Artificial intelligence and machine learning guided optimization in drug delivery

The optimisation of drug delivery systems is a complex, multidimensional challenge involving the interplay of formulation composition, process parameters, and biological performance. Traditional empirical and statistical approaches are increasingly limited by the high dimensionality, nonlinearity, and multi-objective nature of modern drug delivery problems. In this review, we explore how artificial intelligence (AI) and machine learning (ML) are transforming formulation science by enabling data-driven, adaptive, and efficient optimisation strategies. We provide a conceptual and practical overview of ML-guided optimisation workflows, including surrogate modelling, Bayesian optimisation, active learning, and…

• EA
  Engineering and Physical Sciences Research Council

  Award: EP/S023054/1