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AI and machine learning assisted development of greener formulations and pharmaceutical processes based on amorphous solid dispersions

Project description

Greener pharma solutions

The pharmaceutical industry faces challenges in reducing its environmental impact while maintaining efficiency and innovation. Supported by the Marie Skłodowska-Curie Actions programme, the i-GREENPHARM project addresses this pressing issue by uniting a diverse group of research and innovation organisations. By employing multidisciplinary technological approaches, the project aims to establish a proof-of-concept framework for greener pharmaceutical practices. Central to this initiative is the introduction of hot-melt extrusion as a novel production method, enhanced by AI and machine learning tools. The project will facilitate knowledge transfer around these core activities, supported by comprehensive environmental assessments, to foster sustainable practices within the pharmaceutical sector.

Objective

This proposal is bringing together R&I related staff by a complementary set of participating organisations that will use multidisciplinary technological approaches to provide a proof-of concept framework for designing and introducing greener practices in pharmaceuticals. Knowledge will be transferred around the core technical activity that will be the introduction of HME as a novel production method, based on AI-ML tools and supported by environmental assessment for greener pharmaceuticals.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-SE - HORIZON TMA MSCA Staff Exchanges

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Call for proposal

(opens in new window) HORIZON-MSCA-2023-SE-01

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Coordinator

ANFARM HELLAS AP NIKOLAOU PHARMACEUTICAL INDUSTRY SA
Net EU contribution
€ 110 400,00
Address
ACHAIAS 4 & TRIZINIAS STR
145 64 KIFISSIA
Greece
Region
Αττική Aττική Βόρειος Τομέας Αθηνών
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
No data

Participants (5)

Partners (4)