Prediction of Human Pharmacokinetics From Chemical Structure: Combining Mechanistic Modeling with Machine Learning

Author:

Gruber AndreaORCID,Führer Florian,Menz Stephan,Diedam HolgerORCID,Göller Andreas H.ORCID,Schneckener SebastianORCID

Funder

Bayer

Publisher

Elsevier BV

Subject

Pharmaceutical Science

Reference42 articles.

1. Improving the accuracy of predicted human pharmacokinetics: lessons learned from the astrazeneca drug pipeline over two decades;Davies;Trends Pharmacol Sci,2020

2. Evaluation of the success of High-Throughput Physiologically Based Pharmacokinetic (HT-PBPK) modeling predictions to inform early drug discovery;Naga;Mol Pharm,2022

3. Chung T.D.Y., Terry D.B., Smith L.H. In vitro and in vivo assessment of ADME and PK properties during lead selection and lead optimization – guidelines, benchmarks and rules of thumb. In: Markossian S., Grossman A., Brimacombe K., et al., eds.; 2004.

4. Estimating human ADME properties, pharmacokinetic parameters and likely clinical dose in drug discovery;Lucas;Expert Opin Drug Discov,2019

5. Evaluation of generic methods to predict human pharmacokinetics using physiologically based pharmacokinetic model for early drug discovery of tyrosine kinase inhibitors;Ren;Eur J Drug Metab Pharmacokinet,2019

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