Software For Cell & Gene Therapy

Fully integrate research, development, and biomanufacturing

Novel treatments with novel data challenges

Fueled by recent scientific milestones, cell and gene therapies (CGTs) have emerged as one of the most promising fields in human health. Drug hunters today have a new, exquisite understanding of human biology and the technological advancements necessary to make novel therapeutics. These new treatments are bringing hope to patients — and complexity to how labs operate and manage scientific data.

Cell and gene companies face novel challenges that have redefined—and in some cases completely reinvented—drug design, development, and manufacturing workflows.
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Companies working on cell and gene therapies need a solution to manage all their data—and make R&D and manufacturing faster, easier, and cheaper than ever before. Unfortunately, existing solutions are not well-suited to the biological complexity and unique R&D/manufacturing dynamic of cell and gene therapies.

Inherently complex therapeutics Gene therapies involve assembling sophisticated payloads that can be delivered to precise targets and manipulate gene expression in a desirable way. Cell therapies meanwhile involve working with living and functional cells. Both have forced biotechs to adapt their processes and adopt new tech stacks.

Blurred lines between R&D and manufacturingCGT product development requires a tight integration between protocols and knowledge developed in the lab, and their smooth roll-out into compliant production. R&D equipment such as flow cytometers often needs to be repurposed for production workflows, despite a lack of industry roadmaps to follow.

Demanding production processesUnlike with traditional drugs, the process itself is often the IP with CGTs. Highly specialized workflows that maintain a high level of quality of the therapeutic end-products and keep costs of goods and services (COGS) under control are a critical challenge.

Reliance on collaboration and CDMOs The complexity of CGT workflows, and the specialized training and equipment involved, mean that biotechs and biopharma have become increasingly dependent on partnerships with research hospitals and with CDMOs to bring these treatments from bench to bedside.

Your lab on Ganymede - Flow Cytometry

Cell and gene therapy companies operate in an area of tremendous biological complexity. In creating new therapeutics, they also create novel workflows for R&D and manufacturing.

Ganymede’s Lab-as-Code platform was specifically designed to help labs with complex biological data and processes. We give labs a birds’ eye view of their entire lab’s activities and empower them to make data-driven, informed decisions that fuels them from early R&D, through clinical trials, to manufacturing.

What’s the most common instrument cell and gene companies struggle with? We see it with our clients all the time — flow cytometers.

Before Ganymede

Flow cytometers—they’re a workhorse instrument in any lab working with cells, starting from early stage R&D through biomanufacturing.

For gene therapies, this may be validation of the delivery and outcome of a potential treatment. For cell therapies, this might be checking your engineered cells for quality and function. Either way, you’ll likely run into these “clogs” in your flow cytometry workflows:

Metadata tracking is necessary as raw data analysis:Flow cytometry is largely about studying populations of cells, and so metadata like laser channels and gating strategy are just as important as the individual events logged as raw data.

Reliance on proprietary software and manual analysis:Flow analysis is highly reliant on proprietary data visualization tools like FlowJo, manual interpretation of cell populations, and secondary analysis of populations across conditions and runs. The result is a nightmare for data management and dependency on tracking and understanding who did what with the data.

Integration of data across flow runs and workflows with ELNs/LIMS:A given workflow could feature multiple flow cytometry validation and QC steps, each with layers of analysis that results in multiple file types that don’t pipe easily nor well into scientific apps like ELNs and LIMS.

After Ganymede

Ganymede centralizes all your flow cytometer data in the cloud, alongside all your lab’s data from every other source. It’s all automatically formatted and cleaned, and it can be analyzed directly in the cloud. Now your scientist’s process looks more like this: run experiment, open workspace, start analyzing.

When Ganymede is powering your flow cytometry data infrastructure:

Metadata is as valued as raw data and results:We automatically ingest, parse, and store all of the raw data and metadata associated with each flow cytometry experiment, meaning you’ll always have the full context of each run that's needed for understanding your cells.

Maximized analytical capabilities, minimized data headaches:Ganymede let’s you virtualize manual analysis so that you can keep using your favorite scientific software tools (like FlowJo) and SOPs, all while streamlining your data management counts and tracking the full provenance of analysis performed by leveraging automation where it.

Harmonize data across your runs and workflows:Data from every step of your flow cytometry run and broader workflow is streamed and structured into a data lake. Our Lab-as-Code technology allows you tap into that data and build customized data pipelines and integrations that automatically upload specific data points and results to your preferred destination in your ELN or LIMS.