A new horizon in synthetic organic chemistry
With the advance of AI and machine learning, high-quality and transparent data now has the power to accelerate the development of predictive models to drive pharmaceutical and chemical innovation. But AI isn’t going to replace human efforts in R&D so much as amplify them.
- How deep learning has demonstrated superior performance to other machine learning algorithms
- How the availability of software tools for building machine learning models has been a significant factor in driving the rapid adoption of machine learning in drug discovery
- What kind of data is needed in order for AI to be effective
In this white paper, discover:
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