Hemophilia

Integrating Multi-Structure Covalent Docking with Machine Learning Consensus Scoring Enhances Virtual Screening of Human Acetylcholinesterase Inhibitors

Acetylcholinesterase (AChE) inhibition is a key mechanism in the treatment of neurodegenerative diseases and in counteracting toxic exposures to pesticides and nerve agents. However, virtual screening of AChE remains challenging due to the enzyme’s structural flexibility and the chemical diversity of its covalently binding inhibitors. In this study, we developed an in silico protocol that integrat...

Design of Allosteric Inhibitors for Mutant EGFR by Combined use of Machine Learning and Molecular Dynamics Simulations

The non-small cell lung cancer (NSCLC)-associated Epidermal Growth Factor Receptor (EGFR) mutant L858R/T790M confers resistance to first- and second-generation tyrosine kinase inhibitors (TKIs). Allosteric inhibitors, binding outside the ATP-binding site, have emerged as alternative therapeutic agents. Unlike orthosteric inhibitors, they preferentially stabilize EGFR in an inactive conformation. H...

Image-based morphological profiling of autophagy phenotypes in Zika virus infected cells

Autophagy is a dynamic intracellular process that is essential in maintaining cellular homeostasis. Its potential as a therapeutic target is exemplifi...

Phenotypic Screening Coupled with AI-Driven Target Deconvolution Identifies α-Terthienyl as a Dual DPP-IV/HSD17β13 Modulator with Efficacy in a Mouse Model of MASLD

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent condition characterized by fat build-up in the liver and ranges...

Integration of artificial intelligence and high-content screening enabled identification of drugs for long-term treatment of cerebral cavernous malformation disease

Adults and children with cerebral cavernous malformations (CCMs) are at risk of experiencing lifelong complications such as hemorrhagic strokes, neuro...

A Machine Learning–3D Microvessel Platform Identifies Kinase Targets Restoring Blood-Brain-Barrier Endothelial Integrity

Disruption of the brain endothelial barrier is a hallmark of traumatic brain injury (TBI), and contributes to cerebral edema, coagulopathy, and delaye...

Subtype-Specific Dependencies and Drug Vulnerabilities Enable Precision Therapeutics in Head and Neck Cancer

Molecular heterogeneity in head and neck squamous cell carcinoma (HNSCC) is well recognized, yet existing subtype frameworks remain largely descriptiv...

Electronic Health Record-Based Prediction Models to Inform Decisions about HIV Pre-exposure Prophylaxis: A Systematic Review

Several clinical prediction models have been developed using electronic health records data to help inform decisions about HIV pre-exposure prophylaxi...

irAE-GPT: Leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets

Large language models (LLMs) have emerged as transformative technologies, revolutionizing natural language understanding and generation across various...

ROC Analysis of Biomarker Combinations in Fragile X Syndrome-Specific Clinical Trials: Evaluating Treatment Efficacy via Exploratory Biomarkers

Fragile X Syndrome (FXS) is a rare neurodevelopmental disorder caused by a trinucleotide repeat expansion on the 5’ untranslated region of the FMR1 ge...

Deep Learning-Based Risk Prediction Model for Major Adverse Cardiovascular Events in Long-Term Breast Cancer Survivors

Clinical practice guidelines recommend cardiovascular toxicity risk restratification including evaluation of new cardiovascular risk factors and cardi...

A conversational agent for providing personalized PrEP support – Protocol for chatbot implementation and evaluation

Chatbots have the potential to reduce barriers to pre-exposure prophylaxis (PrEP), including lack of awareness, misconceptions, and stigma, by providi...

Deep learning predicts cardiac output from seismocardiographic signals in heart failure

Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks...

Serum metabolic signatures are associated with anti-drug antibody development in rheumatoid arthritis patients treated with adalimumab

Development of anti-drug antibodies (ADAs) is a barrier to long-term efficacy of biologic therapies in rheumatoid arthritis (RA), but no biomarkers ex...

Predictive Modelling’s role in Improving Pre-exposure Prophylaxis (PrEP) Uptake in High-Risk HIV Groups in Africa: An Integrative Scoping Review

This scoping review explores how predictive modelling can strengthen pre-exposure prophylaxis (PrEP) uptake among high-risk populations in Africa, whe...

Combining blood transcriptomic signatures improves the prediction of progression to tuberculosis among household contacts in Brazil

Tuberculosis remains a major health threat, infecting nearly a third of the world’s population. Of those infected, 5-10% progress from latent infectio...

Spatial biomarker-driven deep learning model via digital pathology predicts response to PI3K inhibitor buparlisib in head and neck squamous cell carcinoma

Buparlisib, a pan-class I PI3K inhibitor, combined with paclitaxel, demonstrated improved survival in the BERIL-1 trial for patients with recurrent/me...

Multiregional CT Features Improve Prediction of Immunotherapy Response in Advanced Melanoma

Immunotherapy has improved outcomes for advanced-stage melanoma, however, predictive biomarkers remain limited. We evaluated whether computed tomograp...

Integrative AI Model Combining Radiomics and Phenomics to Predict Survival in Non-Small Cell Lung Cancer Patients Treated with Immunotherapy Containing Regimen

Immunotherapy has improved outcomes in non-small cell lung cancer (NSCLC), but only a subset of patients achieves durable survival benefit. Convention...

Broad-spectrum coronavirus inhibitors discovered by modeling viral fusion dynamics.

Development of oral, broad-spectrum therapeutics targeting SARS-CoV-2, its variants, and related coronaviruses could curb the spread of COVID-19 and a...