Category: Blog

Welcome to our latest blog post, where we delve into the evolving landscape of histology and image analysis through an exclusive interview with industry experts from NovAliX – a fully integrated drug discovery CRO based in Strasbourg, France.

In this insightful conversation, Didier Merciris and Florence Anquetil-Besnard from NovAliX share their experiences in incorporating Visiopharm’s image analysis software into NovAliX’s workflows, and the profound impact it has had on their projects and clients.

Visiopharm: Welcome, Didier and Florence. Can you tell us about NovAliX, the services you offer, and how you differentiate yourself from other CROs? 

Florence Anquetil-Besnard: NovAliX is a fully integrated drug discovery CRO. We support biopharma companies with a range of programs, from initial target identification to the delivery of preclinical candidates. We have seasoned teams in medicinal chemistry and pharmacology, covering a variety of fields – oncology, inflammation, fibrosis, infectious diseases, kidney diseases, and more. We work with a diverse selection of screenings and characterization techniques, including a unique DNA encoded library platform, along with a vast array of biophysical methods, including Cryo-Electron Microscopy (Cryo-EM). Such advanced technologies are rare finds in the market and enhance our research capabilities significantly.

Didier Merciris: In 2023, our former company, Galapagos, transferred all its discovery resources located in France to NovAliX. This strategic move included integrating a team of highly trained experts, each with over 20 years of experience in fields such as chemistry, protein production, in vivo pharmacology, DMPK (Drug Metabolism and Pharmacokinetics), translational science, and histology. We now offer comprehensive histology services tailored to any requirement within the histology workflow. This ranges from basic tissue processing to advanced staining techniques and in-depth image analyses.

Visiopharm: What problems were you trying to solve when you started working with us compared with previous analysis software and how did Visiopharm help you overcome those challenges? 

Didier Merciris: For years, we had been working with an old-fashion image analysis software with limited machine learning capabilities. Developing an image analysis project with this tool required extensive annotations and post-processing steps, which were not only time-consuming, but also yielded unsatisfactory results.

We were literally stuck due to the software’s limitations, which significantly affected our ability to accurately measure data on slides. This was a major source of frustration in my daily work.

Florence Anquetil-Besnard: When I joined NovAliX, one of the first things I did was to share my previous experience with Visiopharm. Indeed, I thought the software could significantly improve our capabilities due to its deep learning features; so, we quickly organized a proof of concept with David Mason (Technical Sales Specialist at Visiopharm). The aim was to present him with our most common and challenging issues. We aimed to test the system thoroughly. As expected, Visiopharm, through David’s efforts, was able to provide solutions to all our challenges.

Didier Merciris: During David’s demonstration, I was really amazed by how Visiopharm easily resolved all our imaging analysis problems. Visiopharm is a complex software to handle, however, thanks to the exhaustive training that we had when we bought the software, it was manageable to learn all its nuances easily.

Florence Anquetil-Besnard: I would say that we are now better equipped to address the complexity of organs. Taking kidney as an example, it is an organ divided into four main compartments: glomeruli, tubules, blood vessels, and interstitium. These parts are independent from each other, but can also be all connected together, posing unique challenges for analysis. Now, with Visiopharm, we can conduct detailed analyses in each area, a task that was significantly more challenging before. For instance, we can independently assess fibrosis in the glomerulus and in the interstitium. This improvement is largely due to the deep learning capabilities of the software.

Even more impressive, we are not limited to broad compartment analysis; for example, in mice, a single section can contain up to 200 glomeruli. Currently, we can isolate and derive specific data from each glomerulus independently.

This represents a substantial advancement for our research. Consequently, we can achieve more accurate and representative results.

Typically, working with a pathologist yields a score for the overall tissue. Now, we can provide a more detailed picture of the tissue section, not just an overall score but insights into specific changes occurring within the tissue.

Visiopharm: What were you specifically looking for in a solution, how did you go about your search, and what ultimately led you to choose Visiopharm?

Florence Anquetil-Besnard: For advanced users like me, the support team is also there to bring you even further than what you thought. For example, once I had a big challenge with a complex macrophage staining project involving multiplex techniques. The heterogeneity of the staining was problematic, with intensity varying significantly across samples. In the image analysis community, heterogeneity of fluorescent staining is a nightmare. So, I called the support team, and they guided me through an unconventional use of the software, not something that is taught at first sight. With their help and additional processing steps, we managed to overcome this variability, enabling us to deliver a reliable and robust analysis to our client.

This experience highlights the importance of not only overcoming technical challenges but also of being able to deliver solid, scientific solutions to our clients.

Florence Anquetil-Besnard: In the imaging community, it’s crucial to stay updated and leverage the most advanced tools to remain competitive. Our requirement was for a flexible solution capable of meeting the market’s existing standards. While the Oncotopix® Discovery software works for up to 4 markers, the transition to real multiplex analysis requires a more sophisticated approach. The introduction of Phenoplex™ has significantly simplified the analysis of complex multiplex immunostains.

