Thursday 16 October, 2025
Introduction: Drug-drug interaction (DDI) may result in toxicity or treatment failure of antiretroviral therapy (ARV) or comedications. Despite the high…
Read morePoster: Methodology – AI/Machine Learning
Integrating Random Effects in Scientific Machine Learning Models for Pharmacokinetic Modeling
Thursday 16 October, 2025
Introduction: The last few years have seen a remarkable rise in the use of machine learning (ML) in clinical pharmacology…
Read moreStochastic Gate Neural Networks for Automatic Covariate Selection in Pharmacometrics Population Modeling
Thursday 16 October, 2025
Introduction: Population pharmacokinetic (PK) models describe the behavior of drugs in the body and are usually constructed within a nonlinear…
Read moreMachine Learning algorithms for concentration prediction in anticancer drug therapy: Towards a method for individual dose adjustment
Thursday 16 October, 2025
Introduction: In oncology, under- or overdosing often occurs due to the administration of drug doses not taking into account the…
Read moreDiscovering Intrinsic PK/PD Models Using Physics Informed Neural Networks
Thursday 16 October, 2025
Introduction: Pharmacokinetic-pharmacodynamic (PK/PD) models employ ordinary differential equations (ODEs) for describing the relationship between dose, concentration, intensity, and response duration…
Read moreIdentifying SHAP’s added value to PK covariate modeling on a small dataset
Thursday 16 October, 2025
Introduction: Covariate model building can be the most time-consuming step of popPK modeling. To reduce this time required, several machine…
Read moreData-Driven Discovery of Interpretable Feedback Mechanisms in Acute Myeloid Leukaemia using DeepPumas
Thursday 16 October, 2025
In pharmacometrics, model derivation and selection are critical for quantitatively analyzing drug-biological interactions, elucidating pharmacokinetic/-dynamic (PKPD) relationships, and optimizing dosing…
Read moreMachine learning time-to-event analysis for prediction of 2-month culture conversion with phase 2a information in tuberculosis drug development
Thursday 16 October, 2025
Introduction: In clinical tuberculosis (TB) drug development, phase 2a trials assess early bactericidal activity over two weeks using the time-to-positivity…
Read moreMachine Learning for Antibiotic-Induced Nephrotoxicity Prediction in Korean Hospitalized Patients
Thursday 16 October, 2025
Objectives: Drug-induced nephrotoxicity accounts for 19-26% of cases of acute kidney injury in hospitalized patients[1]. Nephrotoxicity is closely related with…
Read moreGenerative Models for Synthetic Data Generation: Application to PKPD data
Thursday 16 October, 2025
Objectives: The generation of synthetic (artificial) patient data that possess the statistical properties of the original ones plays a fundamental…
Read more