Arora and Moore in The Scientist:
The path to bringing a new drug to market is increasingly complex and costly, with development costs now exceeding $2 billion and timelines approaching a decade.1,2 The stakes have never been higher—demanding new models, new technologies, and new thinking to reduce risk and accelerate breakthroughs. Up to 90 percent of compounds entering clinical trials never reach the market, often due to unforeseen toxicity or lack of efficacy in heterogenous patient populations. This high failure rate has accelerated a shift toward more targeted development strategies.
Companion diagnostics are central to this shift, enabling more precise trials, faster development cycles, and better health outcomes for some of the world’s sickest patients. Artificial intelligence (AI) is reshaping the landscape—not only for therapeutics but also for precision diagnostics that guide patient selection and treatment decisions. Digital pathology and AI now sit at the heart of this transformation, offering new ways to extract quantitative biological signals, harmonize global lab variability, and support earlier, sharper decision‑making in clinical trials.3
More here.
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