Controlling UF/DF with Confidence: How to Define, Monitor, and Hit Critical Endpoints

A practical framework for reducing variability, minimizing manual sampling, and improving run-to-run consistency with modern UF/DF control strategies.

August 26, 2026 | 11:00 AM ET

Ultrafiltration Diafiltration (UF/DF) is often treated as a straightforward concentration and buffer-exchange step, but teams know the reality looks different. Small differences in setup, endpoint definition, and in-process decision-making can create major run-to-run variability, especially as programs move from process development into scale-up and manufacturing.

In this webinar, we will focus on the practical question that determines whether UF/DF is repeatable and scalable: How do you define the right endpoints, monitor them in real time, and consistently hit them without relying on constant manual sampling and operator intervention? We will walk through a clear approach to selecting critical UF/DF endpoints (for concentration and diafiltration), connecting them to the right measurements, and using in-line analytics to improve accuracy and consistency.

Key topics include:
What “critical endpoints” really mean in UF/DF, and why unclear endpoints drive variability across runs and teams
Endpoint selection made practical: choosing concentration and diafiltration endpoints that align with process goals and downstream requirements
How real-time, in-line concentration data enables automated control, reducing manual sampling and dilution while improving efficiency, consistency, and decision-making
Reducing variability across scales by linking endpoint definition, monitoring strategy, and execution consistency from PD through manufacturing
Troubleshooting through the lens of control: how clearer endpoints and better monitoring help teams respond faster to instability and performance drift

Whether you are building a UF/DF strategy in development, preparing for tech transfer, or tightening control in manufacturing, this session will provide practical guidance for making UF/DF easier to run, easier to scale, and easier to reproduce.