor is that Dotmatics is an informatics provider that has been road tested really well. We have hundreds of implementations across the world from startups to the largest biopharma companies.

GEN: How is Dotmatics breaking down the barriers to the lab of the future?

Dr LeBeau: What we see in terms of the lab of the future from the technology perspective is a lot more data automation and faster cycle times. Automation means we can get more high-quality data sooner so that scientists can progress therapeutic programs as fast as possible, while relieving them of labor-intensive tasks. Whatever we can do to reduce the time and cost of R&D, the better. We want to let researchers to do what they do best—science.

We have built our software platform to be as integrable as possible so that we can participate in the types of automation approaches that are becoming more common in the industry, and generate high-quality data to support machine learning and artificial intelligence techniques.


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