The pharmaceutical sector is vital to the healthcare system. Without it, drug discovery,
development, and distribution would be impossible. When we say “the pharmaceutical …

This review critically examines the integration of Machine Learning (ML) in drug discovery,
highlighting its applications across target identification, hit discovery, lead optimization, and …

The application of machine learning (ML) to solve real-world problems does not only bear
great potential but also high risk. One fundamental challenge in risk mitigation is to ensure …

Computational methods have gained prominence in healthcare research. The accessibility
of healthcare data has greatly incited academicians and researchers to develop executions …

Tailoring optimal treatment for individual cancer patients remains a significant challenge. To
address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression …

Recent advances in treating cutaneous melanoma have resulted in impressive patient
survival gains. Refinement of disease staging and accurate patient risk classification have …

Colorectal cancer represents a leading cause of cancer-related morbidity and mortality.
Despite improvements, chemotherapy remains the backbone of colorectal cancer treatment …

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 …

Background Intra-tumour heterogeneity (ITH) presents a significant obstacle in formulating
effective treatment strategies in clinical practice. Single-cell RNA sequencing (scRNA-seq) …

The intricate nature of biological processes is orchestrated by molecular interactions. The
complexity of these interactions stems from the sheer number of components involved and …