A5005380946- Computational Drug Discovery Methods
- Pharmacogenetics and Drug Metabolism
- Antibiotic Resistance in Bacteria
- Biosimilars and Bioanalytical Methods
- Cell Image Analysis Techniques
- CAR-T cell therapy research
- Pharmaceutical and Antibiotic Environmental Impacts
- Bacteriophages and microbial interactions
- Technology Adoption and User Behaviour
- Evolution and Genetic Dynamics
- Animal testing and alternatives
- Advanced Electron Microscopy Techniques and Applications
- Statistical Methods in Clinical Trials
- Personal Information Management and User Behavior
- Advanced Fluorescence Microscopy Techniques
- Genomics and Phylogenetic Studies
- Viral Infectious Diseases and Gene Expression in Insects
- Augmented Reality Applications
AstraZeneca (Sweden)
2021-2022
University of Gothenburg
2020
Chalmers University of Technology
2020
Prior to clinical development, a comprehensive pharmacokinetic characterization of novel drug is required understand its exposure at the site action and elimination. Accordingly, in vitro assays animal studies are regularly employed predict humans, which often costly time-consuming. For this reason, prediction human pharmacokinetics point design would be high value for discovery. Therefore, we have established data curation protocol that enables machine learning evaluation 12 vivo parameters...
Animal pharmacokinetic (PK) data as well human and animal in vitro systems are utilized drug discovery to define the rate route of elimination. Accurate prediction mechanistic understanding clearance disposition animals provide a degree confidence for extrapolation humans. In addition, vivo properties can be used improve design during discovery, help select compounds with better properties, reduce number experiments. this study, we generated machine learning models able predict rat PK...
PROteolysis TArgeting Chimeras (PROTACs) use the ubiquitin–proteasome system to degrade a protein of interest for therapeutic benefit. Advances made in targeted degradation technology have been remarkable, with several molecules having moved into clinical studies. However, robust routes assess and better understand safety risks PROTACs need be identified, which is an essential step toward delivering efficacious safe compounds patients. In this work, we used Cell Painting, unbiased...
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 the three main mechanisms: active efflux, ribosomal target protection enzymatic degradation. In last few decades, large number new tetracycline-resistance genes have been discovered in clinical settings. These hypothesized originate from environmental and commensal bacteria, but diversity determinants that not...
Combination therapy or concomitant drug administration can be associated with pharmacokinetic drug-drug interactions, increasing the risk of adverse events and reduced efficacy. Thus far, machine-learning models have been developed that classify interactions. However, to enable quantification effects a interaction, regression-based machine learning should explored. Therefore, this study investigated use predict changes in exposure caused by Fold relative substrate monotherapy were collected...
Summary PROTACs (PROteolysis TArgeting Chimeras) use the ubiquitin-proteasome system to degrade a protein of interest for therapeutic benefit. Advances in targeted degradation technology have been remarkable with several molecules moving into clinical studies. However, robust routes assess and better understand safety risks need be identified, which is an essential step towards delivering efficacious safe compounds patients. In this work, we used Cell Painting, unbiased high content imaging...