Machine Learning Models for Human In Vivo Pharmacokinetic Parameters with In-House Validation

F Miljkovic, A Martinsson, O Obrezanova… - Molecular …, 2021 - ACS Publications
Prior to clinical development, a comprehensive pharmacokinetic characterization of a novel
drug is required to understand its exposure at the site of action and elimination. Accordingly, …

Cell morphological profiling enables high-throughput screening for PROteolysis TArgeting Chimera (PROTAC) phenotypic signature

…, K Juhani, R Turkki, F Miljkovic, A Martinsson… - ACS Chemical …, 2022 - ACS Publications
PROteolysis TArgeting Chimeras (PROTACs) use the ubiquitin–proteasome system to
degrade a protein of interest for therapeutic benefit. Advances made in targeted protein …

Prediction of in vivo pharmacokinetic parameters and time–exposure curves in rats using machine learning from the chemical structure

O Obrezanova, A Martinsson, T Whitehead… - Molecular …, 2022 - ACS Publications
Animal pharmacokinetic (PK) data as well as human and animal in vitro systems are utilized
in drug discovery to define the rate and route of drug elimination. Accurate prediction and …

Comprehensive screening of genomic and metagenomic data reveals a large diversity of tetracycline resistance genes

F Berglund, ME Böhm, A Martinsson… - Microbial …, 2020 - microbiologyresearch.org
Tetracyclines are broad-spectrum antibiotics used to prevent or treat a variety of bacterial
infections. Resistance is often mediated through mobile resistance genes, which encode one …

A parameter-free perfectly matched layer formulation for the finite-element-based solution of the Helmholtz equation

R Cimpeanu, A Martinsson, M Heil - Journal of Computational Physics, 2015 - Elsevier
This paper presents a parameter-free perfectly matched layer (PML) method for the finite-element-based
solution of the Helmholtz equation. We employ one of Bermúdez et al.'s …

Comparing the applications of machine learning, PBPK, and population pharmacokinetic models in pharmacokinetic drug–drug interaction prediction

J Gill, M Moullet, A Martinsson… - CPT …, 2022 - Wiley Online Library
The gold‐standard approach for modeling pharmacokinetic mediated drug–drug
interactions is the use of physiologically‐based pharmacokinetic modeling and population …

Evaluating the performance of machine‐learning regression models for pharmacokinetic drug–drug interactions

J Gill, M Moullet, A Martinsson… - CPT …, 2023 - Wiley Online Library
Combination therapy or concomitant drug administration can be associated with pharmacokinetic
drug–drug interactions, increasing the risk of adverse drug events and reduced drug …

The simulated tempering method in the infinite switch limit with adaptive weight learning

A Martinsson, J Lu, B Leimkuhler… - Journal of Statistical …, 2019 - iopscience.iop.org
We investigate the theoretical foundations of the simulated tempering (ST) method and use
our findings to design an efficient accelerated sampling algorithm. Employing a large …

Accelerated sampling schemes for high dimensional systems

A Martinsson - 2020 - era.ed.ac.uk
In this thesis we discuss accelerated sampling schemes for high dimensional systems, for
example molecular dynamics (MD). The development of these methods is fundamental to the …

Transferability of operational status classification models among different wind turbine types

Z Trstanova, A Martinsson, C Matthews… - Journal of physics …, 2019 - iopscience.iop.org
A detailed understanding of wind turbine performance status classification can improve
operations and maintenance in the wind energy industry. Due to different engineering properties …