Industry News: Discover the science of AI and machine learning at AAPS 2023 PharmSci 360

20 Sep 2023

Eileen Hannigan and Sarah Nadin, Assay Development team at Merck
SelectScience partners with AAPS to elevate scientific engagement within the pharmaceutical industry

From basic research to manufacturing and analytical characterization, learn about the latest developments in AI and machine learning at the American Association of Pharmaceutical Scientists (AAPS) 2023 PharmSci 360 conference, October 22-25, in Orlando, FL.

AI applications have seen remarkable growth in recent years, revolutionizing the pharmaceutical continuum. PharmSci 360 offers you a unique opportunity to explore the profound implications of AI and machine learning across the drug development pipeline. Learn from AAPS experts as they shed light on the transformative role of AI in your area of science and discuss how it will shape our future.

Attend these sessions and posters to stay up to speed with the rapidly evolving world of AI.

Symposium: Addressing Health Disparities in Basic Science Research

Tuesday, October 24, 9:00 am-9:30 am ET
Harnessing Machine Learning and Protein Structure to Characterize SLC Structure and Function
Avner Schlessinger

Symposium: Advanced Modelling and Predictive Approaches in Drug Development, Manufacturing and Analysis 2

Tuesday, October 24, 9:00 am-9:30 am ET
Recent Advances in Machine Learning for Characterizing Subvisible Particles
Chris P. Calderon, Ph.D., Ursa Analytic

Tuesday, October 24, 9:30 am-10:00 am ET
Deep Learning Models to Reduce False Rejects in Pharmaceutical Manufacturing
Vijay Yadav, Merck & Co.

Symposium: Harnessing the Power of AI/ML in Drug Development

Tuesday, October 24, 9:00 am-9:30 am ET
Understand the Regulatory Environment for AI and Machine Learning
Kim Huynh-Ba, MS, PMP, FAAPS, Pharmalytik Consulting

Tuesday, October 24, 9:30 am-10:00 am ET
The Use of Machine Learning in the Development of Scoring Rule for the Identification of Adult Patients Under the Emergency Use Authorization for Anakinra for Treatment of COVID-19 in the United States
Ruihao Huang, Ph.D., U.S. Food and Drug Administration

Tuesday, October 24, 10:00 am-10:30 am ET
Integrating Machine Learning and Systems Pharmacology to Predict Clinical Outcomes to CAR-T Therapies
Avisek Deyati, Ph.D., Notch Therapeutics

Symposium: Formulation and Delivery for Patient Centric Product Development 2

Wednesday, October 25, 9:00 am-9:30 am ET
Industrial Perspective on Recent Advances in Pediatric Formulation and Delivery Systems
Robert L. Ternik, Ph.D., Rolara Medaka Consulting

Symposium: State-of-the-Art-Tools for Basic Research and Early-Stage Drug Discovery

Wednesday, October 25, 9:00 am-9:30 am ET
Automated Analysis of Organoid Culture Development
James A. Corson, Ph.D., Enthought

Wednesday, October 25, 9:30 am-10:00 am ET
Application of Quantitative Modelling in the Development of Respiratory Medicines
Hochhaus Guenther, Ph.D., University of Florida College of Pharmacy

Symposium: Alternative Approach to Animal Studies

Wednesday, October 25, 10:30 am-11:00 am ET
SafetAI Initiative: AI Based Prediction Initiative For Predicting Toxicity End-Points
Shraddha Thakkar, MSc, M.S., Ph.D., U.S. Food & Drug Administration


  • Machine Learning Predicts Pharmaceutical Inkjet Printing Outcomes
  • Accelerating Development of FDM 3D Printed Medicines with Machine Learning
  • Benchmarking Large Multi-task Machine Learning Models for ADME, Toxicology and Drug Discovery Endpoints
  • Toward the Development of a Self-Driving Laboratory for Nanomedicines
  • Advancing Nanocarrier Therapeutic Development with Structural AI Analysis of Cryo-EM Images

View the full program and register to attend PharmSci 360 online.

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