Earlier this year, we announced that OracleBio is now conducting quantitative image analysis on clinical trial samples in accordance with Good Clinical Practices (GCP). Having recognised these standards, it is important to ensure that this high-level quality is...
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Quantitative Image Analysis and GCP: Q&A Blog
OracleBio's recent GCP implementation was driven by Clinical Operations Manager, Alison Bigley. In this blog, Alison discusses why GCP is important, the current state of play with regulatory standards in image analysis and more...What is Good Clinical Practice and why...
OracleBio’s Path to GCP Image Analysis – Digital Pathology Place Podcast
OracleBio's Chief Scientific Officer, Lorcan Sherry, recently joined Aleksandra Zuraw on the Digital Pathology Place podcast. During the podcast, Aleks and Lorcan have a conversation about the history of OracleBio and the company's journey to GCP Image Analysis....
Image Analysis Quality Control Part 3: Staining QC
Image Quality Control (QC) is an essential first step in any image analysis study. At OracleBio, we QC check every image before analysis and only proceed with images that meet certain criteria, taking into consideration 1) Image Scan 2) Tissue Section and 3) Staining....
Image Analysis Quality Control Part 2: Tissue Section QC
Getting the image quality right before embarking on advanced image analysis may be an obvious statement to make. However, there are multiple ways to assess image quality and this speaks to the need for robust quality control (QC) processes throughout an image...
Image Analysis Quality Control Part 1: Image Scan QC
Good quality image analysis requires good quality images. Therefore, before beginning quantitative analysis it is essential to first conduct a Quality Control (QC) review of all images to assess suitability for analysis and to only proceed with images that meet...
6 Ways to Improve the Quality of Quantitative Histopathology Data
The production of robust tissue-based quantitative histopathology data is completely dependent on high quality sample preparation and staining. Failure to ensure that samples are of a high quality can hinder subsequent image analysis processes, negatively impact on...
Quality Counts: Implementing Quality Standards as part of Image Analysis in Clinical R&D
Delivering robust and meaningful data in support of an ever-increasing demand on tissue-based biomarker evaluations is critical to improving decision making in clinical R&D. To realise these requirements, it is vitally important to implement quality standards...