Next Generation Biologics R&D

Biologics researchers face numerous choices in early discovery that can significantly impact candidate selection and downstream R&D efforts. Many teams struggle to make well-informed decisions quickly because their data, workflows, and teams are not unified. At the BioIT-World Expo and Conference, Christian Olsen, Dotmatics’ Associate VP and Industry Principal for Biologics, discussed how Dotmatics’ flexible end-to-end R&D platform addresses these challenges by uniting all the data and tools researchers need to uncover promising preclinical biologics candidates and reduce time spent managing data.

Multi-Dimensional Discovery in Biologics R&D

Biologics R&D teams pursue complex treatments, such as antibodies, to address challenging diseases. Breakthroughs often depend on building new knowledge by combining different types of research data—a concept Dotmatics calls “research composability.” Teams use various tools and analyses to examine data from multiple perspectives, including:

• ​Sequencing (e.g., B-cell, T-cell repertoire sequencing)
• ​Mass spectrometry and high-performance liquid chromatography (primary structures, post-translational modifications, glycan structures)
• ​Flow cytometry (immune cell characterization)

While each approach provides specific insights, these are only partially useful in isolation. Combining insights from each method creates a more complete candidate profile.

Obstacles to Multidimensional Discovery in Biologics R&D

Attaining a complete candidate profile is challenging, primarily due to data issues such as diversity, silos, and difficulties in transferring data between tasks and teams.

Data Diversity and Data Silos

Biologics research is highly diverse, with different groups producing various types of results using specialized technologies at different stages of the R&D process. This leads to a complex and interconnected data web that is difficult to manage, relate, and decipher, resulting in R&D inefficiencies. Common challenges include:

• ​Large volumes and variety of complex data
• ​Disconnected data silos (e.g., protein, assay, flow, sequence, image, animal, antibody, patient)
• ​Inaccurate, outdated, duplicated, inaccessible, or lost data
• ​Incomplete data (e.g., missing connections between antibody and antigen, limited antigen-specificity data)
• ​Fractured infrastructure and incompatible specialty tools that do not feed data into an interoperable master data source
• ​Disjointed or redundant workflows with no easy dataflow between tasks or teams

Estimates suggest up to 30% of annual revenue can be lost due to inefficiencies from incorrect or siloed data.

Data Transfer Between Tasks and Teams

Data silos hinder researchers’ ability to switch tasks or share data with other groups or collaborators. When data are locked in disconnected silos, workflow and productivity suffer, as researchers cannot easily access the data they need. The process of switching tasks and transferring data wastes time, interrupts concentration, and increases the risk of errors. However, task switching is essential in multi-dimensional discovery, where researchers often move between different experiments or analyses to identify patterns and gain new insights.

Make Better Decisions, Faster

Improved dataflow and workflow enable teams to quickly create complete candidate profiles and make better decisions. Achieving this requires a flexible end-to-end R&D platform, such as the Dotmatics Platform, which offers:

• ​A single source of scientific truth with FAIR data that are easy to find and share
• ​A rich collection of specialty applications for biologics researchers
• ​The ability to overlay multiple types of complex data (e.g., sequence, flow, mass spec) to construct comprehensive candidate profiles
• ​Workflow efficiency and productivity tools to allow researchers to focus on scientific exploration rather than data handling

Example: Improved Dataflow and Workflow in Antibody Sequence Discovery

Dotmatics provides the scientific depth and enterprise architecture needed for scientists to explore granular details and connect discoveries to the broader context. The Dotmatics Antibody Discovery Solution supports every step of the Make-Test-Decide innovation cycle, with specialty functionality including:

• ​Make: SnapGene, Geneious Prime
• ​Test: Protein Metrics, Prism, OMIQ, FCS Express
• ​Decide: Geneious Biologics

These capabilities are integrated with Dotmatics’ core data and productivity tools, such as electronic lab notebooks (ELN), entity registration, sample and task management, scientific search, data visualization and analytics, assay screening and management, instrument integration, and third-party openness. This unified solution streamlines dataflows and workflows, enabling analysis through multiple innovation-cycle iterations. With each cycle, the pool of targets narrows and the value of the data increases. Powerful tools for capturing, sharing, aggregating, and analyzing data are essential for making the right decisions quickly. Dotmatics transforms the web of biologics discovery data into a unified, connected, organized, and standardized repository.

With Dotmatics, R&D teams can achieve up to:

• ​70% reduction in data integration and analysis time, allowing more time for experiments
• ​50% reduction in documentation creation time, increasing opportunities for collaboration

Next Steps

Request a product demonstration with a product expert to see how the Dotmatics Biology Solution for Biologics Drug Discovery can help your team make better decisions, faster.