Autonomous Impinging Jet Mixing For LNP Process Development

LNP process development has long depended on empirical iteration, a slow and resource-intensive approach that struggles to account for the sensitivity of particle quality attributes to formulation and processing conditions. This webinar examines how impinging jet mixing, when combined with automation, inline analytics, and data-driven optimization, can fundamentally change that dynamic. The session covers automated design of experiments, dynamic process sweeps, self-optimization, and predictive modeling as tools for mapping complex process-property relationships and identifying conditions that achieve target quality attributes more efficiently.

The discussion also addresses the remaining challenges on the path to fully autonomous nanoparticle manufacturing. Watch the webinar to explore how closed-loop experimentation is reshaping LNP development workflows.