Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs
for new medical indications. Several machine learning (ML) and artificial intelligence (AI) …

Cancer claims millions of lives yearly worldwide. While many therapies have been made
available in recent years, by in large cancer remains unsolved. Exploiting computational …

Resistance to therapy remains a major cause of cancer treatment failures, resulting in many
cancer-related deaths. Resistance can occur at any time during the treatment, even at the …

Artificial intelligence (AI) has transformed pharmacological research through machine
learning, deep learning, and natural language processing. These advancements have …

Purpose. Artificial intelligence (AI) techniques are used in precision medicine to explore
novel genotypes and phenotypes data. The main aims of precision medicine include early …

For an increasing number of preclinical samples, both detailed molecular profiles and their
responses to various drugs are becoming available. Efforts to understand, and predict, drug …

Drug response prediction is important to establish personalized medicine for cancer therapy.
Model construction for predicting drug response (ie, cell viability half-maximal inhibitory …

Motivation Predicting drug response is critical for precision medicine. Diverse methods have
predicted drug responsiveness, as measured by the half-maximal drug inhibitory …

Simple Summary Glioblastoma (GBM) is a type of primary brain cancer that is extremely
aggressive and almost always fatal. To examine the response to treatment and classify GBM …

Simple Summary There is an unmet need for novel anticancer therapeutics that work
differently to current standard-of-care therapies. BOLD-100 is a unique clinical-stage …