Digital Technologies


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Digital Technology Roadmap

This paper outlines the foundational element that chart the course for pharmaceutical manufacturers who decide to take this journey and provides a vision of what that destination could look like in 10 years’ time. It outlines the current state of the industry, key challenges and barriers to adoption, and hints at the value that taking this journey will bring to patients, organizations and industry. This paper (which forms Part 1 of the Digital Technology Roadmap) looks at the problem statement and the work that has gone before.

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The benefits of progressively more sophisticated lab instrument integration in the quality control labs

QC labs play a key role across biopharmaceutical organizations to ensure product quality and patient safety. However, they have yet to achieve full digital maturity. Poor digitalization and integration have led to many non-optimal solutions for labs, such as workarounds and tailored solutions that are too expensive to upgrade. Often teams cannot take advantage of the latest innovations. With the help of this document, advocates for change can persuade other stakeholders to raise their game by showing the opportunity for significant benefits. The origins of this analysis in cross-industry collaboration and alignment represent a weight of common intent that should not be ignored.

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MES of the future manifesto

The purpose of the MES of the future manifesto is a call to action from the biomanufacturing industry to vendors of MES solutions. The manifesto articulates: the gap between the current generation of MES solutions and the needs of the biomanufacturing industry and a realistic and achievable vision for the MES of the future that will meet the needs of the biomanufacturing plants of the future. It is intended to stimulate collaboration between biomanufacturers and vendors of MES solutions that will outline roadmaps for future development.

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Regulatory: Feedback to DMKA questions to critical GXP augmented intelligence

BioPhorum response to work being conducted by The Danish Medicines Agency (DKMA) to define criteria for the application of artificial intelligence (AI) and machine learning (ML) across GxP-regulated areas. The questions  asked by the agency considered the requirements and quality of data used to build, test and validate an algorithm, and how it would respond to biases and deviations in results.

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