Accumulated preclinical data are increasingly being re-used to build and validate predictive
models generated by artificial intelligence (AI)[1] algorithms. Such in silico models have a …

Quantitative and systems pharmacology concepts and tools are the foundation of the model‐
informed drug development paradigm at Merck for integrating knowledge, enabling …

Model-based drug development (MBDD) is an approach that is used to organize the vast
and complex data streams that feed the drug development pipelines of small molecule and …

GLOSSARY OF TERMS USED IN COMPUTATIONAL DRUG DESIGN Page 1 Pure&Appl.
Chem.,Vol. 69, No. 5, pp. 1137-1152, 1997. Printed in Great Britain. 0 1997 IUPAC …

This special issue focuses on computational model for drug research regarding drug
bioactivity prediction, drug-related interaction prediction, modelling for immunotherapy and …

Mathematical modelling: Forecasting cancer | Nature Skip to main content Thank you for
visiting nature.com. You are using a browser version with limited support for CSS. To obtain the …

Systems medicine is an interdisciplinary approach that integrates data from basic research
and clinical practice to improve our understanding and treatment of diseases. Systems …

In the near future, computational tools and methods based on the mathematical modeling of
biomedically relevant networks and pathways will be necessary for the design of therapeutic …

Background: Predicting and tailoring optimal cancer treatments presents a major challenge.
Methods: A computational model (kinetically tailored treatment, or KITT model) is developed …

Highlights•Mathematical models can help discover new drug targets for cancer.•Network-
based modeling can reveal promising single or combinatorial drug targets.•Multiscale …