Quantum computing's potential for drug discovery: Early stage industry dynamics

Area of Science:

• Drug discovery and development
• Quantum computing applications
• Computational chemistry

Background:

• Classical supercomputers face limitations in complex drug discovery tasks.
• Quantum computing (QC) offers potential for revolutionizing pharmaceutical research.
• The practical realization and timeline for QC in drug discovery remain uncertain.

Purpose of the Study:

• To analyze quantum computing activities within the drug discovery and development sector.
• To identify key stakeholders and their focus areas in QC for pharmaceuticals.
• To assess the collaborative landscape in the quantum computing ecosystem for drug discovery.

Main Methods:

• Systematic review of QC-related activities.
• Analysis of publications, patents, and industry reports.
• Stakeholder mapping across pharmaceutical companies, startups, and academia.

Main Results:

• Quantum computing has gained significant interest across pharmaceutical companies, startups, and academic institutions.
• Current research and development efforts are concentrated on applications such as lead optimization and compound screening.
• A clear need for enhanced collaboration exists within the dynamic quantum computing ecosystem.

Conclusions:

• Quantum computing is increasingly relevant to drug discovery and development.
• Lead optimization and compound screening are primary areas of QC application in the pharmaceutical industry.
• Collaboration is essential to navigate and advance the rapidly evolving field of quantum computing for drug discovery.