September 21, 2025Bilad Alrafidain Journal for Engineering Science and TechnologyOpen Access

Advanced Deep Learning for Accelerated Drug Discovery: Approaches, Challenges, and Future Expectations

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Deep learning shows promise in improving drug discovery efficiency and accuracy through various techniques.
Key innovations like reinforcement learning and explainable AI enhance model predictions and data interpretability.
Implementing multi-modal datasets has proven essential for capturing complex molecular relationships in drug discovery.
Despite advancements, challenges in data quality, multi-drug modeling, and toxicity assessment still require innovative solutions.

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Implication

This analysis reveals enhanced drug-target interactions and model interpretability using deep learning, indicating a transformative approach to drug discovery.

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Abdulkareem et al. (2025) studied this question.

synapsesocial.com/papers/68d43c8e713b0b5dfea7c878 https://doi.org/10.56990/bajest/2025.040207

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Implication

This analysis reveals enhanced drug-target interactions and model interpretability using deep learning, indicating a transformative approach to drug discovery.

Advanced Deep Learning for Accelerated Drug Discovery: Approaches, Challenges, and Future Expectations

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Discussion

Implication

Cite This Study

Advanced Deep Learning for Accelerated Drug Discovery: Approaches, Challenges, and Future Expectations

Key Points

Discussion

Implication

Cite This Study