Independent drug action in combination therapy: implications for precision oncology
Combination therapies are superior to monotherapy for many cancers. This advantage was
historically ascribed to the ability of combinations to address tumor heterogeneity, but …
historically ascribed to the ability of combinations to address tumor heterogeneity, but …
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing drugs for central nervous system (CNS) disorders remains the most …
[HTML][HTML] Effective drug combinations in breast, colon and pancreatic cancer cells
P Jaaks, EA Coker, DJ Vis, O Edwards, EF Carpenter… - Nature, 2022 - nature.com
Combinations of anti-cancer drugs can overcome resistance and provide new treatments,.
The number of possible drug combinations vastly exceeds what could be tested clinically …
The number of possible drug combinations vastly exceeds what could be tested clinically …
Deep learning identifies synergistic drug combinations for treating COVID-19
Effective treatments for COVID-19 are urgently needed. However, discovering single-agent
therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV …
therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV …
DeepTraSynergy: drug combinations using multimodal deep learning with transformers
Motivation Screening bioactive compounds in cancer cell lines receive more attention.
Multidisciplinary drugs or drug combinations have a more effective role in treatments and …
Multidisciplinary drugs or drug combinations have a more effective role in treatments and …
CancerGPT for few shot drug pair synergy prediction using large pretrained language models
Large language models (LLMs) have been shown to have significant potential in few-shot
learning across various fields, even with minimal training data. However, their ability to …
learning across various fields, even with minimal training data. However, their ability to …
CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics
Abstract CellMiner Cross-Database (CellMinerCDB, discover. nci. nih. gov/cellminercdb)
allows integration and analysis of molecular and pharmacological data within and across …
allows integration and analysis of molecular and pharmacological data within and across …
[HTML][HTML] Evaluation of synergism in drug combinations and reference models for future orientations in oncology
Current cancer therapy includes a variety of strategies that can comprise only one type of
treatment or a combination of multiple treatments. Chemotherapy is still the gold standard for …
treatment or a combination of multiple treatments. Chemotherapy is still the gold standard for …
[HTML][HTML] Drug combination therapy for emerging viral diseases
ZA Shyr, YS Cheng, DC Lo, W Zheng - Drug discovery today, 2021 - Elsevier
Effective therapeutics to combat emerging viral infections are an unmet need. Historically,
treatments for chronic viral infections with single drugs have not been successful, as …
treatments for chronic viral infections with single drugs have not been successful, as …
Comparative analysis of molecular fingerprints in prediction of drug combination effects
B Zagidullin, Z Wang, Y Guan… - Briefings in …, 2021 - academic.oup.com
Application of machine and deep learning methods in drug discovery and cancer research
has gained a considerable amount of attention in the past years. As the field grows, it …
has gained a considerable amount of attention in the past years. As the field grows, it …