⚡ Article Synopsis: In this article, OracleBio's Marketing Manager, Mark Laurie, wraps up some of this year’s highlights and gives you a peek at what’s to come in 2023!As 2022 draws to a close, it’s a good time to reflect on the year and appreciate how much we’ve...
.
6 Ways to Improve the Quality of Quantitative Histopathology Data in 2022
⚡ Article Synopsis: In this article, OracleBio's Deputy Clinical Operations Manager, Nicole Couper, outlines 6 of the most prevalent issues encountered in Histopathology that hinder or negatively impact data quality.The generation of high-quality and robust...
Improving multiplex IF image analysis workflows: Does the perfect solution to autofluorescence exist?
⚡ Article Synopsis: In this article, OracleBio Image Analysis Scientist - Cristina Suanno, discusses ways to overcome autofluorescence, a common issue associated with multiplex immunofluorescent stained images.There are measures that can be taken at the tissue...
Utilizing AI to improve analysis accuracy and turnaround time for Preclinical tumor model IHC studies
⚡ Article Synopsis: In this article, we highlight a previous webinar case study where we utilized AI deep learning techniques to improve the accuracy and turn-around time for quantification of cytotoxic T-cell (CD8 marker), macrophage (F4/80 marker), and vasculature...
The use and value of the preclinical Bleomycin model in Drug Development for Idiopathic Pulmonary Fibrosis (IPF)
⚡ Article Synopsis: In this article, OracleBio has come together with one of our partners, TherapeutAix, who provide strategic and operational support for drug development projects, to provide our collective thoughts on the use and value of the preclinical Bleomycin...
The integration of Deep Learning methods to improve Nuclei Detection and Segmentation
In this article, we will briefly discuss different methods to detect and segment nuclei and in particular, give examples of how artificial intelligence (AI) Deep Learning (DL) methods are increasingly being applied within our organisation to streamline our image...
Using AI to assess Tertiary Lymphoid Structures in H&E and mIF stained Liver tissue
Following on from our previous article on Tertiary Lymphoid Structures (TLS), in which OracleBio clinical pathologist Gabriele Kohnen discussed the potential role of Tertiary Lymphoid Structures in normal and diseased tissues, this article describes some recent work...
Where does Cancer come from? – Cancer precursors and their terminology
In this article, OracleBio Senior Clinical Pathologist, Dr. James Going, talks about the importance of understanding where cancer comes from as we seek earlier detection and appropriate treatment.A neoplasm is a population of abnormal cells which persist and...
Using Deep Learning to address Staining Variance across Multiplex IF images
Multiplex IF assays are highly valuable in generating data that enables a deeper understanding of cell phenotypes, their functional status, and spatial relationships within tissues across different diseases or therapeutic interventions. However, the staining of...
OracleBio and the INCISE collaboration project
Bowel cancer is currently the second most deadly cancer in the UK, accounting for 10% of all cancer deaths. The current screening protocol for this type of malignancy involves a colonoscopy for patients who test positive for blood in their stool. About one in three of...
Working With Multiplex Images
Imagine an image 20,000 times the file size of a standard iPhone photo... and imagine hundreds of these images having to be transferred, stored, and analysed to reveal their secrets. That's the reality and the challenge facing researchers working in the field of...
Selecting the Correct Therapeutic Indication: A Case Study Utilising Tissue Microarrays (TMA) with Digital Image Analysis
Selecting the right therapeutic disease indication in which to trial new therapies is a notoriously difficult task. Failure to choose the right indication can result in failure in Phase II/III trials resulting in drug discovery programs being halted which, given...