Artificial intelligence in multi-objective drug design

Curr Opin Struct Biol. 2023 Apr:79:102537. doi: 10.1016/ Epub 2023 Feb 10.


The factors determining a drug's success are manifold, making de novo drug design an inherently multi-objective optimisation (MOO) problem. With the advent of machine learning and optimisation methods, the field of multi-objective compound design has seen a rapid increase in developments and applications. Population-based metaheuris-tics and deep reinforcement learning are the most commonly used artificial intelligence methods in the field, but recently conditional learning methods are gaining popularity. The former approaches are coupled with a MOO strat-egy which is most commonly an aggregation function, but Pareto-based strategies are widespread too. Besides these and conditional learning, various innovative approaches to tackle MOO in drug design have been proposed. Here we provide a brief overview of the field and the latest innovations.

Keywords: Compound optimisation; Multi-objective optimisation; Pareto dominance; de novo drug design.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence*
  • Drug Design*
  • Machine Learning