The generation of large-scale biomedical data is creating unprecedented opportunities for
basic and translational science. Typically, the data producers perform initial analyses, but it …

The analysis of big healthcare data has enormous potential as a tool for advancing oncology
drug development and patient treatment, particularly in the context of precision medicine …

Background Sharing of participant-level clinical trial data has potential benefits, but
concerns about potential harms to research participants have led some pharmaceutical …

Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape for cancer.
Due to the mechanism of action of ICIs, inflammatory reactions against normal tissue were …

We apply machine-learning techniques to predict drug approvals using drug-development
and clinicaltrial data from 2003 to 2015 involving several thousand drug-indication pairs with …

Patient access to new cancer drugs in the EU involves centralised licensing decisions by
regulators as well as reimbursement recommendations in the context of national healthcare …

Highlights•Cancer is a heterogeneous and evolving disease, yet most drugs are
administered to simply give the maximum dose.•Treatment scheduling currently ignores the …

Background Shifts in data sharing policy have increased researchers' access to individual
participant data (IPD) from clinical studies. Simultaneously the number of IPD meta-analyses …

Background Connected health has created opportunities for leveraging health data to
deliver preventive and personalized health care services. The increasing number of …

Objective Re-identification risk methods for biomedical data often assume a worst case, in
which attackers know all identifiable features (eg, age and race) about a subject. Yet, worst …