AIMC Topic: Drug Combinations
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DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations.
Briefings in bioinformatics
Nov 22, 2024
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex i...
Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19 Patients Receiving Antivirals.
Influenza and other respiratory viruses
Sep 1, 2024
INTRODUCTION: There is still a lack of clinical evidence comprehensively evaluating the effectiveness of antiviral treatments for COVID-19 hospitalized patients.
COVID-19
Retrospective Studies
Tomography, X-Ray Computed
Humans
Artificial Intelligence
Pandemics
Pneumonia, Viral
Ritonavir
COVID-19 Drug Treatment
Middle Aged
Betacoronavirus
Lung
Antiviral Agents
Aged
Treatment Outcome
Female
Adult
Drug Combinations
SARS-CoV-2
Male
Coronavirus Infections
Hospitalization
[A Case of Gastric Cancer with Pulmonary Carcinomatous Lymphangitis and Disseminated Carcinomatosis of the Bone Marrow Responding to S-1 plus Cisplatin Chemotherapy].
Gan to kagaku ryoho. Cancer & chemotherapy
Dec 1, 2023
A 63-year-old man was admitted to a hospital owing to shortness of breath. He was diagnosed as having gastric cancer with pulmonary carcinomatous lymphangitis(PCL)and disseminated carcinomatosis of the bone marrow(DCBM). Regarding tumor markers, carc...
Efficacy and Tolerability of Tenofovir/Lamivudine/Dolutegravir among Antiretroviral Therapy Naive Human Immunodeficiency Virus Infected Patients of a Tertiary Care Center in Eastern India.
The Journal of the Association of Physicians of India
Sep 1, 2023
BACKGROUND: Although many drug regimens have been used in the treatment of human immunodeficiency virus (HIV) infection, the National AIDS Control Organization (NACO) of India recommends the use of a fixed-dose combination of tenofovir/lamivudine/dol...
DeepTraSynergy: drug combinations using multimodal deep learning with transformers.
Bioinformatics (Oxford, England)
Aug 1, 2023
MOTIVATION: Screening bioactive compounds in cancer cell lines receive more attention. Multidisciplinary drugs or drug combinations have a more effective role in treatments and selectively inhibit the growth of cancer cells.
MARSY: a multitask deep-learning framework for prediction of drug combination synergy scores.
Bioinformatics (Oxford, England)
Apr 3, 2023
MOTIVATION: Combination therapies have emerged as a treatment strategy for cancers to reduce the probability of drug resistance and to improve outcomes. Large databases curating the results of many drug screening studies on preclinical cancer cell li...
CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy.
Briefings in bioinformatics
Jan 19, 2023
Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug sy...
Predicting cell line-specific synergistic drug combinations through a relational graph convolutional network with attention mechanism.
Briefings in bioinformatics
Nov 19, 2022
Identifying synergistic drug combinations (SDCs) is a great challenge due to the combinatorial complexity and the fact that SDC is cell line specific. The existing computational methods either did not consider the cell line specificity of SDC, or did...
DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations.
Briefings in bioinformatics
Sep 20, 2022
Drug combination therapies are superior to monotherapy for cancer treatment in many ways. Identifying novel drug combinations by screening is challenging for the wet-lab experiments due to the time-consuming process of the enormous search space of po...
Multidrug representation learning based on pretraining model and molecular graph for drug interaction and combination prediction.
Bioinformatics (Oxford, England)
Sep 15, 2022
MOTIVATION: Approaches for the diagnosis and treatment of diseases often adopt the multidrug therapy method because it can increase the efficacy or reduce the toxic side effects of drugs. Using different drugs simultaneously may trigger unexpected ph...
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