Drug discovery and development remains one of the most challenging and resource-intensive processes in modern medicine. With development timelines spanning 10-15 years and costs exceeding $1-3 billion per approved drug1, the need for more efficient target identification methods has never been more critical. Traditional approaches, heavily reliant on expensive in vitro and in vivo experiments, face substantial failure rates, with about 90% of drug candidates failing during clinical trials.1 An improved capability for identifying likely efficacious and nonefficacious novel targets could increase the odds of clinical trial success, bringing successful treatments to patients more quickly and effectively.
Investing in clinical trials is a high-stakes endeavor. While the potential for transformative medical breakthroughs and substantial financial rewards exists, the reality is that a significant portion of trials fail. These failures result in devastating financial losses, eroding investor confidence and delaying the development of life-saving therapies for patients world-wide.
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