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Accelerating Drug Design
Generate Optimal Lead Candidates Faster
The development time and costs for new therapeutics are enormous (average 12 years and $2.6 B). Drug Discovery requires synthesis of thousands of molecules and up to five years to produce one lead candidate and only 10% of compounds in Phase 1 clinical trials receive approval. Projects are delayed during the pandemic due to reduced experimental capacity. Combining in silico modeling and simulation and machine learning can lead to savings in experimental costs of up to 50% and reduce the overall R&D cycle time, while still improving overall drug performance.
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