Thursday 7 May, 2026
Introduction Artificial intelligence and machine learning (AI/ML) approaches are increasingly being applied across pharmacometrics, including QSP, PBPK and population PK/PD….
Read morePoster: Methodology – AI/Machine Learning
INTERPRETABLE MACHINE LEARNING-BASED DECISION SUPPORT FOR POPULATION PHARMACOKINETIC DIAGNOSTICS UNDER REALISTIC SHRINKAGE AND SPARSITY CONDITIONS
Thursday 7 May, 2026
Introduction Model development in population pharmacokinetics is inherently iterative and largely guided by qualitative interpretation of diagnostic plots and fit…
Read moreAn Interactive Shiny Application for Machine Learning-Driven Covariate Selection in Pharmacometrics
Thursday 7 May, 2026
Introduction/Objectives: Machine learning (ML)-based approaches are efficient alternatives to stepwise covariate modeling (SCM) for covariate selection in pharmacometrics [1,2]. The…
Read moreNONMEM IMPLEMENTATION OF NEURAL NETWORKS AS FLEXIBLE MODELS OF HAZARD FUNCTIONS IN JOINT MODELS
Thursday 7 May, 2026
Introduction In recent years, machine learning (ML) models have gained popularity in pharmacometrics. However, these two quantitative fields differ markedly…
Read moreTOWARD AUTONOMOUS PHARMACOMETRICS: A MULTI AGENT FRAMEWORK FOR STRUCTURE DISCOVERY, COVARIATE SELECTION AND GRAY-BOX MODELING
Thursday 7 May, 2026
Objectives: Developing population pharmacokinetic (PopPK) models is an iterative, expert-dependent process. We present an autonomous multi-agent framework capable of performing…
Read moreMULTI-AGENT AI APPLICATION FOR INTERACTIVE EXPLORATORY CLINICAL DATA ANALYSIS IN R
Thursday 7 May, 2026
Introduction/Objectives: Exploratory data analysis (EDA) of clinical study data requires rapid iteration on visualizations and data summaries, yet many workflows…
Read moreHomoscedastic Uncertainty Weighting-Enhanced Multi-Task Multi-Granularity NER for Pharmacokinetic Parameters
Thursday 7 May, 2026
Objectives: The exponential growth of pharmacological information in unstructured sources such as scientific publications and clinical trial reports presents a…
Read moreHybrid AI-PBPK Framework for End-to-End Pharmacokinetic Prediction from SMILES
Thursday 7 May, 2026
Objectives: Drug development requires scalable and traceable pharmacokinetic (PK) prediction frameworks that support compound prioritization and model-informed translation across development…
Read moreDIRECT AND HYBRID MACHINE LEARNING APPROACHES DO NOT OUTPERFORM NLME-BASED FULL BAYESIAN FORECASTING FOR EARLY IDENTIFICATION OF DELAYED METHOTREXATE ELIMINATION
Thursday 7 May, 2026
INTRODUCTION Nonlinear mixed-effects (NLME) models with Bayesian forecasting are widely used for model-informed clinical decision-making, including guidance of post-infusion care…
Read moreAutomatic digitization of time series plots from published sources with EVA application
Thursday 7 May, 2026
Objectives: Extraction of quantitative data from published figures is a necessary but dreary and severely time-consuming step that follows systematic…
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