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Pistoia Alliance Publishes Free Guide to Accelerate the Implementation of FAIR Principles in Clinical Data

Boston, 25 January 2023, The Pistoia Alliance, a global, not-for-profit alliance that advocates for greater collaboration in life sciences R&D today launched its freely accessible FAIR4Clin guide. The guide will help clinical regulators, biopharmaceutical and healthcare organizations to implement the FAIR principles (Findable, Accessible, Interoperable, Reusable) in clinical datasets. The diversity of data types, standards, and regulatory and privacy requirements, combined with the huge volume of clinical datasets, has presented a particular problem in life sciences R&D. The guide emphasizes the value of FAIR to the clinical space, including making data machine-readable to support AI, innovating in clinical trial design, and enabling the transfer of data between sponsors, CROs, and regulatory agencies. FAIR4Clin was co-authored by the Pistoia Alliance and leading experts in the field, including from AstraZeneca, Bayer, Roche, Genentech, Galapagos, The Hyve, Elixir, The University of Manchester and Oxford University.
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White Papers

Medpace Reference Laboratories establishes state of the art Flow Cytometry techniques for flexible approaches to clinical trials across multiple therapeutic areas.

Medpace

Cytometry is the process of measuring the properties of individual cells. These properties may include gene or protein expression, chemical properties, deoxyribonucleic acid (DNA) content, and various cellular functions. The earliest methods of cytometry relied upon light microscopy for the classification and observation of cells and cellular components. Microscopy permitted direct visual observation of cells for the first time, leading to the classification of cells by morphology and insight into cellular functions. However, the time required for microscopic analysis constrains the number of samples or number of cells in each sample that can be examined. Therefore, the utility of microscopy for analysis of rare cells or in situations where sample throughput is a priority is limited. Flow cytometry was developed largely to improve upon these limitations.
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