What if you could increase trial success rates 2.5x while cutting costs in half? See what in silico clinical development could really deliver.
Clinical development is one of the most expensive and uncertain parts of drug innovation. In silico methods are changing the equation.
This white paper quantifies how AI-driven simulation, digital twins and model-informed approaches can reshape the economics of clinical trials—not just how they work.
Based on real case studies, validated sources and modeled scenarios, ZS analysis reveals that in silico clinical development has the potential to:
- Increase probability of success by up to 2.5x
- Reduce development costs by up to 60%
- Shorten clinical timelines by ~40%
Beyond the technology, the paper explores how these gains are achieved across the development life cycle and what it will take to apply them in practice.
For R&D and clinical leaders, this is a shift from high-risk, intuition-led trial design to a more predictable, simulation-driven model for delivering the next generation of patient therapies.
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