Published on 17 Feb 2026
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Technology transfer, especially in biologics, is rarely a single, linear activity. It is a layered, high-stakes transition that brings development learnings, tacit know-how, engineering rigor, and manufacturing realities into the same room. Anyone who has lived through a biologics technology transfer understands the journey.
What follows is a perspective on why scale-up challenges persist, and how organizations can meaningfully reduce friction by improving data continuity, engineering comparability, and cross-site collaboration.
The Four Distinct Types of Process Transfers, and Why Scale-Up Often Breaks the Smoothest of Plans
Biologics technology transfer is fundamentally a movement of both process and analytical QC methods from process development to commercial manufacturing, or between manufacturing facilities, with typically four distinct transfer models, each driven by different business and operational realities.
- Internal to Internal, the most common scenario in large pharma, where processes move from development to manufacturing,
- Internal to External, typical among early-stage or mid-sized biopharmas who have strong development capabilities but need large-scale GMP capacities,
- External to Internal, common when companies mature and want to internalize outsourced manufacturing for cost control, supply-chain resilience, or IP protection, and
- External to External, the least frequent, driven by strategic realignment, vendor performance issues, or the need for redundancy for high-value products.
Regardless of type, each of these pathways forces one unavoidable reality, the need to scale-up. And scale-up in biologics is inherently unforgiving. Even minor changes in the physical environment can influence critical quality attributes (CQAs). Moving processes from a bench-top process development laboratory to a pilot or a large-scale commercial manufacturing environment is technically complex and risk-prone transition in drug development.
This includes several scale-up issues that practitioners routinely encounter, including:
- Shear stress and mixing challenges, with static mixers that can introduce gradients that simply do not exist at bench-scale,
- Longer hold and transfer times, increasing risks of degradation or aggregation,
- Filtration non-linearities, where larger filter areas lead to unexpected fouling behaviors,
- Media/buffer preparation hurdles, particularly when tens or hundreds of liters must be prepared reproducibly and sterilely, and
- Chromatography inconsistencies, especially with larger columns that introduce packing variability and high backpressure.
These are not abstract hurdles, but rather, tend to compound quickly and can compromise operational flexibility and scheduling. In that sense, scale-up is less about making a process bigger and more about making it behave comparably without compromising on quality.
Digital Knowledge, Scalable Engineering, and the Quiet Importance of Shared Language
A recurring theme is the loss of tacit knowledge, including, the undocumented insights, instincts and rationales accumulated in development environments. Much of the friction in technology transfer traces back to incomplete data capture, across scattered spreadsheets, handwritten notes, or undocumented operator intuition that do not travel well across sites or organizations.
Digitizing Development Early
Implementing electronic lab notebooks (eLNs), LIMS, and standardized digital templates in development allows early experimentation data, including parameters, history, and decisions, to flow cleanly into Manufacturing Science and Technology (MSAT) and production teams. The document stresses the importance of these platforms to ensure structured knowledge transfer, data integrity, and decision transparency.
Designing for Scalability, Not Just Success at Bench Scale
Maintaining comparable process conditions across scales is another anchor point. By selecting development bioreactors and filtration/chromatography systems that align with manufacturing-scale engineering parameters – kLa, P/V, flux, transmembrane pressure (TMP), linear velocity, or column height – teams can better predict behavior during scale-up.
This reduces guesswork, establishes comparable engineering environments, and prevents divergence between development and manufacturing.
Collaboration: The Often-Ignored Variable That Determines Success or Failure
Even with perfect data capture and well-selected equipment, technology transfer ultimately depends on the people executing it. It is evident that site collaboration forms the glue that determines a transfer’s success.
Several on-ground realities stand out:
- Undocumented tacit knowledge will always exist, no matter how digital a development environment becomes. This is why MSAT and MFG teams must spend time observing multiple bench/engineering batches early.
- Teams have misaligned priorities, where development optimizes for product quality, and manufacturing optimizes for flexibility, cost, and compliance. Leadership-level alignment is essential to avoid friction.
- Transfer teams need intentional composition, with a mix of process engineering, manufacturing, and R&D experience, often enhanced through structured rotations or shared project responsibilities.
Technology Transfer Is a Knowledge Discipline, Not a Transaction
Technology transfer is not a single event but a knowledge-driven, integrated process that balances scientific rigor, engineering comparability, and operational reality. Its purpose is not merely to reproduce a process at scale, but to preserve product quality, maintain regulatory compliance, and accelerate time-to-market, all while enabling a culture of cross-functional learning and partnership.
Effective transfers are ultimately about continuity across data, design logic, tacit insights, and collaboration. When organizations commit to that continuity, they strengthen not just the transfer, but the long-term reliability of delivering high-quality therapies to patients.
