As biologic pipelines become more varied, manufacturers need to support different modalities, scales and development pathways. At the same time, artificial intelligence (AI) and supply-chain resilience are changing how companies plan future production.

As a result, the capacity question is shifting beyond volume. Companies need to find the right balance of scale, specialisation, flexibility and regional access to support the next generation of biologics.

Scientific progress is changing capacity requirements

Biologic pipelines are moving in two directions:

 Advances in genomics, diagnostics and disease biology are allowing developers to define diseases more precisely and identify narrower patient populations. This has supported the growth of precision medicine, with therapies increasingly designed around specific molecular characteristics rather than broad indications. Technologies that first emerged in rare and ultra-rare diseases are beginning to move beyond those niches. Gene editing, base editing and antisense oligonucleotides have demonstrated their value in highly targeted settings, and researchers are now exploring whether these platforms can be applied to much larger populations affected by common cardiovascular, metabolic and autoimmune diseases. 

These directions create distinct manufacturing demands. Targeted therapies require lower-volume production and specialised technical knowledge, while successful advanced therapies for a common chronic disease could generate demand at a scale that current platforms were never designed to support. Manufacturers, therefore, need to prepare for greater variation in batch size, process type as well as commercial volume.

The market is splitting between scale and specialisation

These pipeline changes are increasing the need for a broader mix of manufacturing models. Large-scale, standardised production remains important for established biologics as these products benefit from mature processes and efficient platforms.

At the same time, advanced and complex modalities require different capabilities. Antibody-drug conjugates, cell and gene therapies, oligonucleotides, viral vectors and complex injectables often need specialist facilities with technical expertise and tailored process development.

As a result, future capacity is unlikely to come from a single manufacturing model. Large integrated facilities will continue to play an important role, while specialist assets and modality-specific expertise are expected to become increasingly important.

AI could bring manufacturing decisions forward

AI could change the speed and output of biopharmaceutical R&D. Potential applications include target selection, candidate optimisation, clinical recruitment, adaptive protocols, digital twins and in-silico trials.

If AI becomes more embedded across discovery and development, manufacturers may need to plan around less predictable timelines and changing customer pipelines. Outsourcing models are evolving towards platform-aware manufacturing strategies, with capacity investments increasingly shaped by visible pipeline demand and technological differentiation. This places greater emphasis on flexible assets that can support different products, scales and stages of development.

Geography will be shaped by innovation, policy and resilience

Future capacity will depend partly on where companies see scientific opportunity, policy support and supply-chain security:1. Innovation: China has become a major centre of biotech activity, with growing clinical trial activity, new medicine launches and cross-border licensing deals. As China becomes a larger source of molecules and clinical activity, it could also become increasingly important to future manufacturing networks.2. Policy: Governments are also trying to strengthen domestic biotech and biomanufacturing sectors. Regulatory and industrial policy initiatives in the US, UK, Japan and EU aim to accelerate development, improve investment conditions and support strategic life sciences activity.3. Resilience: Organisations are also reassessing supply chain resilience. Hybrid or “right-shoring” models allow companies to retain cost-efficient global supply chains while placing selected high-risk products, critical inputs or strategic activities closer to key markets.These pressures make capacity planning harder through single-site or single-region strategies. As scientific progress creates more varied manufacturing needs, AI becomes more embedded across R&D and supply-chain strategy, influencing where capacity should sit, and CDMOs become central to the capacity question.

CDMOs will play a central role in responding to capacity demands

Companies are seeking specialist capabilities and stronger manufacturing networks. Some capacity may come through new construction, but it may also come from acquisitions, site transfers, repurposed assets and targeted expansion of existing sites.

This gives CDMOs several ways to respond to demand. Large, integrated CDMOs can support broad programmes and end-to-end services, while specialist CDMOs provide deeper expertise in specific modalities or process steps. For sponsors, decisions will increasingly depend on how well the capacity fits the product’s stage of development and long-term manufacturing strategy.

Capacity must follow the pipeline

As pipelines become more varied, a more selective capacity landscape may develop. Large-scale platforms will remain important, but future growth may depend on specialist facilities, flexible assets, regional manufacturing options, CDMO networks and the repurposing of existing sites.

For sponsors and manufacturing partners, capacity must be technically relevant, commercially justified and resilient enough to support products as they move through development.

To learn more about how outsourcing models, CDMO investment, modality complexity and right-shoring strategies are shaping the next phase of pharmaceutical manufacturing capacity, download the latest insight report from CPHI.