NOVASIGN STUDIO | BIG PHARMA PROCESS DEVELOPMENT
Stop running experiments you have already run
Novasign Studio turns historical process data into reusable, scientist-ready workflows – so your team builds on what it already knows instead of rediscovering it.
Cost down. Fewer experiments. Faster decisions. Scale-up confidence. Self-controlling processes
Trusted in bioprocess development and digitalization initiatives
Cloud-based or fully on-premises. No-code for process engineers, code where your data scientists need it.
Strategic partner: Repligen – Novasign selected after comprehensive global market research and strategic investment in 2025.
THE CHALLENGE
Why Big Pharma process teams keep running the same experiments
The bottleneck is almost never a lack of data. It is data that cannot be found, compared, or reused – scattered across tools, systems, sites, and development campaigns. Teams rebuild knowledge that already existed as the reusable workflow is missing.
Historical knowledge stays locked in the past
Process learnings from prior products, campaigns, and development cycles stay fragmented across tools, sites, and individual scientists – instead of informing the next decision. The work has been done. The insight is inaccessible.
Internal tools are hard to scale beyond the expert who built them
Homegrown models, scripts, and analytical pipelines often work well for one or two people. Operationalizing that knowledge across teams, molecules, and sites is where in-house built tools consistently stalls.
Scientist adoption determines whether digital capability lives or dies
When a workflow is not intuitive for scientists running experiments daily, even technically strong solutions fail to gain traction. The best model that goes unused delivers zero value.
Scale-up confidence gaps create expensive late-stage risk
When process understanding from development does not transfer cleanly to pilot or manufacturing scale, the cost is delayed programs, failed batches, and unplanned engineering campaigns.
Build-vs-buy inertia slows digital progress
Every team that starts building an internal platform faces the same wall: Data Preprocessing, model validation and maintenance, simple user Interface for engineers, and adoption each become a project. The platforms rarely reach the scientists who need them.
NOVASIGN STUDIO
From fragmented process data to one connected decision workflow
Novasign Studio introduces a structured workflow layer across your development process.
Instead of disconnected analyses and local scripts, your team works within one structured environment: It does not replace your existing models, scripts, or data infrastructure it makes them reusable, reproducible, and shareable across your organization.
01
Plan
Design smarter experiments around the specific decision you need to make – from screening to model-based Design of Experiments.
02
Prepare
Transform campaign data from any source, bioreactors, PAT, LIMS, data, lakes, historian – into reproducible, comparable datasets your whole team and organization can work from.
03
Model
Combine mechanistic 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 expensive lab or engineering runs.
05
Decide and Reuse
Generate clear, explainable outputs that can be shared with clients, applied across programs, and built on over time and also applied for process control in real-time and not rebuilt from scratch.
USE CASES
Where Novasign Studio fits in Big Pharma process development
One platform. Upstream to downstream. All unit operations – from early-stage feasibility through tech transfer and process handoff.
Historical data feasibility
Use existing datasets from prior campaigns or development runs to answer value process questions – before committing to new experiments. Common first use: ‘What can our historical mAb data tell us about this new molecules ideal process?’
Upstream process optimization
Model-based DoE for seed train, fed-batch and perfusion, processes. Reduce experimental rounds, explore broader CPP/CQA design spaces, and design more informative experiments from the start.
Downstream development and robustness
Chromatography, UF/DF, TFF, SPTFF, and formulation workflows. Identify robust operating windows with fewer runs and stronger mechanistic justification for process characterization packages.
Process characterization support
Reduce the experimental burden of characterization studies that Our model-based designs identify CPP ranges and CQA linkage with significantly fewer runs compared to standard DoE
Scale-up and tech transfer rationale
Scenario-based simulation of scale effects before committing large-scale runs. Strengthen the tech transfer package with process understanding that scales with the process to the manufacturing level.
Cross-project workflow standardization
Turn local expert knowledge into reusable process decision logic. Deploy consistent workflows across multiple molecules, platforms, and sites without each team rebuilding from scratch.
22 → 8
Experimental runs. From 22 to 8 in a single process development project (Bespark*bio)
~€40k
Material cost saved in one feasibility project through model-based experimental design
(Bespark*bio)
50%+
Development timeline reduction in an initial proof-of-concept study
(Bisy GmbH)
10%-5x
Higher Titers compared to the standard process
(Arkeon)
Who benefits from Studio?
