RT Journal Article
SR Electronic
T1 Prediction of the Human Pharmacokinetics of 30 Modern Antibiotics Using the ANDROMEDA Software
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2023.03.28.534601
DO 10.1101/2023.03.28.534601
A1 Urban Fagerholm
A1 Sven Hellberg
A1 Jonathan Alvarsson
A1 Ola Spjuth
YR 2023
UL http://biorxiv.org/content/early/2023/03/29/2023.03.28.534601.abstract
AB The ANDROMEDA software, based on machine learning, conformal prediction and a new physiologically-based pharmacokinetic model, was used to predict and characterize the human clinical pharmacokinetics of 30 selected modern small antibiotic compounds (investigational and marketed drugs). A majority of clinical pharmacokinetic data was missing. ANDROMEDA successfully filled this gap. Most antibiotics were predicted and measured to have limited permeability, good metabolic stability and multiple elimination pathways. According to predictions, most of the antibiotics are mainly eliminated renally and biliary and every other antibiotic is mainly eliminated via the renal route. Mean prediction errors for steady state volume of distribution, unbound fraction in plasma, renal and total clearance, oral clearance, fraction absorbed, fraction excreted renally, oral bioavailability and half-life were 1.3- to 2.3-fold. The overall median and maximum prediction errors were 1.5- and 4.8-fold, respectively, and 92 % of predictions had <3-fold error. Results are consistent with those obtained in previous validation studies and are better than with the best laboratory-based prediction methods, which validates ANDROMEDA for predictions of human clinical pharmacokinetics of modern antibiotic drugs, which to a great extent demonstrate pharmacokinetic characteristics challenging for laboratory methods (metabolic stability, limited permeability, efflux and multiple elimination pathways). Advantages with ANDROMEDA include that results are produced without the use of animals and cells and that predictions and decision-making can be done already at the design stage.Competing Interest StatementUrban Fagerholm, Sven Hellberg and Ola Spjuth declare shares in Prosilico AB, a Swedish company that develops solutions for human clinical ADME/PK predictions. Ola Spjuth declares shares in Aros Bio AB, a company developing the CPSign software.