Biologics discovery is an inherently complex process. Tracking a molecule's journey from design to production involves countless variables, and even the most rigorous workflows can face challenges in maintaining seamless data continuity without the right technology in place. For example, without traceable IDs that follow a molecule across batches and systems, molecular biologists may struggle to confirm that the DNA they have cloned will produce the intended protein.Those running cell expression systems often lack visibility into the exact molecules or byproducts their cells are producing—a problem further complicated when dealing with multispecific antibodies (MsAbs) subject to issues such as assembly mispairings (as shown below). Protein purification adds another layer of complexity, as byproducts with similar masses to the desired protein can be difficult to distinguish, increasing the risk that unwanted molecules go undetected. All of these issues can create a ripple effect across the pipeline, causing miscommunication, errors, and delays. Without a centralized system to connect and trace data from initial in silico design and throughout downstream in vitro workflows, teams are left struggling to pass data between fragmented specialty tools and often making partially-informed assumptions in isolation, which slows progress and increases the risk of costly mistakes.

Figure 1: Engineered novel antibodies, like the bispecific antibodies shown here, are subject to assembly mispairings that impact activity and immunogenicity. The presence of these mispairings and other byproducts can also reduce main peak yield, adding significant cost to the development process. Many R&D teams are searching for easier ways to not only identify when issues such as mispairings and impurities occur, but also trace back the R&D steps that led to them so that designs and processes can be refined in order to improve outcomes.

Dotmatics Luma: Enabling Full Traceability and Visibility From Design to Production

With the Dotmatics Luma scientific R&D platform, researchers can design and score novel entities like MsAbs in silico, track promising structures through downstream in vitro processes, and use the knowledge gleaned to refine designs and processes.  By having all key steps of the design-make-test-decide R&D cycle tied to the same underlying platform, teams can collaboratively innovate like never before possible. Dotmatics Luma offers rich functionality spanning:

• Computational Design (and Refinement): BioGlyph provides a building-block-based design pad (dPAD), AI-powered developability assessment, and universal markup-language support (e.g., AbML and VERITAS) to help teams precisely design and differentiate novel biologic entities and decide which ones to push through to the lab. Within structured projects, teams can design new molecular formats, pull in variable regions from external campaigns, and assemble building blocks with desired technologies. They then assemble these custom building blocks into the designed format to create panels of molecules. Throughout the R&D process, BioGlyph links sequences to dynamic 2D format and 3D structure representations, showing their precise design and underlying sequences, tying in all relevant data from downstream processes and analyses—providing a holistic profile of each candidate and illuminating opportunities for further design refinement (see Figure 3).

• Cloning Design and Execution: Geneious Luma helps teams use their computationally-designed entity specifications to detail the cellular components that will need to be made in the lab.

• Expression, Purification and PTM Analysis: Protein Metrics Luma provides a rich collection of tools for quantifying, characterizing, and analyzing the resulting protein structures that have been expressed in the lab.

• Functional Assay Development:  Prism/Flow Luma enables assessment of the functional properties of proteins, leveraging Luma Lab Connect for seamless acquisition of analysis-ready result data/metadata from instruments.

Adaptive Workflows

While Luma supports the broad range of research steps needed in MsAb R&D, it does not prescribe linear, step-by-step processes. Instead, Luma’s ‘Adaptive Workflow’ capabilities enable rapid refinements that are directly informed by the insights uncovered during R&D. Teams can easily make design and process adjustments, assign additional lab tasks to explore new options, and collect the contextualized data needed to make decisions or guide further refinements.

Figure 2: Dotmatics Luma unites the diverse instruments, applications, and data that cross-functional biologics discovery teams rely on for: protein engineering; cloning design and execution; expression, purification and structural characterization; and functional essay development and execution. The structured data management, workflow cohesion, and real-time connectivity that once felt impossible to teams working with novel entities, like MsAbs, is now a reality with Luma.

Lab-in-a-Loop: Uniting Virtual and Wet Labs to Optimize R&D

By enabling a seamless lab-in-a-loop, Dotmatics Luma lets researchers tie results from all of their in vitro work back to the original in silico structure design in order to guide further design and process refinement, using AI/ML to help inform decisions where possible. Every molecule is assigned a unique ID that tracks its progress at each stage of development, ensuring full traceability from design through production. This enables teams to link every relevant data point from across the entire workflow back to their initial molecular structures, as highlighted in Figure 3. The interconnected Dotmatics platform not only enables seamless dataflow and automation of repetitive workflow steps, but also simplifies collaboration for cross-functional teams who often rely on different specialty instruments, applications, and workflows, which often don’t work together so smoothly with other third-party or custom-built solutions. With Dotmatics, everyone—whether in research, development or production—can access real-time, accurate information about each structure’s identity and status. This seamless flow of data across tools and teams removes bottlenecks, reduces errors, and improves collaborative innovation. 

Figure 3: With Dotmatics, researchers can see their MsAb designs alongside key data from downstream analyses, providing holistic candidate profiles that help inform design and process refinements.

Learn More

Watch a demo to see how the Dotmatics Luma Platform and collection of specialty science applications can help your cross-functional MsAb development teams optimize their iterative design-make-test-decide R&D cycles.