Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases

Area of Science:

• Biomedical research
• Computational biology
• Drug discovery

Background:

• Artificial intelligence (AI) applications are rapidly expanding with increasing digital data.
• Drug development for rare diseases faces significant hurdles due to data scarcity and high costs.

Purpose of the Study:

• To review the application of AI in drug development, focusing on rare diseases.
• To highlight AI's achievements and challenges in this specialized field.

Main Methods:

• Integration of heterogeneous datasets and knowledge bases using AI.
• Leveraging expert biological understanding to guide AI approaches.
• Analysis of AI's role in overcoming data paucity in rare disease research.

Main Results:

• AI enables novel approaches for rare disease drug development through large-scale data integration.
• AI facilitates the use of complex biological data that was previously inaccessible.
• Challenges remain for routine AI adoption in the conservative pharmaceutical industry.

Conclusions:

• AI is a powerful supportive tool for drug discovery and development, particularly for rare diseases.
• AI can assist but not replace human expertise in pharmaceutical research and development.
• Addressing obstacles is crucial for the routine implementation of AI in drug development.