Three types of people tend to find Novasign Studio relevant. If any of these sounds like your Monday morning, this page is for you.
“My team keeps redoing work we have already done.”
VP Process Development · Head of Bioprocess Sciences · Director CMC
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You have historical data, internal expertise, and development campaigns that produced real process knowledge. The problem is that knowledge is not reusable – it lives in files, tools, and the heads of people who have moved on. Novasign turns that scattered knowledge into a workflow the next team can build on.
“We have models and scripts that only one person can actually use.”
Digital CMC Lead · Process Modeling Lead · Data Science Lead
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Your team has built real digital capability -preprocessing scripts, analytical pipelines and models. But they live with the expert who built them. The moment that person moves on in their career, the capability goes with them.
Novasign operationalizes what you have already built so anyone on the team can use it – not just the person who created it.
“I need a modeling workflow I can actually run myself.”
Process Scientist · Research Scientist · Process Engineer USP / DSP
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You know the biology. You know what questions need answering. What you need is a workflow that fits how development scientist actually work – not one that requires a data scientist sitting next to you to run it.
Novasign brings “No-code” where you need speed. Full- Code when you want it. Transparent models you can understand, explain, and defend in a regulatory review.
WHY NOVASIGN STUDIO
Why process development teams choose Novasign Studio
One platform. Upstream to downstream. All unit operations – from early-stage feasibility through tech transfer and process handoff.
Reuse what your organization already knows
Historical process data from prior campaigns, development runs, and platform molecules already exists inside your organization. Novasign makes it usable for the next decision instead of designing another experiment to rediscover it.
Bring your own models, scripts, and code
Novasign does not force you to replace internal developed models or custom scripts you know that work for your process. We integrate your existing digital assets into a shareable, reproducible workflow that the broader team can use and not just the one expert who built them.
Designed for scientist adoption - not IT adoption
No-code where scientists need speed. Code-ready where data scientists need flexibility. Transparent model logic every stakeholder can understand. Built so the workflow gains traction, not just gets deployed.
One platform across all unit operations
Upstream, downstream, filtration, chromatography, formulation, scale-up and tech transfer. One connected workflow and not multiple disconnected tools. Process understanding from one step informs decisions in the next.
Start with a scoped feasibility, not a platform commitment
One process question. Existing data. Novasign scopes what is answerable, returns a proposal, and proves value before any license decision is made. Low-risk entry. Evidence-led expansion, same path that has led every successful Big Pharma collaboration.
BUILD VS BUY
Operationalize what you already know
Your organization has valuable code, models, datasets, and scientific expertise. The challenge is not a lack of digital capability, it is making that capability usable, reproducible, and accessible beyond the team or expert who created it. Novasign Studio is designed to accelerate and scale what you are already building.
| Internal build or existing tools | Novasign Studio | |
|---|---|---|
|
Time to value |
Months to years. data preprocessing, model building, user-interface, and adoption are each a separate project. |
Weeks to first feasibility result. Workflow infrastructure is pre-built. Data Preprocessing included. |
|
Scientist adoption |
High risk. Tools built by data scientists often require data scientists to use daily. |
Designed for scientists. No-code workflows. Transparent models. Built for daily use. |
|
Your existing code & models |
You own them, but they are siloed with the expert who built them. |
Integrate your scripts and models directly into Novasign in a reusable format. Operationalize them across teams |
|
Maintenance overhead |
Ongoing. Every new dataset, modality, or site is a new IT project. |
Maintained by Novasign. Regular Software updates. On-premise or cloud installations as desired. |
|
"Explainability" for regulatory |
Often transparent internally, but hard to document reproducibly for dossiers. |
Traceable inputs. Documented, datasets, workflow logic and model binding. Reproducible outputs for regulatory use. |
|
Entry cost and risk |
High total cost of ownership. Talent, maintenance, and adoption often exceed estimates. |
Scoped feasibility first. No large upfront commitment. Scale only after value is proven. |
GETTING STARTED
Start with a question. We will tell you what is answerable.
What a Historical Data Feasibility Assessment looks like:
01
You share context: one process challenge, one unit operation or workflow area, raw data availability
02
Novasign reviews the context and scopes what is answerable at no cost to this point
03
You receive a scoped proposal: What the workflow would produce and the timeline looks like
04
Go / no-go. Your decision, based on a scoped analysis