A5092349153- Single-cell and spatial transcriptomics
- Cancer Genomics and Diagnostics
- Immune responses and vaccinations
- Cancer Immunotherapy and Biomarkers
- Health Systems, Economic Evaluations, Quality of Life
- Computational Drug Discovery Methods
- CAR-T cell therapy research
- Biosimilars and Bioanalytical Methods
Institute for Molecular Medicine Finland
2023-2025
University of Helsinki
2023-2025
Helsinki University Hospital
2024
Abstract RepurposeDrugs (https://repurposedrugs.org/) is a comprehensive web-portal that combines unique drug indication database with machine learning (ML) predictor to discover new drug-indication associations for approved as well investigational mono and combination therapies. The platform provides detailed information on treatment status, disease indications clinical trials across 25 categories, including neoplasms cardiovascular conditions. current version comprises 4314 compounds...
Abstract Summary The limited resolution of spatial transcriptomics (ST) assays in the past has led to development cell type annotation methods that separate convolved signal based on available external atlas data. In light rapidly increasing ST assay technologies, we made and investigated performance a deconvolution-free marker-based method called scType. contrast existing methods, application scType does not require computationally strenuous deconvolution, nor large single-cell reference...
Abstract Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in patients with advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number possible drug-dose combinations vastly exceeds what could be tested scarce patient cells. Here, we developed scTherapy, machine learning model leverages single-cell...