Revisiting nanomedicine design strategies for follow-on products: A model-informed approach to optimize performance

J Control Release. 2024 Dec:376:1251-1270. doi: 10.1016/j.jconrel.2024.11.004. Epub 2024 Nov 12.

Abstract

The field of nanomedicine is undergoing a seismic transformations with the rise of nanosimilars, reshaping the pharmaceutical landscape and expanding beyond traditional innovators and generic manufacturers. Nanodrugs are increasingly replacing conventional therapies, offering improved efficacy and safety, while the demand for follow-on products drives market diversification. However, the transition from preclinical to clinical stages presents challenges due to the complex biopharmaceutical behavior of nanodrugs. This review highlights the integration of Quality-by-Design (QbD), in vitro-in vivo correlations (IVIVCs), machine learning, and Model-Informed Drug Development (MIDD) as key strategies to address these complexities. Additionally, it discusses the role of high-throughput processes in the optimization of the nanodrug development pipelines. Covering generations of delivery systems from liposomes to RNA-loaded nanoparticles, this review underscores the evolving market dynamics driven by recent advances in nanomedicine.

Keywords: Biopharmaceutics; Dissolution specifications; Drug delivery; IVIVC; Nanomedicine; Physicochemical characterization; Quality-by-design; Regulations.

Publication types

  • Review

MeSH terms

  • Animals
  • Drug Delivery Systems
  • Drug Design
  • Drug Development / methods
  • Humans
  • Liposomes
  • Machine Learning
  • Nanomedicine* / methods
  • Nanoparticles / chemistry

Substances

  • Liposomes