Lab to launch: the strategic advantage of scalability
Whether you’re a large biopharma giant or small start-up, the ability to scale your processes effectively can make all the difference to commercial success.
The pharmaceutical industry is moving fast
Macro and micro forces are accelerating scientific breakthroughs, while companies face pressure to deliver shareholder value and bring novel biologics to market. High-impact modalities, such as GLP-1 anti-obesity agonists, immuno-oncology drugs, and cell and gene therapies (CGT), are raising the stakes for speed, robustness and compliance.
For many teams, the race is to reach Good Manufacturing Practice (GMP) as quickly as possible. But developing a promising bioprocess at the bench is not the same as producing it at scale - consistently, safely and profitably - meeting GMP expectations.
Precision is especially critical in active pharmaceutical ingredients (APIs) production: even small variations introduced during scale-up can affect quality and efficacy. In modern drug development, scalability is not a downstream detail. It’s a strategic requirement that can determine whether a candidate becomes a manufacturable medicine.
From lab to launch: key decision points where early scalability enables smoother clinical and commercial manufacturing.
Design scalacility from the start
Scalability should be designed in from day one. Early decisions - such defining critical process parameters, standardizing technologies, planning the scale‑up strategy and applying data‑driven control - help reduce risk, improve consistency and enable smoother transitions from development through clinical phases into GMP commercial manufacturing.
By aligning development and manufacturing teams early, companies can avoid costly rework, accelerate tech transfer and build a stronger foundation for regulatory compliance. A structured, scalable approach ultimately shortens time to market while support robust, repeatable production at commercial scale.
What to prioritize to unlock the value of smooth production?
Scalable bioprocesses hinge on several key elements.
The first of these factors is a deep understanding of the process itself, which requires identifying the critical variables that influence performance and understanding how to optimize them during each stage of product development.
Once this foundation is laid, biopharmaceutical manufacturers can focus on equipment scalability.
As production increases, equipment of all types - from bioreactors to utility purification systems - must be considered to ensure smooth accommodation for larger batches and higher volumes, without compromising performance or creating bottlenecks. And finally, reliable measurement can make or break a scale-up effort. Consistent and accurate data are essential for making informed decisions regarding operational efficiency, production throughput and quality throughout the project.
What makes scale-up and technology transfer so challenging?
Scale-up challenges rarely sit only in the unit operation. They also emerge because analytical and quality measurement must scale with the process.
Common friction points include:
- Distributed operations across the lifecycle: R&D, clinical, and commercial manufacturing often happen at different sites.
- Mixed equipment environments: instrumentation from multiple manufacturers may not share data natively.
- Measurement inconsistencies: even similar instruments from different suppliers can behave differently due to design, materials, or compensation algorithms.
Many critical parameters are still assessed using offline lab methods. That approach can introduce variability due to sampling technique, handling, the gap between real-time process conditions and lab results. Delays between sampling and data can prevent feedback control, reduce efficiency, and increase risk of deviations, especially when variables shift during a production run.
When scale, location, or instrumentation changes, variability often increases. If parameter values drift outside specifications, product quality can be impacted, and batch loss risk rises.
How do you design a scalable bioprocess from the early stages?
A successful scale-up starts with a clear definition of a scalable bioprocess, especially for biologics and advanced therapies. The goal is a process that is:
- Transferable to manufacturing
- Replicable across sites and equipment
- Compatible with different bioreactor setups
In practice, that means designing for transfer across scenarios such as:
- Stainless steel vs. single use
- Different agitation designs
- Different sensor ports and installation constraints
Scalability is a holistic discipline that integrates:
- Process understanding (what matters and why). Teams need deep process understanding to identify the critical variables that influence performance, and to determine how to optimize and control them at each stage, especially the scale-relevant parameters.
- Equipment upscale (what must hold at larger volumes). Bioreactors, utilities, and purification systems must support larger batches without bottlenecks or loss in performance or quality.
- Measurement reliability (decisions depend on data). Reliable measurement is essential for decisions on operational efficiency, throughput, and quality. For this reason, many biomanufacturers prefer to standardize sensor and analytical technology from lab through large-scale production to avoid measurement discrepancies during scale-up.
