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Sustainable Inhalable Anti-infective Microparticle Manufacturing Through Life Cycle and Cost Analysis with Machine Learning Optimization

  • Yong Liu
  • , Xinyu Li
  • , Yuanyue Wang
  • , Xiya Sun
  • , Shaoyang Tong
  • , Suxu Zhao
  • , Lynda Thubelihle Kanye
  • , Qingzhen Zhang
  • , Ning Xue
  • , Kaiqi Shi*
  • , Justin Z. Lian*
  • , Fanran Meng*
  • , Bin Dong*
  • *Corresponding author for this work
  • China Pharmaceutical University
  • Dublin City University
  • Ltd.
  • University of Nottingham Ningbo China
  • University of Sheffield

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Pharmaceutical manufacturing must balance therapeutic efficacy with environmental and economic sustainability. Inhalable dry powder formulations are effective for treating respiratory infections, yet the sustainability of production methods remains poorly understood. This study evaluates three scalable microparticle fabrication techniques, spray drying (SD), spray freeze-drying (SFD), and supercritical CO2 antisolvent crystallization (SAS), for producing dual-drug inhalable formulations combining molnupiravir and tobramycin. In the machine learning section, random forest (RF) was used to investigate the impact of each condition in different methods on the drug particle size. Particle morphology and stability varied by method, with SFD producing highly porous particles and optimal aerosol performance. However, a gate-to-gate life cycle assessment (LCA) and life cycle costing (LCC) highlight trade-offs: SFD incurred higher burdens than SD across all nine environmental impact categories, while SD achieved the lowest overall environmental burden and the lowest cost (USD $0.4218 one batch). Sensitivity analysis shows that shifting to clean energy sources could reduce emissions by up to 52%. Through machine learning, LCA, and LCC, this work establishes a predictive framework for sustainability-oriented pharmaceutical manufacturing, advancing both granulation-stage eco-conscious drug production and strategies for reducing the footprint of emerging therapeutic technologies.

Original languageEnglish
Pages (from-to)1800-1813
Number of pages14
JournalACS Sustainable Resource Management
Volume3
Issue number6
DOIs
Publication statusPublished - 25 Jun 2026

Bibliographical note

Publisher Copyright:
© 2026 The Authors. Published by American Chemical Society

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • dry powder inhalation
  • granulation-stage sustainability
  • life cycle assessment
  • life cycle costing
  • machine learning
  • process optimization
  • sustainable pharmaceutical manufacturing

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