Machine Learning for Pharmacogenomics and Precision Medicine

Dear Colleagues,

Delivering the correct drug to the correct patient at the right time while avoiding toxic side effects remains a major limitation of modern medicine across disease modalities. The corpus of available disease-relevant omics data is ever-expanding alongside the increasing panoply of imaging and other relevant data types. Concurrent with this expansion, various machine learning algorithms are becoming increasingly suitable for application using these diverse data types and are even able to integrate multiple types. Together, these advances present the opportunity to ask and answer important questions around pharmacogenomics and precision medicine.

This Topic serves as a compendium for global leaders to present their most recent findings to educate and enhance the work of the broader community. In order to be relevant to experts and newcomers alike, both review and original research articles are invited to this Topic.

Prof. Dr. Weida Tong
Dr. Rebecca Kusko
Topic Editors