Normalized claim
Cost: 44-67%
Expected cost reductions of 44%-67% in drug discovery and development.
EY guides pharmaceutical companies through adopting generative AI (GenAI) to accelerate and automate early-stage drug discovery processes. GenAI enables significant breakthroughs in molecule creation, compound screening, and toxicity prediction, previously requiring extensive time and costs. EY collaborates with life sciences industry leaders, providing strategy and change management for successful GenAI implementation. The solution leverages deep learning algorithms for virtual screening, target identification, and optimal resource allocation. Predictions point toward cost savings from 44% to 67% and time reductions up to 50% for critical research phases, as GenAI adoption accelerates. The methodology streamlines clinical trial design and data analysis, improves regulatory submission, and automates documentation and compliance. EY works with both large and small biopharma companies to extend the benefits industry-wide, including for organizations lacking in-house AI capabilities. The approach helps CDMOs and CROs differentiate using advanced AI for outsourced drug research steps. Results reported by EY clients and survey respondents describe speed-to-market and cost reduction as primary impacts. The article describes a transformation in research and development operating models for faster patient benefit and broader treatment diversity.
Reported outcomes
Time: Up to 50% lower
Time & speed
No explicit deployment-stage evidence found.
Primary read
Showing 3 of 3
The same organization appears in newer AI deployment evidence.
Measures whether this deployment's public evidence persists — not whether the system is still in production.
AI-generated summary. Verify important details with the linked sources before relying on this case.
Was this useful?
Community
No published comments yet.