Article | August 12, 2026

Reducing Risks In Biologics Manufacturing Through Predictive Modeling And PAT

Source: Lonza

By Alessandro Gallazzi, Director of Global MSAT Mammalian, Conail Murphy, Process Expert, Large Scale MSAT Mammalian, and Erwan Bourles, PhD, Head of Lyophilization Technologies, Drug Product Services

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The growing complexity of next-generation biologics, particularly bispecific antibodies (BsAbs), is increasing development uncertainty while sponsors face mounting pressure to reach IND submission quickly. The central challenge is determining where established platform approaches can be applied confidently and where molecule-specific adaptation is necessary. A knowledge-driven development model addresses this tension by combining platform methods, targeted experimentation, high-throughput screening, and accumulated program experience.

Across analytical development, many methods established for monoclonal antibodies remain applicable to BsAbs and other engineered proteins. Historical program data can help teams assess platform suitability before committing significant resources, allowing experimentation to focus on areas of genuine uncertainty. When platform methods are insufficient, analytical toolboxes incorporating mass spectrometry, advanced potency assays, high-throughput methods, and design-of-experiment approaches can provide targeted solutions.

The same philosophy extends to downstream processing and formulation. Expanded purification toolboxes and high-throughput screening can accelerate evaluation of chromatography conditions, impurity clearance, and product stability. Early formulatability assessments can also identify aggregation and stability risks and inform candidate selection before development resources become heavily committed.

Ultimately, platform intelligence enables organizations to balance speed, flexibility, and scientific rigor. By systematically capturing lessons across programs and combining prior knowledge with focused experimentation, teams can reduce development uncertainty and create a more predictable pathway toward GMP manufacturing and IND readiness.

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