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This book has been an effort to cover the many various aspects of artificial intelligence as it is applied to drug discovery. While many new methods and approaches have been introduced, and their impact or potential impact in drug discovery, has been presented, it is also important to reflect on the various advances that have been made in all fields as a whole to optimising drug discovery and thereby improving success rates in this endeavour. A grand challenge of artificial intelligence in drug discovery is to anticipate the potential benefits and adverse effects prior to testing these potential drugs experimentally, but realising that judicious use of experimentation is essential to enable these advances. We are experiencing a step-change in the ability of algorithms to apply available data in helping design the next generation of therapeutics. It is unlikely that any one innovation will be the dominant method going forward, but it is likely however that novel combinations of both new and old methods, with appropriate enhancements will lead to significant advances in these methods in drug discovery efforts.

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