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Related papers: Generating Drug Repurposing Hypotheses through the…

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To date, there are no effective treatments for most neurodegenerative diseases. Knowledge graphs can provide comprehensive and semantic representation for heterogeneous data, and have been successfully leveraged in many biomedical…

Artificial Intelligence · Computer Science 2022-11-30 Yi Nian , Xinyue Hu , Rui Zhang , Jingna Feng , Jingcheng Du , Fang Li , Yong Chen , Cui Tao

Drug repurposing has historically been an economically infeasible process for identifying novel uses for abandoned drugs. Modern machine learning has enabled the identification of complex biochemical intricacies in candidate drugs; however,…

Machine Learning · Computer Science 2025-09-16 Luke Delzer , Robert Kroleski , Ali K. AlShami , Jugal Kalita

Repurposing existing drugs to treat new diseases is a cost-effective alternative to de novo drug development, but there are millions of potential drug-disease combinations to be considered with only a small fraction being viable. In silico…

Quantitative Methods · Quantitative Biology 2025-10-24 Austin Polanco , M. E. J. Newman

A pharmacological effect of a drug on cells, organs and systems refers to the specific biochemical interaction produced by a drug substance, which is called its mechanism of action. Drug repositioning (or drug repurposing) is a fundamental…

Machine Learning · Computer Science 2020-05-19 Dehua Chen , Amir Jalilifard , Adriano Veloso , Nivio Ziviani

Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to…

Machine Learning · Computer Science 2024-05-21 Ali Gharizadeh , Karim Abbasi , Amin Ghareyazi , Mohammad R. K. Mofrad , Hamid R. Rabiee

Drug repositioning-a promising strategy for discovering new therapeutic uses for existing drugs-has been increasingly explored in the computational science literature using biomedical databases. However, the technological potential of drug…

Artificial Intelligence · Computer Science 2024-07-25 Yongseung Jegal , Jaewoong Choi , Jiho Lee , Ki-Su Park , Seyoung Lee , Janghyeok Yoon

The 2019 novel coronavirus (SARS-CoV-2) pandemic has resulted in more than a million deaths, high morbidities, and economic distress worldwide. There is an urgent need to identify medications that would treat and prevent novel diseases like…

Machine Learning · Computer Science 2020-12-04 Siddhant Doshi , Sundeep Prabhakar Chepuri

Drug repurposing is more relevant than ever due to drug development's rising costs and the need to respond to emerging diseases quickly. Knowledge graph embedding enables drug repurposing using heterogeneous data sources combined with…

The extraction of biomedical data has significant academic and practical value in contemporary biomedical sciences. In recent years, drug repositioning, a cost-effective strategy for drug development by discovering new indications for…

Machine Learning · Computer Science 2025-01-20 Enqiang Zhu , Xiang Li , Chanjuan Liu , Nikhil R. Pal

Drug repositioning (DR) refers to identification of novel indications for the approved drugs. The requirement of huge investment of time as well as money and risk of failure in clinical trials have led to surge in interest in drug…

Computation and Language · Computer Science 2017-05-23 Sahil Manchanda , Ashish Anand

The contributions of model complexity, data volume, and feature modalities to knowledge graph-based drug repurposing remain poorly quantified under rigorous temporal validation. We constructed a pharmacology knowledge graph from ChEMBL 36…

Artificial Intelligence · Computer Science 2026-03-03 Youssef Abo-Dahab , Ruby Hernandez , Ismael Caleb Arechiga Duran

Recently, drug repurposing has emerged as an effective and resource-efficient paradigm for AD drug discovery. Among various methods for drug repurposing, network-based methods have shown promising results as they are capable of leveraging…

Quantitative Methods · Quantitative Biology 2023-10-30 Shunian Xiang , Patrick J. Lawrence , Bo Peng , ChienWei Chiang , Dokyoon Kim , Li Shen , Xia Ning

In recent decades, traditional drug research and development have been facing challenges such as high cost, long timelines, and high risks. To address these issues, many computational approaches have been suggested for predicting the…

Quantitative Methods · Quantitative Biology 2023-09-13 Chunyan Ao , Zhichao Xiao , Lixin Guan , Liang Yu

Drug repurposing is an emerging approach for drug discovery involving the reassignment of existing drugs for novel purposes. An alternative to the traditional de novo process of drug development, repurposed drugs are faster, cheaper, and…

Biomolecules · Quantitative Biology 2023-09-26 Srilekha Mamidala

The drug discovery and development process is a long and expensive one, costing over 1 billion USD on average per drug and taking 10-15 years. To reduce the high levels of attrition throughout the process, there has been a growing interest…

Quantitative Methods · Quantitative Biology 2022-08-22 Cheng Ye , Rowan Swiers , Stephen Bonner , Ian Barrett

Drug repurposing has attracted increasing attention from both the pharmaceutical industry and the research community. Many existing computational drug repurposing methods rely on preclinical data (e.g., chemical structures, drug targets),…

Quantitative Methods · Quantitative Biology 2020-07-28 Qianlong Wen , Ruoqi Liu , Ping Zhang

Drug repurposing is an effective strategy to identify new uses for existing drugs, providing the quickest possible transition from bench to bedside. Existing methods for drug repurposing that mainly focus on pre-clinical information may…

Applications · Statistics 2021-04-14 Ruoqi Liu , Lai Wei , Ping Zhang

Drug repurposing (or repositioning) is the process of finding new therapeutic uses for drugs already approved by drug regulatory authorities (e.g., the Food and Drug Administration (FDA) and Therapeutic Goods Administration (TGA)) for other…

Artificial Intelligence · Computer Science 2023-06-27 Chaarvi Bansal , Rohitash Chandra , Vinti Agarwal , P. R. Deepa

Combination therapy has shown to improve therapeutic efficacy while reducing side effects. Importantly, it has become an indispensable strategy to overcome resistance in antibiotics, anti-microbials, and anti-cancer drugs. Facing enormous…

Molecular Networks · Quantitative Biology 2020-04-24 Mostafa Karimi , Arman Hasanzadeh , Yang shen

Adverse drug reactions (ADRs) are a major barrier to safe and effective pharmacotherapy and increasingly reflect higher order interactions between drugs, genetic background, and clinical phenotypes. Existing graph based approaches usually…

Quantitative Methods · Quantitative Biology 2025-12-02 Ze Cai , Haotian Tang , Shuai Gao , Binbin Zhou , Junhan Zhao , Jun Wen
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