End-to-End System for Estimating Crystallization Kinetics Using a Deep Learning-Based Approach

High Resolution Image Download MS PowerPoint Slide Protein crystallization has emerging potential as an efficient and scalable purification approach in biopharmaceutical manufacturing. However, quantitative modeling of crystallization kinetics remains challenging due to limited experimental data quality, difficulty in detecting and characterizing crystals from noisy images, and lack of robustness in parameter estimation across diverse conditions. This study presents an end-to-end system for estimating crystallization kinetics by integrating deep learning-based image analysis with droplet-based crystallization experiments. Synthetic crystal images with realistic noise and morphological variations are employed to train robust models for crystal detection and dimension prediction. These predictions are then coupled with experimental time-series data to extract nucleation and growth data thr…