NOVASIGN STUDIO | CDMO
Novasign Studio for CDMOs
Deliver faster, more defensible process decisions -and build capability your team can reuse across every program.
Novasign Studio helps CDMO process development teams turn process data, experimental results, expertise and models into structured, reusable workflows across upstream and downstream development.
Start with one process question. Prove value. Expand from there.
THE CHALLENGE
The challenge strong CDMO teams still face
You already know what matters: deliver robust processes, hit timelines, and keep manufacturing capacity filled. The challenge is getting there efficiently – and with documentation you can defend.
Campaign data is hard to compare consistently across runs, scales, and sites
Experimental effort grows quickly without always improving the quality of decisions
Scale-up and tech transfer decisions still carry more uncertainty than they should
Process justifications to sponsors are often manual, slow, and hard to standardise
Internal modelling capacity is limited
Even the strongest teams end up in iterative cycles that are slower and more resource-intensive than the competitive landscape allows.
HOW NOVASIGN STUDIO HELPS
One connected workflow. From process-data to defensible decisions
Novasign Studio introduces a structured workflow layer across your development process.
Planning → Data preparation (ETL) → Hybrid modeling / digital twin → Decision support
Instead of disconnected analyses and local scripts, your team works within one structured environment:
01
Plan
Design smarter experiments around the specific decision you need to make -from screening to model-based Design of Experiments.
02
ETL
Transform campaign data from any source, bioreactors, PAT, LIMS, historian -into reproducible, comparable datasets your whole team can work from.
03
Model
Combine process knowledge and experimental data into hybrid models that are explainable, auditable, and built for your process, not a generic template.
04
Simulate
Run virtual digital twin scenarios to test operating strategies, de-risk scale-up, and evaluate trade-offs before committing to expensive lab or engineering runs.
05
Decide and reuse
Generate clear, explainable outputs that can be shared with clients, applied across programmes, and built on over time – not rebuilt from scratch.
USE CASES: WHERE STUDIO FITS IN CDMO DEVELOPMENT
The use cases where teams see the fastest return
The best entry points are where teams already feel repeated work, data friction, or scale-up uncertainty – across upstream and downstream development.
Faster Speed-to-Clinic
Build a workflow around your platform process to only perform minimal effort for early development.
Process characterization and optimization typically requires more experiments than necessary. Novasign replaces brute-force DoE with model-based experimental planning building on your platform – running only the experiments that matter.
Clients have reduced experimental effort by 35–70% in development programs spanning E. coli, yeast, ATMPs , and mammalian platforms.
Scale-up and tech transfer prediction
Scale-up is where CDMOs win or lose client relationships. Novasign integrates CFD-derived parameters – kLa, mixing time, shear rate, P/V -directly into hybrid bioreactor models, enabling in-silico prediction of process performance at any target scale before running a single engineering run. This is where you can convince your clients the most
Transfer from any lab equipment like AMBR, DASGIP, or INFORS small-scale systems to pilot or manufacturing scale – with quantified confidence, not engineering judgment alone.
Upstream to downstream in one workflow
Optimize all unit operations in sequence in a single Software: upstream processes feeds downstream modelling for filtration (UF/DF, SPTFF, MF), chromatography, and formulation. Changes in upstream parameters are propagated to downstream performance.
Data fragmentation and knowledge reuse
Valuable process knowledge is currently buried in spreadsheets, local scripts, and specialist expertise. Studio standardises how data is transformed, how models are built, and how decisions are documented – so knowledge stays in the organization, not in one person’s head.
Deviation Investigation and CAPA support
When deviations occur, root-cause assessment depends on having good process context and traceable data. Studio’s reproducible ETL workflows and documented decision logic give quality and process teams faster access to the data they need – and a clear audit trail of how the process was characterized and run.
NOVASIGN STUDIO
Two ways CDMO teams use Novasign Studio
Studio supports both day-to-day process execution and longer-term capability building – depending on where your team is starting from.
Standardize decisions across programs
Reduce manual data wrangling and inconsistent interpretation across upstream and downstream programmes. Give process teams reusable workflow support -without adding modelling overhead or specialist resource requirements.
Each workflow built today becomes a template for the next programme.
Add a workflow intelligence layer
Differentiate yourself from classic asset driven CDMOS. Our Studio gives you a structured digital layer that makes process decisions faster, more consistent, and easier to justify -without overhauling your existing infrastructure.
The result is a tangible differentiator you can show sponsors, not just describe.
WHY NOVASIGN STUDIO
What makes Novasign Studio different for CDMO teams
01
Up to 70% fewer experiments
Learn more
Our workflows reduce experimental burden by 35–70% in process development -demonstrated across CHO, HEK, E. coli, and ATMP platforms. Fewer experiments means faster programmes and lower material cost per client engagement.
