ACoP14 Programming

SxP reviewed the ACoP program and abstracts to select content of interest for SxP

ACoP14
Program
Published

November 1, 2023

Link to the ACoP14 program and abstracts

Monday Nov 6

11:15 AM - 1:00 PM Concurrent Session 1B - The present and future of MIDD: focusing on drug develop- ment and human health:

  • Hugo Geerts: Moving Boundaries: Towards Virtual Twin Pa- tients in Clinical Trials and Precision Medicine for CNS Disorders [Statistical Methodology]

11:15 AM - 1:00 PM Concurrent Session 1C - Redefining Pharmacometrics: Is machine learning need-to-have or nice-to-have?:

  • Antari Khot: Are ML methods superior to Cox proportion- al-hazards model for survival analysis? The answer may surprise you! [AI/ML]

2:30 PM - 4:30 PM Concurrent Session 2B - Emerging use of non-traditional healthcare data sources to enhance the impact of MIDD in advancing drug development program:

  • Flora Musuamba Tshinanu: Regulatory perspective on non-traditional healthcare data sources [Real World Evidence]

Tuesday Nov 7

12:30 - 2:00 PM SxP SIG Lunch

  • SxP SIG Lunch - no tickets required this year!

2:00 PM - 3:30 PM Concurrent Session 3A - Integration of PMx approaches to model-informed decision making: Across SIG Perspectives:

  • Kosalaram Goteti: Integrating statistics and PMx techniques for model-informed decision making in SLE - SxP SIG [Bayesian Statistics, AI/ML, Latent Variable Models, Disease Progression]

Wednesdsay Nov 8

9:00 AM - 11:00 AM Roller Coaster 1:

  • Ahmed Elmokadem: UDE Know It If UDE Saw It: Leveraging Deep Machine Learning for QSP Model Development and Evaluation [AI/ML]
  • Robert Bies: Exploration of multiple AI search algorithms for nonlinear mixed effects model identification [AI/ML]

9:00 AM - 11:00 AM Roller Coaster 2:

  • Dominic Braem: Modelling pharmacometrics data with Neural ODEs including inter-individual variability [AI/ML]

1:30 PM - 3:00 PM Concurrent Session 5A - May the odds be ever in your favor: Innovative Approaches to improve Go/No-Go (GNG) decision making in Oncology:

  • Madhav Channavazzala: Leveraging historic data for generating a rigorous Synthetic Control Arm that accounts for patient covariates [Statistical Methodology]