The current R&D model is broken
the problem
It takes 12-15 years to bring a new drug to market.
On average, it costs $2.5 billion to develop a new drug.
90% of drug candidates that enter Phase 1 clinical trials fail to reach regulatory approval.
Less than 70 new drugs enter the market each year.
the Opportunity
Since the 17th century, the scientific method has remained largely unchanged, relying on slow, human-intensive, cycles of observation, hypothesis, experimentation, and analysis.
AI offers an unprecedented opportunity to compress these cycles, accelerate the time from observation to discovery, and reduce the need for experimentation.
This paradigm shift, AI for Scientific Discovery, will transform discovery across all industries, and especially the pharmaceutical industry, where on average, it takes 12 to 15 years and costs over $2 billion to develop a new drug.
To realize the promise of AI for Scientific Discovery for pharmaceutical R&D, a new end-to-end drug discovery and development process must be reimagined from the ground up using AI, and it must overcome historically fragmented data, create new types of data at scale, and put massive parallel data, AI, and lab automation in the same, iterative loop.