Galenic preparations are patient-centered medicines prepared by pharmacists or veterinarians, which allow personalizing dosages, overcoming allergy problems, reducing costs, and dealing with rare diseases. However, the current manual production process of galenic preparations poses several challenges to human workers. This paper proposes the use of collaborative robots to help pharmacists carry out the most tiresome, precise, error-prone, and time-consuming tasks. In particular, an end-user development (EUD) environment called PRAISE (pharmaceutical robotic and AI system for end users) has been designed to support pharmacists in programming the tasks to be performed by a collaborative robot. The EUD environment integrates artificial intelligence (AI) features based on large language models but ensures that end users always have complete control over the generated output, that is, a robot program. The paper focuses on the application of a human-centered methodology adopted to design PRAISE by involving representative end users (experts in the pharmaceutical sector) from system ideation to its evaluation. Design implications related to AI-enabled EUD for collaborative robots are the main findings of the paper.

Exploring the Adoption of Collaborative Robots for the Preparation of Galenic Formulations

Gargioni L.;Fogli D.;Baroni P.
2025-01-01

Abstract

Galenic preparations are patient-centered medicines prepared by pharmacists or veterinarians, which allow personalizing dosages, overcoming allergy problems, reducing costs, and dealing with rare diseases. However, the current manual production process of galenic preparations poses several challenges to human workers. This paper proposes the use of collaborative robots to help pharmacists carry out the most tiresome, precise, error-prone, and time-consuming tasks. In particular, an end-user development (EUD) environment called PRAISE (pharmaceutical robotic and AI system for end users) has been designed to support pharmacists in programming the tasks to be performed by a collaborative robot. The EUD environment integrates artificial intelligence (AI) features based on large language models but ensures that end users always have complete control over the generated output, that is, a robot program. The paper focuses on the application of a human-centered methodology adopted to design PRAISE by involving representative end users (experts in the pharmaceutical sector) from system ideation to its evaluation. Design implications related to AI-enabled EUD for collaborative robots are the main findings of the paper.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/632910
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