ACoP15 Posters

ACoP15
Posters
SxP reviewed the ACoP program and abstracts to select content of interest for SxP
Published

November 7, 2024

Link to the ACoP15 program and abstracts

Monday Nov 11

  • (M-004)
    • MBMA Bridging Models as A Tool for Exploration of Clinical Endpoints in Unstudied Indications [MBMA]
  • (M-027)
    • Model-based meta-analysis of safety for monomethyl auristatin E-conjugated antibody drug conjugates in cancer patients [MBMA]
  • (M-036)
    • Pharmacometric-Pharmacoeconomic Modeling and Simulation in Atopic Dermatitis: Informing Early Drug Development Decisions for a Hypothetical New Therapeutic [Early development decision making]
  • (M-051)
    • The impact of misspecified covariate models on inclusion and omission bias when using FREM and FFEM [Statistical methodology]
  • (M-061)
    • A clinical trial simulator tool for a randomized delayed start trial in Parkinson’s disease [Tools]
  • (M-091)
    • Fully Bayesian Covariate Selection in Population Pharmacokinetics and Pharmacodynamics Models Using Regularized Horseshoe Priors [Bayesian statistics]
  • (M-099)
    • Advancing Drug Development in Relapsed and Refractory Multiple Myeloma (RRMM): Assessing the Safety and Efficacy Landscape Utilizing Model-Based Meta-Analysis [MBMA]
  • (M-108)
    • How should we leverage prior adult knowledge for pediatric PK analysis? - A case study comparing Pooled and Bayesian population PK approaches [Bayesian statistics]
  • (M-135)
    • A Bayesian disease progression model for Major Depressive Disorder [Bayesian statistics]

Tuesday Nov 12

  • (T-016)
    • Bridging the Gap: A Comprehensive Checklist for Hybrid Pharmacometrics-Machine Learning Model Building to Support Oncology Clinical Development [AI/ML]
  • (T-024)
    • A Bayesian Approach to Item Response Theory Modeling for Exposure-Response Relationships in Stan [Bayesian Statistics]
  • (T-042)
    • Use of Model-informed Drug Development and Natural History Data to Inform the Development of Iluzanebart in ALSP: A Neurological Rare Disease [MIDD]
  • (T-056)
    • A modified Bayesian information criterion (mBIC) with multiple testing correction for population pharmacokinetic model building [Statistical methodology]
  • (T-057)
    • Hybrid Population PK-Machine Learning Model Approach to Predict Infliximab Concentrations in Pediatric Patients with Crohn’s Disease [AI/ML]
  • (T-075)
    • Enhancing Parameter Estimation Process for Pharmacokinetic-Pharmacodynamic Models with Meta-heuristic Optimization Approaches [Statistical methodology]
  • (T-078)
    • A Bayesian Semi-Mechanistic Dose-Finding Design for Phase I Drug Combination Trials in Oncology [Bayesian statistics]
  • (T-091)
    • Fast Stepwise Selection Methods for Efficient Covariate Model Development in Population Data Analysis [Statistical methodology]
  • (T-135)
    • Potential Bias Evaluation of Conventional Exposure-Response Analysis Methods: A Small Molecule Cancer Drug Example [Statistical methodology]

Wednesdsay Nov 13

  • (W-003)
    • Leveraging Machine Learning and Real-World Data: Time-to-Event Analysis of COVID-19 Patients Using Electronic Health Records [AI/ML, RWD/RWE]
  • (W-008)
    • The reference corrected VPC (rcVPC) - An informative model diagnostic for assessing underlying exposure-response relationships [Tools]
  • (W-032)
    • Longitudinal Joint Modeling of Modified Mayo Score and Dropout in Patients with Moderate to Severely Active Ulcerative Colitis [Statistical Methodology]
  • (W-045)
    • Clinical Trial Simulation to Assess Sample Size and Power For Detecting Differences in Pharmacokinetic Exposure Metrics [Statistical Methodology]
  • (W-055)
    • Confounding Impact of Event-Driven Exposure Phenomenon on Summary Exposure Metrics in Time-to-Event Exposure Response Analyses [Statistical Methodology]
  • (W-069)
    • Exploring Appropriate Prior Distributions for Covariance Matrix Estimation in Bayesian Population Pharmacokinetic Analysis [Bayesian statistics]
  • (W-084)
    • Exploring the feasibility of using AI to identify patient characteristics predictive of histological endpoints in metabolic dysfunction associated steatohepatitis (MASH) [AI/ML]
  • (W-099)
    • Constructing a virtual control arm and evaluating operating characteristics using TGI metrics to support go/no-go decisions for single-arm Phase Ib/II combination studies [Virtual control arm]
  • (W-114)
    • Consideration of Study design aspects in the creation of virtual populations for organ impairment studies: One size may not fit all [Virtual control arm]
  • (W-133)
    • Losing the Forest: Causal Shapley Additive Explanations for Interpretation of Population-Pharmacokinetic models [Statistical Methodology]
  • (W-141)
    • Disease progression modeling of myositis from real-world data [RWD/RWE]