Michael Angelo-Anthony Daniele

Adaptive Machine Learning Framework enables Unprecedented Yield and Purity of Adeno-Associated Viral Vectors for Gene Therapy

This paper develops a machine learning framework using Bayesian optimization to enhance the yield and purity of AAV vectors in gene therapy.

Integrating affinity chromatography in the platform process for Adenovirus purification

This paper develops an affinity-based purification process for adenoviral vectors using peptide-functionalized resins, achieving high yield and purity suitable for clinical applications.

Comparative Approaches for Quantification of Product Yield in the Production of Recombinant Green Fluorescent Protein (GFPuv) Expressed in E. coli

The paper compares methods for quantifying GFPuv yield in E. coli bioreactors, identifying optimal harvest times and highlighting the strengths of imaging over other techniques.