Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.

Centre Blaise Pascal de Simulation et de Modélisation Numérique Ecole Normale Supérieure de Lyon 46 Allée d'Italie 69364 Lyon France

IT4Innovations VŠB Technical University of Ostrava 17 listopadu 2172 15 708 00 Ostrava Poruba Czech Republic

Laboratoire de Biologie et Modélisation de la Cellule CNRS UMR 5239 Inserm U1293 Université Claude Bernard Lyon 1 Ecole Normale Supérieure de Lyon 46 Allée d'Italie 69364 Lyon France

mRNA Center of Excellence Sanofi 69280 Marcy l'Étoile France

mRNA Center of Excellence Sanofi Waltham Massachusetts 02451 United States

Regional Center of Advanced Technologies and Materials Czech Advanced Technology and Research Institute Palacký University Olomouc Šlechtitelů 27 779 00 Olomouc Czech Republic

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