Revolutionizing drug formulation development: The increasing impact of machine learning

[Display omitted] Over the past few years, the adoption of machine learning (ML) techniques has rapidly expanded across many fields of research including formulation science. At the same time, the use of lipid nanoparticles to enable the successful delivery of mRNA vaccines in the recent COVID-19 pa...

Full description

Saved in:
Bibliographic Details
Published in:Advanced drug delivery reviews 2023-11, Vol.202, p.115108-115108, Article 115108
Main Authors: Bao, Zeqing, Bufton, Jack, Hickman, Riley J., Aspuru-Guzik, Alán, Bannigan, Pauric, Allen, Christine
Format: Article
Language:English
Subjects:
Active learning
Drug Compounding
Drug delivery
Drug development
Humans
Machine Learning
Pandemics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:[Display omitted] Over the past few years, the adoption of machine learning (ML) techniques has rapidly expanded across many fields of research including formulation science. At the same time, the use of lipid nanoparticles to enable the successful delivery of mRNA vaccines in the recent COVID-19 pandemic demonstrated the impact of formulation science. Yet, the design of advanced pharmaceutical formulations is non-trivial and primarily relies on costly and time-consuming wet-lab experimentation. In 2021, our group published a review article focused on the use of ML as a means to accelerate drug formulation development. Since then, the field has witnessed significant growth and progress, reflected by an increasing number of studies published in this area. This updated review summarizes the current state of ML directed drug formulation development, introduces advanced ML techniques that have been implemented in formulation design and shares the progress on making self-driving laboratories a reality. Furthermore, this review highlights several future applications of ML yet to be fully exploited to advance drug formulation research and development.
ISSN:0169-409X
1872-8294
DOI:10.1016/j.addr.2023.115108