In this paper, we review multiscale modeling for cancer treatment with the incorporation of
drug effects from an applied system's pharmacology perspective. Both the classical …

The development of computational models for simulating tumor growth and response to
treatment has gained significant momentum during the last few decades. At the dawn of the …

Glioblastoma is the most malignant brain tumor among adults. Despite multimodality
treatment, it remains incurable, mainly because of its extensive heterogeneity and infiltration …

The main reason why therapeutic schemes fail in Glioblastoma lies on its own peculiarities
as a cancer and on our failure to fully decipher them. Fast tumor evolution, invasiveness and …

This paper discusses the need for interconnecting computational cancer models from
different sources and scales within clinically relevant scenarios to increase the accuracy of …

Secure access to patient data and analysis tools to run on that data will revolutionize the
treatment of a wide range of diseases, by using advanced simulation techniques to underpin …

Glioma is the most aggressive type of brain tumor. Several mathematical models have been
developed during the last two decades, towards simulating the mechanisms that govern the …

Rapid advancements in high-throughput omics technologies and experimental protocols
have led to the generation of vast amounts of biomolecular data on cancer that now …

Distributed and high performance computing are increasingly finding a role in medical
research and ultimately simulation using high performance and distributed computing is …

The Oncosimulator is a top-down discrete entity-discrete event model for multiscale cancer
modeling, that represents the tumor in silico as a 3D matrix of voxels and utilizes the …