Case study

Solution design for efficient single and multi-omics R&D

The client sought to transform its R&D bioinformatics capabilities, enabling efficient single-omic operations and facilitating multi-omics integration. They needed to harmonise data practices, define roles and responsibilities and plan a major organisational change.

Our Approach

We assessed existing capabilities, designed a technical and operational architecture and planned a transformation with support to harmonise multi-omics R&D.

  • Assessment & strategy development: Conducted interviews and workshops to evaluate single-omic and multi-omic needs and recommended a data-mesh architecture with defined data domains.
  • Technical architecture & operational model: Designed a FAIR technical architecture, defined technologies and pipelines, and clarified roles and responsibilities.
  • Transformation planning & support: Planned a twelve-month transformation with resource estimates, harmonised data formats, consolidated teams and provided long-term implementation support.

The Outcome

  • Delivered a customised solution design ensuring data are findable, accessible, interoperable and reusable.
  • Unified teams into data domains and provided documentation for omics pipelines.
  • Empowered the client to own the solution and make informed implementation choices.
  • Set the stage for multi-omics discovery by harmonising data practices and establishing a clear roadmap.

Why It Matters

Effective data-management strategies enable large organisations to leverage omics data for discovery. By harmonising processes and defining clear ownership, the client maximised its potential for innovation and efficiency.

Let’s discuss how we can turn your data into real scientific impact.

Contact us >

Beyond animal testing in drug development

Beyond animal testing in drug development

For over a century, the life sciences industry has relied on animal models as the standard for predicting drug safety and effect. But today, the industry faces a harsh reality: over 90% of new drugs that appear safe and effective in animal tests ultimately fail in human clinical trials (see for example Ineichen et al. 2024 [1] and Marshall et al. 2023[2])

How spatial biology improves clinical trial success in oncology

How spatial biology improves clinical trial success in oncology

Oncology drug development often begins in patients, allowing early safety and efficacy insights. Yet many cancer drugs still fail in the clinic. We validate the target but ignore its context within the tumor microenvironment. This article explores why spatial biology may improve clinical success.