Why easy scalability matters
Scalable bioprocesses don’t happen by chance—they’re built on consistent, reliable measurements. From early experiments to full-scale production, data continuity is critical to reducing risk, accelerating scale-up, and protecting yield.
Discover why scalability matters and how a scalable bioprocessing measurement approach can support confident decisions at every stage.
The role of single-use technology (SUT) in enabling faster process development
Speed is the ultimate competitive advantage in biopharma.
Every day shaved off development timelines can mean earlier clinical trials, faster regulatory submissions and a stronger market position. Single-use technology (SUT) accelerates this journey by eliminating time-intensive steps like cleaning and sterilization, reducing changeover downtime and enabling parallel processing.
SUT offers a flexible, modular alternative to traditional stainless-steel systems. It eliminates time-consuming cleaning and sterilization steps associated with fixed infrastructure. By utilizing disposable components, SUT enables rapid process iterations and seamless transitions between different production scales.
This agility is crucial in today’s the competitive biopharma industry.
Inline measurement advantages
For process optimization, real-time, inline process analysis can solve a core scale-up problem: understanding what is happening in the process as it happens, at any scale.
One established Process Analytical Technology (PAT) approach is Raman spectroscopy. Endress+Hauser’s Raman systems enable real-time, non-destructive monitoring of critical process parameters (CPPs).
Raman systems use robust optical methods to measure composition and concentration, supporting continuous monitoring of parameters such as:
- Glucose concentration
- Viable cell density
- Lactate
- Amino acids
- Protein titer
- Cell density
- CQA surrogates
A key scale-up advantage is consistency: the same Raman instruments used for small-scale experiments can be integrated into larger-scale bioreactors. This helps maintain comparable measurement approaches across development and manufacturing, supporting consistent product quality, including in API production contexts where variability can be particularly consequential.
Inline measurement replaces offline sampling with real‑time insight - enabling faster decisions, better control and scalable PAT models across manufacturing stages.
Why inline measurement matters
Offline measurement workflows rely on sampling and delayed analysis, limiting process insight and control. In contrast, inline measurement integrates sensors directly into the reactor, enabling continuous monitoring of critical process parameters and quality attributes. This real‑time visibility supports faster, more informed decisions and reduces the risk of variability or deviation.
By eliminating sampling and enabling consistent optics across scales, inline workflows provide a strong foundation for model predictive control and transferable PAT models. The result is a more robust, scalable manufacturing strategy that improves process understanding, supports automation and accelerates the path from development to commercial production.
A further benefit of using Raman spectroscopy in bioprocessing is the transferability of its predictive models across different production scales. Provided that the optical components and probe geometry remain consistent, the spectral fingerprint obtained during analysis is stable whether at laboratory or larger manufacturing scale. This stability means that predictive models developed and validated in the laboratory can be confidently applied to larger-scale production, significantly reducing the need for extensive revalidation processes.
This seamless model transfer supports consistent Process Analytical Technology (PAT) control throughout the stages of scale-up, helping maintain robust process monitoring and quality assurance.
How are Memosens sensors so accurate - and why does it matter at scale?
Alongside inline analytics, robust sensor infrastructure is critical for GMP operations. Memosens digital sensor technology provides highly accurate measurements with minimal maintenance requirements through reliable, non-contact signal transmission.
Key capabilities include:
- Plug-and-play, pre-calibrated sensors to minimize downtime
- Digital data transmission to eliminate signal interference
- Predictive maintenance to improve reliability over time
What does this improve in real operations?
In practical terms, digital sensors support smoother production and more consistent operations across sites by:
- Helping standardize measurement practices
- Maximize data reliability by digital signal transmission in contactless connectors
- Simplifying maintenance and calibration workflows
These advantages become increasingly important when processes move into round-the-clock cGMP operations at commercial scale.
Everything you need to know
Scaling a bioprocess from lab to GMP manufacturing is not a linear exercise. It requires early design decisions that protect product quality, enable transferability, and reduce risk as volumes, sites, and technologies change. The questions below address the most critical considerations highlighted in this article.