02
CFD-infused scale-up prediction
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Predict process performance at any target scale – bioreactor geometry, kLa, mixing time – before running engineering or pilot runs. Build client trust by arriving at tech transfer with a model, not a guess.
03
Reusable workflow foundation
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Capture process knowledge in structured workflows that teams can apply across programms, sites, and development stages.
04
Transparent, auditable decision support
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Every model assumption, preprocessing step, and decision path is visible and explainable. This is what regulators expect and what clients need to justify.
05
End-to-end process continuity
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Connect upstream to downstream unit operations in one workflow environment – with clear visibility from raw data to final process recommendation.
SELECTED CASES
Results from real CDMO and biopharma programmes
22 → 8
Bespark*bio Reduced experimental runs from 22 to 8 -achieving approximately €40k in material cost savings and a 12-week development acceleration. 64% reduction in experimental effort.
50% +
Bisy GmbH Reduced development timelines by more than 50% in an initial proof-of-concept study, using Novasign to translate process potential into new products and processes.
Comparing Novasign with other solutions
Novasign Studio is built for teams that need a practical workflow from experimental data to modeling, simulation, and better process decisions.
Novasign VS internal scripts and local models
Move from person-dependent analyses to reusable workflows your team can review, reuse, and scale.
Novasign VS bioprocess cloud – based modeling platform
Keep flexibility in deployment, workflows, and model integration – including fully on-prem setups if desired.
Seamless integration with full white-label capabilities
Novasign Studio combines full integration and white-labeling flexibility with seamless compatibility across complex bioprocessing hardware and software workflows.
Full-Spectrum Modeling Across the Entire Bioprocess
Supports mechanistic and data-driven approaches across all unit operations, enabling full upstream-to-downstream process modeling within a single environment.
GETING STARTED: STUDIO + GUIDED FEASIBILITY PLOT
Start with a scoped, low-risk engagement
01
Scoping Call
Define one area to improve (e.g., scale-up, optimization, DSP strategy)
02
Feasibility Check
Assess whether your historical data can support predictive modeling
03
Pilot Workflow
We build the workflow in Novasign Studio for you.
04
Results & Workshop
Clear outputs, recommendations, and next steps
STUDIO ONLY
Studio Access
01
Hands-on directly
For teams that want to get hands-on with the software directly.
02
Access Novasign Studio
Getaccess to our Studio.
03
Srtandart Workflow
Receive workshop on standard datasets.
04
Use Studio independently
You are all set, and you will have access to our support.
Frequently asked questions
What data do we need to start?
Structured or semi-structured process data -CSV, historian exports, LIMS, XLSX. We assess data suitability in the feasibility check before any commitment. Most teams start with retrospective data from a single unit operation
Can we run this on-premises?
Yes. Novasign Studio is designed as for cloud-based or fully on-prem deployments, which is an important differentiator for teams with stricter data requirements.
Do we need an internal modelling team?
No. Studio is designed for process scientists and engineers, not data scientists. All core features are accessible through no-code graphical interfaces. For teams with data science capability, custom Python code integrates directly within Studio.
Who owns the models and workflows we build?
You do. All models, processing workflows, and derived insights generated in Studio belong to your organisation. Novasign retains ownership of the platform's native components only. Client data is never used by Novasign for any other purpose. The results and learnings are fully owned by you.
Can Studio handle multi-client data separation?
Yes. The permission system supports nested organisational structures -company, site, department, user -with admin-controlled access at each level. Client data can be strictly separated or selectively shared, depending on your operational model.
How many experiments do we need to get started?
You can begin even with limited data. Studio helps you extract maximum knowledge from what already exists, and recommends the most informative next experiments to run -reducing total experimental effort by up to 70% compared to conventional DoE approaches.
How long before we see ROI?
Return on investment has been demonstrated within 1–3 months for multiple customers. The first level of value -data aggregation and visualisation -can be delivered within 1–4 weeks. Process modelling and experimental reduction typically follows within 1–3 months.
Do we need to automate everything to get value?
No. Most value comes from decision support before automation. A practical starting point is one unit operation or one process question -then you expand when the data and operational context support it.
Is this a black box?
No. Workflows are fully transparent and explainable. Teams can inspect every preprocessing step, model assumption, and decision path. This is essential for sponsor-facing justifications and regulatory submissions.
GETING STARTED
Build digital capability.
One workflow at a time
Start with a focused workflow that matters to your team.
Bring together process data, decision logic, and user adoption in one practical use case.
Show value in a defined area, then scale with confidence.