13 citations · 15 across the 8 of their papers we have counts for
9 papers
Prior-Fitted Functional Flow: In-Context Generative Models for Pharmacokinetics
César Ojeda, Niklas Hartung, Wilhelm Huisinga +6
We introduce Prior-Fitted Functional Flows, a generative foundation model for pharmacokinetics that enables zero-shot population synthesis and individual forecasting without manual…
Amortized In-Context Mixed Effect Transformer Models: A Zero-Shot Approach for Pharmacokinetics
César Ali Ojeda Marin, Wilhelm Huisinga, Purity Kavwele +2
Accurate dose-response forecasting under sparse sampling is central to precision pharmacotherapy. We present the Amortized In-Context Mixed-Effect Transformer (AICMET) model, a tra…
Hierarchical Bayesian estimation for continual learning during model-informed precision dosing
Franziska Thoma, Niklas Hartung, Manfred Opper +1
Model informed precision dosing (MIPD) is a Bayesian framework to individualize drug therapy based on prior knowledge and patient-specific monitoring data. Typically, prior knowled…
Information-theoretic evaluation of covariate distributions models
Niklas Hartung, Aleksandra Khatova
Statistical modelling of covariate distributions allows to generate virtual populations or to impute missing values in a covariate dataset. Covariate distributions typically have n…
A continued learning approach for model-informed precision dosing: updating models in clinical practice
Corinna Maier, Jana de Wiljes, Niklas Hartung +2
Model-informed precision dosing (MIPD) is a quantitative dosing framework that combines prior knowledge on the drug-disease-patient system with patient data from therapeutic drug/…
Nonparametric goodness-of-fit testing for parametric covariate models in pharmacometric analyses
Niklas Hartung, Martin Wahl, Abhishake Rastogi +1
The characterization of covariate effects on model parameters is a crucial step during pharmacokinetic/pharmacodynamic analyses. While covariate selection criteria have been studie…
A mechanistic framework for a priori pharmacokinetic predictions of orally inhaled drugs
Niklas Hartung, Jens Borghardt
The fate of orally inhaled drugs is determined by pulmonary pharmacokinetic (PK) processes such as particle deposition, pulmonary drug dissolution, and mucociliary clearance. Altho…
Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology
Corinna Maier, Niklas Hartung, Charlotte Kloft +2
Model-informed precision dosing (MIPD) using therapeutic drug/biomarker monitoring offers the opportunity to significantly improve the efficacy and safety of drug therapies. Curren…
Bayesian data assimilation to support informed decision-making in individualised chemotherapy
Corinna Maier, Niklas Hartung, Jana de Wiljes +2
An essential component of therapeutic drug/biomarker monitoring (TDM) is to combine patient data with prior knowledge for model-based predictions of therapy outcomes. Current Bayes…