Data Science to Improve Manufacturing of Cell Therapies

University of Puerto Rico         

Mayagüez Campus         

Chemistry Department         

Departmental Seminar         

          

Celebrating the 75^th. Anniversary of the ACS of Puerto Rico           

       

Dra. Wandaliz Torres García  

Catedrática de Ingeniería Industrial 

 Universidad de Puerto Rico, Mayagüez  

  

24 de marzo de 2023   

10:30 am   

Química 125  

 Unirse a la reunión de Teams
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Código de acceso: GNMubi  

  

Título: Data Science to Improve Manufacturing of Cell Therapies   

Abstract   

Large-scale, reproducible manufacturing of therapeutic cells with consistently high quality is vital for translation to clinically effective and widely accessible cell therapies. However, the biological and logistical complexity of manufacturing a living product, including challenges associated with their inherent variability and uncertainties of process parameters, currently make it difficult to achieve predictable cell-product quality. Using a degradable microscaffold-based T-cell process, we developed an artificial intelligence (AI)-driven experimental-computational platform to identify a set of critical process parameters and critical quality attributes from heterogeneous, high-dimensional, time-dependent multiomics data, measurable during early stages of manufacturing and predictive of end-of-manufacturing product quality. Sequential, design-of-experiment-based studies, coupled with an agnostic machine-learning framework, were used to extract feature combinations from early in-culture media assessment that were highly predictive of the end-product CD4/CD8 ratio and total live CD4+ and CD8+ naïve and central memory T cells (CD63L+CCR7+). Our results demonstrate a broadly applicable platform tool to predict end-product quality and composition from early time point in-process measurements during therapeutic cell manufacturing.   

  

Biografía:  

Wandaliz Torres-García Contact Information Work: PO Box 9001 Mayagüez, PR 00681 USA 

(787) 832-4040 x3063 

wandaliz.torres@upr.edu  

Interests data mining, statistical learning, bioinformatics, big data analytics, simulation, applied statistics, molecular genomics Education Arizona State University, Tempe, Arizona USA Ph.D., Industrial Engineering, May 2011 Dissertation: “Integrative Analyses of Diverse Biological Data Sources” Committee Members: George C. Runger (Co-chair), Deirdre R. Meldrum (Co-chair), Weiwen Zhang, Jing Li, and Esma S. Gel. University of South Florida, Tampa, Florida USA Masters, Industrial Engineering, May 2006 University of Puerto Rico, Mayagüez, Puerto Rico USA B.S., Industrial Engineering, May 2003