Fiona Mitchell
We are witnessing a fundamental shift in how we understand and treat disease. The convergence of computational methods and biological research is creating unprecedented opportunities to intervene in conditions that were previously intractable.
For decades, drug discovery has been an expensive, time-consuming process with high failure rates. The traditional approach—identifying a target, screening compounds, optimizing leads, and testing in clinical trials—takes an average of 10-15 years and costs billions of dollars. Most candidates fail.
A New Paradigm
Machine learning and artificial intelligence are fundamentally changing this equation. By analyzing vast datasets of biological information—genomic sequences, protein structures, clinical outcomes, and more—these tools can identify patterns and relationships that human researchers might miss.
"The question is no longer whether AI will transform drug discovery, but how quickly and how completely."
The most exciting developments are happening at the intersection of multiple disciplines. Companies that combine deep biological expertise with sophisticated computational methods are making breakthroughs that neither field could achieve alone.
Implications for Investment
For investors, this convergence creates both opportunities and challenges. The potential returns from successful AI-driven drug discovery are enormous, but evaluating these companies requires expertise in both technology and biology.
At CGV, we look for founders who can bridge these worlds—scientists who understand computation, technologists who understand biology. These rare individuals are building the companies that will define the next era of healthcare innovation.