AI/ML-guided Biomaterials Design and Synthesis

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Session Chair(s)

• 

  Indrajit Srivastava, PhD (he/him/his)

  Assistant Professor
  Texas Tech University
  Lubbock, Texas, United States
• 

  Theresa Raimondo, PhD

  Assistant Professor of Engineering
  Brown University, United States

Track Chair(s)

• 

  Josephine Allen, PhD (she/her/hers)

  Professor
  University of Florida, Florida, United States
• 

  Hai-Quan Mao, PhD (he/him/his)

  Professor
  Johns Hopkins University, Maryland, United States
• 

  Huiliang Wang, PhD

  Assistant Professor
  University of Texas at Austin, United States
• 

  Rosalyn Abbott, PhD (she/her/hers)

  Associate Professor
  Department of Biomedical Engineering, Carnegie Mellon University, United States

Presentations:

• 8:45 AM – 9:00 AM EST

  Automation and Active Learning for the Multi-Objective Optimization of Biopharmaceutical Formulations
  

  Presenting Author: David C. Radford, PhD – Rutgers University

  Co-Author: Matthew Tamasi – Rutgers University

  Co-Author: Elena Di Mare (she/her/hers) – Rutgers, The State University of New Jersey

  Primary Investigator: Adam Gormley, PhD (he/him/his) – Rutgers University
• 9:00 AM – 9:15 AM EST

  Data-Driven Design of Novel Polymer Excipients for Pharmaceutical Amorphous Solid Dispersions
  

  Presenting Author: Elena Di Mare (she/her/hers) – Rutgers, The State University of New Jersey

  Co-Author: Ashish Punia, PhD – Merck

  Co-Author: Matthew Lamm, PhD – Merck

  Co-Author: Timothy Rhodes – Merck

  Primary Investigator: Adam Gormley, PhD (he/him/his) – Rutgers University
• 9:15 AM – 9:30 AM EST

  GPT Models to Predict Liquid-liquid Phase Separation Propensity of Peptides
  

  Presenting Author: Ushasi Pramanik, Ph. D (she/her/hers) – Washington University in St. Louis

  Co-Author: Jai Rudra, Ph. D – Washington University in St. Louis

  Co-Author: Abdul Wasim, PhD (he/him/his) – TIFR Hyderabad, India

  Co-Author: Anirban Das, PhD (he/him/his) – Washington University in St. Louis

  Primary Investigator: Jagannath Mondal, PhD – TIFR Hyderabad, India
• 9:30 AM – 9:45 AM EST

  Machine Learning Elucidates Design Features of Lipid Nanoparticles for Cell Type-Preferential Transfection
  

  Presenting Author: Leonardo Cheng, BS (he/him/his) – Johns Hopkins University

  Last Author: Hai-Quan Mao, PhD (he/him/his) – Johns Hopkins University

  Co-Author: Ramya Kumar – Colorado School of Mines

  Co-Author: Yining Zhu, MSE (he/him/his) – Johns Hopkins University

  Co-Author: Jingyao Ma, MSE (he/him/his) – Johns Hopkins University

  Co-Author: Ataes Aggarwal – Johns Hopkins University

  Co-Author: Wu Han Toh (he/him/his) – Johns Hopkins University

  Co-Author: Charles Shin – Johns Hopkins University

  Co-Author: Will Sangpachatanaruk

  Co-Author: Gene Weng – Johns Hopkins University
• 9:45 AM – 10:00 AM EST

  Optimizing Hydrogel Drug Release by Machine Learning
  

  Presenting Author: Chee Meng Eugene Cheong (he/him/his) – Rutgers University New Brunswick

  Primary Investigator: Adam Gormley, PhD (he/him/his) – Rutgers University