<br/>Throughout the world mankind is facing an ageing and growing population that requires more effective and safer medicines in all therapeutic areas. Despite significant advances in our understanding of the biological basis of diseases, pharmaceutical R&D is struggling to sustain the level of productivity and efficiency it reached in the second half of the 20th century. High rates of failure and the increasing cost of drug discovery as well as extended research and development timelines hinder the development of medicines. Due to these challenges there has been an increasing need for substantial innovations in the pharmaceutical sector.<br/>It has been shown that if the selection of the synthetic targets in lead optimization cycles is supported by QSAR or deep learning methods, the number of compounds synthesized as well as the cycle time for each iteration can be significantly reduced. We have developed a rule-based artificial intelligence technology that can produce a large number of novel and synthetically-enabled lead analogues and scaffold hopping designs around lead structures. Since its introduction, the cloud-based SynSpace software has been found by multiple organizations to generate a larger number of relevant novel ideas around leads than medicinal chemist teams can do. Thus, SynSpace is a valuable addition to the medicinal chemistry toolbox.<br/>We have also been developing automated lead analysis tools and a synthesis-based library enumerator that - in conjunction with SynSpace - can automatically carry out scaffold hopping and lead analogue idea generation and thereby offer large sets of novel and project specific lead-like structures to advanced AI platforms for selection.<br/>These platforms have the biggest impact on a number of key parameters in drug discovery: cycle time, number of discovery cycles, the number of compounds to be synthesized and coverage of IP space. Improvements in these factors can be converted into higher success rates and major resource savings towards a more economical and productive candidate development phase.

SynSpace: A user-friendly web- and cloud-based design platform to expand synthetically-enabled scaffold and lead analogue space for medicinal chemistry and AI-assisted drug discovery

2019 Spring National Meeting

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