Integrating Everything: The Molecule Selection Toolkit, a System for Compound Prioritization in Drug Discovery

In recent years there have been numerous
papers on the topic of
multiattribute optimization in pharmaceutical discovery chemistry,
applied to compound prioritization. Many solutions proposed are static
in nature; fixed functions are proposed for general purpose use. As
needs change, these are modified and proposed as the latest enhancement.
Rather than producing one more set of static functions, this work
proposes a flexible approach to prioritizing compounds. Most published
approaches also lack a design component. This work describes a comprehensive
implementation that includes predictive modeling, multiattribute optimization,
and modern statistical design. This gives a complete package for effectively
prioritizing compounds for lead generation and lead optimization.
The approach described has been used at our company in various stages
of discovery since 2001. An adaptable system alleviates the need for
different static solutions, each of which inevitably must be updated
as the needs of a project change.