Speaker
Description
The work discussed here is in progress nevertheless it provides insights into good
practices in drug design, discovery, and development (4D). The final goal is to make the
4D flexible and scalable and reduce the total time for bringing a new chemical entity to
the market a few times. The focus of the presentation is on bio-chemistry data, its
discretization, augmentation, and saturation (DAS). The digital twin approach has been
employed for domain digitalization. The idea behind is to use GOAL oriented approach
to represent the objectives that may vary or change over time in order to achieve the
final goal in 4D. It is a belief of the team behind this work that 4D needs to handle
adequately the dynamically changing environment and any new piece of knowledge
need to be explored. The emphasis presented here in the 4D process is on the AI
pipelines and processes that allow prediction of chemical properties and how this
information is used to generate virtual libraries that facilitate the establishment of drug
candidates and reduce the choice of stem molecules from a few thousand or millions to
a hand full. The software at the end is presented as a SaaS and a PaaS is used for
implementation.
