Connecting Data Across Scientific Disciplines
As novel therapeutic research increasingly occurs between multidisciplinary teams, scientists need to optimize their data flow so they can focus on collaborative discovery and innovation. They need a better way to share data and build off their collective knowledge.
LifeArc, a UK-based medical charity, has sought to break down barriers between disciplines so their research teams can collectively make critical, data-driven decisions and ultimately identify and pursue the most promising design ideas.
Case Study: Streamlined Biologics and Small Molecule Drug Discovery and Design LifeArc
LifeArc has been on a mission to “make life science life changing” for more than two decades. The UK-based medical charity is transforming the way life science ideas are brought to fruition by bridging the gap between lab and patient. Their novel approach has already led to four licensed medications, with several more in trials.
LifeArc’s drug discovery and design processes are remarkably diverse and collaborative on all fronts.
Scientists: The company has over 100 internal R&D scientists whose exploration of drugs and targets is informed by feedback from off-site molecular diagnostic colleagues.
Partners: In addition to internal researchers, LifeArc has a large network of pharma and biotech partners, academic collaborators, and contract research organizations (CROs) who are all producing important data that must flow into the company’s data warehouse.
Modalities: LifeArc is working with both small molecules and biologics, including engineered antibodies such as antibody-drug conjugates – which means many diverse chemical and biological data types must be accommodated.
Diseases: The company is exploring therapeutics for a wide range of conditions, including cancer, Crohn’s disease, multiple sclerosis, rheumatoid arthritis, and COVID-19.
Informatics needs: LifeArc’s informatics systems must handle huge data volumes, both internal and external data sources, and highly variable data types, including:
Small molecule discovery data (e.g., public and proprietary compound databases, CRO assay data, property calculations)
Biologics R&D data (e.g., B-cell workflows, phage display, immunization, humanization, X-ray crystallography)
Associated data and metadata (e.g., patent data, predicted data, ontologies, annotations, batch data, purification and expression data)
With such diversity at play, LifeArc’s ability to fulfill its mission hinges upon seamless collaboration and data flow between its multidisciplinary R&D teams and their many partners across pharma, biotech, and academia. This level of interconnectivity demands an end-to-end data platform like Dotmatics, which removes barriers between teams, breaks down data silos, and lets researchers easily access and build off their collective R&D data.
“With such an eclectic mix of therapeutic areas and modalities, LifeArc needed an informatics platform that was fit for purpose. We believe that the Dotmatics platform gives us the flexibility to plug in and play any other tools that we have now or might need in the future,” explained one LifeArc scientist.
Generate Better Insights With Improved R&D Data Processes
With Dotmatics solutions, LifeArc’s people and processes work together, better than ever. Some of the Dotmatics solutions that LifeArc has implemented include:
Data Visualization and Analysis: Project-based viewing of all relevant data, which can be further analyzed and modeled to make data-driven R&D decisions.
Compound Design Tools: Compound design informed by diverse data derived from structural drawings, similarity searching, property prediction, modeling, and machine learning.
Biological and Chemical Entity Registration- Registration for both small molecule drugs and biologics, including DNA, RNA, peptides, proteins, antibodies, conjugates, non-natural peptides and nucleotides, plasmids, cell lines, and user-defined entities.
Dotmatics solutions have had a huge impact on LifeArc researchers’ day-to-day work. One expert explains, “All data are available for scientists to use and easy to locate, which saves a lot of time. For example, it is possible to see if a compound has a SureChEMBL patent, without the need to look up elsewhere. Our growing team of data scientists can also reuse the data for predictive models, machine learning and AI.”
Read the full LifeArc case study about leveraging informatics and modeling tools to develop a comprehensive Design Make and Test platform.
Multimodal Therapeutic Discovery on a Unified R&D Platform
Dotmatics solutions break down barriers between multidisciplinary teams, helping them better collaborate, share data, and build off their collective knowledge. With data flows and workflows optimized, researchers can return their focus to innovation and idea generation. Dotmatics solutions can:
Combine biology and chemistry data and use it to guide decision making
Facilitate cross-discipline research and promote workflow optimization
Simplify database and technology infrastructure and reduce total cost of ownership
Request a product demonstration to discuss how Dotmatics can help improve your data flow for accelerated and advanced insights.