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A framework for making digital technology trustworthy in the highly regulated area of pharmaceutical manufacturing

Project: Funded research

Project Details

Description

The digital transformation in the pharmaceutical industry holds the potential to revolutionize drug development and manufacturing. Integrating digital tools such as artificial intelligence (AI)/machine learning (ML)-based digital twins, process control, and human-in-the-loop concepts can enhance efficiency, reduce costs, and improve product quality. The current supply chain issues, drug shortages, and the high ecological burden of pharmaceutical processes are pressing concerns.

However, implementing digital algorithms in the pharmaceutical industry faces notable challenges due to its conservative and highly regulated nature. To incorporate digital algorithms into established manufacturing processes, companies must revise documentation and demonstrate compliance with the strict good manufacturing practice (GMP) requirements set forth by regulatory authorities. This exploratory project offers a technical solution by proposing a framework for the regulatory evaluation of digital algorithms. In this project, we will identify critical regulatory aspects of digital technologies in the pharmaceutical industry. The technical framework will be developed in compliance with these regulations, utilizing the digital algorithms available at RCPE’s algorithm library.

The breakthrough innovations brought by this project are:
(1) We will use sophisticated scientific approaches to further develop digital algorithms within a technical framework that will ensure compliance with regulatory standards. For the first time, a workflow for the regulatory evaluation of algorithms, such as process control, will be created and transparently published.
(2) Companies currently hesitant to implement digital algorithms due to concerns of regulatory rejection will use this workflow as a blueprint.

Like this, we aim to facilitate the digitalization of GMP-conform industrial environments, thereby addressing ‘Careful and sustainable use of resources’, ‘Reliability,’ and ‘Dependency reduction’. Since the involved technologies improve product quality, reduce operational costs, and decrease resource consumption, the project will positively affect patient safety, supply-chain problems, and sustainability. Moreover, industrial digitalization will raise attractiveness and facilitate the re-establishment of European manufacturing sites.
AcronymPharmTechTrust
StatusFinished
Effective start/end date1/10/2430/09/25

Collaborative partners

Keywords

  • Digital Transformation
  • pharmaceutical industry
  • Artificial intelligence
  • Machine Learning
  • Pharma regulatory affairs
  • Industrial digitalization
  • Process- and quality control
  • Algorithm lifecycle management via data analytics
  • Regulatory compliance framework

Classification according to Österreichische Systematik der Wissenschaftszweige (ÖFOS 2012)

  • 102035 Data science

Applied Research Level (ARL)

  • ARL Level 4 - Experimental setup in laboratory-like conditions

Research focus/foci

  • Industrial Informatics

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