What are the challenges and opportunities in developing drug interaction search tools?
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Developing drug interaction search tools faces several challenges and opportunities. One challenge is the lack of gold standard positive and negative drug pairs, which hampers the assessment of results from big data studies . Another challenge is the need to explore the rich and complex relationships between drugs and proteins, which can be addressed through graph machine learning . Additionally, explicitly modeling and learning local interactions between drugs and targets is crucial for better prediction and interpretation . Furthermore, the translation of in vitro data to clinically significant effects is challenging due to the variability in assay designs and the lack of sensitive index substrates and specific inhibitors for individual transporters . Despite these challenges, integrating clinical data mining with mechanistic understanding of drug action can promote confidence in drug-drug interaction predictions . Overall, the development of drug interaction search tools presents opportunities for advancements in prediction accuracy, generalization to novel drug-target pairs, and interpretable insights from prediction results .
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| Papers (5) | Insight |
|---|---|
37 Citations | The provided paper does not specifically mention drug interaction search tools. The paper is about opportunities and challenges in search interaction in general. |
4 Citations | The provided paper discusses challenges in translating in vitro data to obtain a quantitative assessment of drug-drug interaction (DDI) risk in the clinic. It also highlights the need for sensitive index substrates and specific inhibitors for individual transporters. However, it does not specifically address the development of drug interaction search tools. |
03 Aug 2022 | The provided paper does not discuss the challenges and opportunities in developing drug interaction search tools. |
6 Citations | The challenges in developing drug interaction search tools include exploring the rich and complex relationships between drugs and proteins, as well as calibrating the intermediate node in the heterogeneous graph. The paper proposes a framework called DSG-DTI to address these challenges. |
| The paper discusses the challenges of interpreting results from big data studies and the lack of gold standard positive and negative drug pairs for drug interaction search tools. |
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