OSD
By: Dr. Uwe Hanenberg, Head of Product Development, Recipharm
Key insights:
Late-stage scale-up and manufacturing issues are most often rooted in early development decisions made without sufficient downstream insight
Compressed timelines, limited API supply and rising regulatory expectations increase the cost of rework and late change
Predictive, integrated development approaches improve transferability and enable smoother transition into reliable commercial manufacturing
Many drug product development programmes progress through early phases without major issues, but encounter challenges later during scale-up, tech-transfer or early commercial manufacturing. At that stage, timelines are tighter and options for change are limited.
In most cases, these issues are not driven by unexpected science. They trace back to early decisions that were made without enough insight into how the formulation would behave beyond the laboratory.
Development teams are being asked to do more with less. Programmes move faster, APIs are available in smaller quantities, and regulatory expectations continue to rise. At the same time, internal formulation and analytical expertise has declined across much of the industry, increasing reliance on external partners.
The challenges are well recognised:
When development is approached as a series of isolated activities, without clear alignment to an overall regulatory and related clinical strategy, late-stage issues become difficult to avoid. One factor is particularly critical: the regulatory pathway must be defined early and communicated clearly across the development programme, with the clinical strategy aligned accordingly.
When this is not done, or when regulatory assumptions are not consistently shared, important activities can be overlooked. This is one of the most common causes of late-stage surprises, rework, or “forgotten” requirements that only emerge once timelines are already under pressure.
Traditional development approaches often focus on whether a formulation meets lab-scale targets, without fully understanding why it behaves as it does. These programmes may look successful early on, only to encounter issues during compression, scale-up or stability testing.
By the time those issues emerge, the cost of change is high, both financially and in lost momentum. What is increasingly needed is a shift from reactive problem-solving to predictive decision-making.
Predictive development starts with building scientific understanding early. Material attributes, processing behaviour and critical formulation parameters are assessed up front to anticipate how a product will perform at larger scale, before those decisions become locked in.
This approach is particularly important when:
Development choices made with scale in mind reduce the risk of rework and help maintain programme velocity.
Another common source of delay is fragmentation of the work. When formulation development, analytical development and scale-up are treated as separate activities, often handled by different teams or suppliers, important context is lost.
Integrated development models allow formulation and analytical challenges to be solved together, improving both speed and robustness. Issues are identified earlier, and solutions are designed with manufacturing and transfer requirements in mind. This is especially valuable for stability-sensitive products, complex release profiles and programmes requiring rapid method development and transfer.
Clear development governance and cross-functional stage gates help reduce risk by keeping technical progress, regulatory strategy and manufacturing readiness aligned throughout the programme. At defined points, progress is assessed against agreed objectives to confirm readiness to proceed, with assumptions, dependencies and risks reviewed early before they impact timelines or scope.
Rather than adding complexity, this type of governance provides structure and clarity. It supports development as a connected system, enables consistent decision-making across teams, and helps ensure programmes move forward with the right inputs in place, reducing the likelihood of late-stage surprises during scale-up and technology transfer.
For development teams, success is not defined by innovation alone. It is defined by predictability. Programmes that transition smoothly into manufacturing are typically those where scale-up behaviour has already been anticipated.
The objective is uneventful manufacturing, processes that behave as expected without unexpected deviations.
As development environments have changed and become more complex, the role of external partners is shifting. The value lies less in executing experiments and more in supporting early decisions that hold up through scale-up, regulatory review and commercial supply.
In this context, development insight becomes a practical requirement rather than a theoretical one. It directly influences programme timelines, risk exposure and long-term viability.
Recipharm helps pharma companies reduce development risk by applying data-led development approaches, using statistical methods and material understanding to support better decisions early in development.
Formulation and analytical development are considered together, with early attention to how products are likely to behave during scale-up, technology transfer and commercial manufacturing. This allows potential issues to be identified and addressed earlier, reducing rework and late-stage surprises.
By combining scientific expertise with data-driven insight and a clear understanding of manufacturing and regulatory requirements, Recipharm supports development programmes that progress more predictably, even when timelines are compressed, API availability is limited or product complexity is high.