BACKGROUND: Sacubitril/valsartan, the first agent to be approved in a new class of drugs called angiotensin receptor neprilysin inhibitors (ARNIs), has been shown to reduce cardiovascular mortality and morbidity compared to enalapril in outpatient su...
European review for medical and pharmacological sciences
33275275
Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that reveal the SARS's cause. Artificial intelligence (AI) learning models can be created to predict drug s...
Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the experimental investigation of all drug combinations...
Despite numerous advances in cancer radiotherapy, tumor radioresistance remain one of the major challenges limiting treatment efficacy of radiotherapy. Conventional strategies to overcome radioresistance involve understanding the underpinning molecul...
Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica
34047141
Drug combination is a common clinical phenomenon. However, the scientific implementation of drug combination is li-mited by the weak rational evaluation that reflects its clinical characteristics. In order to break through the limitations of existing...
Proceedings of the National Academy of Sciences of the United States of America
34526388
Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been challenging. Combination therapies play an important role i...
Journal of the American Medical Informatics Association : JAMIA
34472609
OBJECTIVE: To develop an end-to-end deep learning framework based on a protein-protein interaction (PPI) network to make synergistic anticancer drug combination predictions.
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 becomes crucial to systematically evaluate the performance of novel computa...
Combination therapy has shown an obvious efficacy on complex diseases and can greatly reduce the development of drug resistance. However, even with high-throughput screens, experimental methods are insufficient to explore novel drug combinations. In ...
IEEE/ACM transactions on computational biology and bioinformatics
34086576
Drug combination therapies have been a viable strategy for the treatment of complex diseases such as cancer due to increased efficacy and reduced side effects. However, experimentally validating all possible combinations for synergistic interaction e...