May 2025 Release

Starting with the May 2025 release, DataHowLab will be deployed as a single, integrated platform, allowing access to all supported process formats. Users working across multiple formats can select the process format when starting a new project.

This structural upgrade brings several key benefits:

• Seamless user experience – No more switching between environments — users working across formats can now access everything in one place.
• Effortless expansion – Extending DataHowLab to additional process formats to match your operational needs is simpler and faster.
  Curious about what’s available? Reach out to your DataHow contact to learn more.
• Simplified maintenance and updates – A unified deployment means faster rollouts, fewer disruptions, and smoother product updates.
• Future-ready architecture – This higher-level abstraction lays the groundwork for upcoming extensions — including new formats and additional unit operations.
  This is just the beginning

We’re excited to announce the BETA release of the new Spectra Module in DataHowLab.

This module is designed to help users explore how spectral data can be leveraged for deeper process insights, faster decision-making, and smarter integration across workflows.

We are offering a 6-month free evaluation of the new module, including:

• Access: Free for all interested users for a 6-month evaluation period
• Training Package (Optional): CHF 1,000 per user
  Including:
  • Half-day virtual training session
  • Full access to documentation
  • 5 hours of expert support during initial use
    (Additional support can be arranged separately or drawn from existing USP retainers.)

If you’d like to learn more about the Spectra Module, we invite you to watch the webinar, “Unlocking the Potential of Spectroscopy in Biopharma: Challenges, Innovations, and Integration Strategies”, led by DataHow CTO Fabian Feidl.

If you’re interested in testing the Spectra Module and planning your training, contact your DataHow representative to get started.

With this release, we’re introducing a smarter, more user-friendly importer that provides clearer, more actionable error and support messages during Excel-based data uploads.

Most users rely on the Excel template import to get started with DataHowLab. Thanks to your valuable feedback, we have made improvements to the clarity of error messages, as well as providing more guidance on how to resolve errors.

What’s new:

• More precise error messages – Know exactly what’s wrong and where it is in your Excel file
• Helpful suggestions – Guidance on how to resolve issues, rather than just flagging them
• Smoother onboarding – Fewer blockers when starting projects or loading new datasets

This update is designed to make working with DataHowLab more intuitive and less error-prone from the very first step.

We’re adding a powerful new tool to help you better evaluate the performance of the combined model before moving forward with model-based tasks.

The combined model plays a central role in model-based activities like what-if analysis, robustness analysis, and design optimization, where predicted Critical Quality Attributes (CQAs) are the target.

Until now, there was no way to directly evaluate the performance of the Combined Model before being used in important activities. That changes with this release.

What’s new:

• New evaluation panel – specifically for the Combined Model
• Clear error metrics – to assess prediction quality of CQAs (Y-variables)
• Better model insight – understand the quality of your combined model when used in key tasks

This new view mirrors the historical model’s evaluation page but reflects the real-world prediction context, where process variable dynamics are estimated, not measured. That means you’ll now have accurate performance metrics for the full model chain you’re relying on in development.

More transparency. Stronger Outcomes. Better decisions.

What-if analyses are at the core of deep process understanding — and now, you can save and share your simulations directly in DataHowLab, allowing you to build and collaborate on important process knowledge.

Whether you’re exploring process uncertainty, testing recipe changes, or identifying new experimental directions, simulations often reveal critical insights that shape future decisions.

What’s new:

• Save your simulations – revisit key What-If analyses anytime, without rerunning them
• Collaborate effortlessly – share outputs with your team for aligned decision-making
• Enable deeper process understanding – store insights that inform recipe design, process characterization, and more

Now, your what-if analyses aren’t just a step in the process — they’re a shared foundation for further innovation.

With our latest release, you can now clone and edit existing recipes directly in DataHowLab, making it easier to fine-tune experimental designs as your projects evolve.

Bioprocess development is inherently iterative. Each round of experiments drives new insights, and those insights shape the next set of recipes. Until now, recipe creation was limited to predefined sources like datasets, initialization designs, or design optimizations.

What’s new:

• Clone existing recipes – as a starting point for new iterations
• Edit recipe values directly – for fine-tuning and manual refinement
• Seamless integration – recipes now act as full counterparts to experimental data in the workflow

This update gives you the flexibility to adapt, iterate, and refine your process designs — making DataHowLab an even more powerful tool for structured, insight-driven development.