Didier Merciris: Another major advantage that influenced our decision was the exceptional support provided by Visiopharm. As a “newbie” to the software, I really appreciate the constant availability of the support team whenever I need them. They respond quickly and efficiently to any queries or issues, which has been incredibly reassuring.

With Visiopharm, you’re never alone with your challenges; there’s a supportive community, the blog, and a dedicated support team ready to assist.

Visiopharm: What specific features of our software do you find most helpful?

Florence Anquetil-Besnard: With Visiopharm, the process is intuitive: start with an image, add annotations, and if opting for deep learning, proceed to train and validate, among other steps. But what is also really nice is the APP Center – it’s like entering a magical world where you can pick an existing app created by someone else, make minor adjustments to fit your needs, and then all of a sudden you have your own customized app, that you didn’t spend time to create, yet still reliable and efficient.

This flexibility is really helpful to adjust our workflows, offering both time savings and inspiration by exposing us to ideas from other APPs, created by other users in multiple different ways.

Moreover, the software’s versatility extends beyond just brightfield images, but multiplex fluorescent and special stains, enhancing our research scope. We are empowered to combine different histological techniques, like integrating IHC and ISH, allowing simultaneous investigation of proteins and RNA, or merging special stains like H&E or PAS with targeted IHC staining.

We can extract as much information as we want from the minimal amount of tissue, which is very helpful when you don’t have a lot of samples to work with, so we can maximize the analysis with just one image.

Didier Merciris: I used to work with another solution, and to be honest, Visiopharm is faster than the other software. It’s significantly quicker because it can process multiple images concurrently. While the speed can vary based on the user’s IT infrastructure, Visiopharm consistently delivers faster results.

Compared to our former software, we’ve seen a substantial reduction in processing time, enabling us to deliver data to clients much more rapidly. Another advantage is the user experience, the software was built with an accessible interface that is very easy to use after a little training.

Visiopharm: Could you share some insights into how the software has added value to your business and your customers?

Didier Merciris: As you know, the power of Histology lies in its spatial resolution at the cellular level.

We had a client interested in quantifying mucus production in epithelial cells from a diseased colon, without considering inflammatory cell infiltration.

The AI capabilities of Visiopharm significantly aided us in meeting the client’s needs within an extremely short timeframe.

Moreover, thanks to deep learning, we can tailor our algorithm to work with any staining. Now, if there are any color variations on the slide, we can simply add them to the APP.

This allows for much greater consistency in our data, which is a significant advantage for us and our clients.

Florence Anquetil-Besnard: An important aspect is our adaptability as a CRO; it’s not limited to Histology. We can adjust to almost any image. A recent unique project involved working with an image from a camera—not even a microscope, but a camera. We developed a program that automates the counting of tumor nodules in photographs from an ex vivo organ.

Previously, scientists had to manually count all the nodules. We’ve automated this task. By collaborating closely with our colleagues, we’ve enhanced the reproducibility and reliability of organ assessments. This project was internal, but ultimately, our client benefitted the most because we were able to deliver faster results.

Stay Ahead – Realize the potential of AI-driven precision pathology.

In conclusion, NovAliX’s integration of Visiopharm’s image analysis software has significantly transformed their histology and image analysis workflows, offering substantial benefits to their services and clients:

• Enhanced research capabilities: The adoption of deep learning and artificial intelligence within Visiopharm has empowered NovAliX to overcome previous limitations in image analysis, enabling more detailed and accurate data extraction from tissue samples.
• Customization and flexibility: The ability to customize algorithms and adapt to a variety of image types has allowed NovAliX to tailor their services to the specific needs of their clients, enhancing the adaptability and reach of their offerings.
• Overall business value: By leveraging Visiopharm’s technology, NovAliX has not only enhanced their service quality but also solidified their position as a cutting-edge CRO, capable of delivering high-quality, reliable results to their clients in the drug discovery industry.

Curious to hear more about Visiopharm software? Contact us here.

Reach out to NovAliX to hear more about their services here.

Exciting news for the world of science and digital pathology! 

Colorado State University (CSU), globally recognized research and veterinary institution, in collaboration with Visiopharm, a leader in image analysis software, is thrilled to announce its partnership in a graduate course in digital pathology. This innovative program will teach 42 graduate students modern digital methods in pathology practice, emphasizing the research and clinical applications of digital pathology (DP) tools.

This course is a unique collaboration featuring lectures and platform training by Visiopharm, complemented by the instruction of Dr. Mac Harris and Dr. Brendan Podell, assistant professors in the CSU Department of Microbiology, Immunology and Pathology, and seasoned Visiopharm users.

A key component of the course involves hands-on experience, where students will embark on an independent project using Visiopharm. These projects, crucial for practical understanding, will be presented between weeks 7 to 9 of the spring semester.

The primary audience for this course comprises graduate students, predominantly from Veterinary Science and Animal Science backgrounds. These bright minds are the future of independent research labs and Veterinary Pathology research, likely to make significant contributions in the next 2-3 years.

Stay tuned for more updates, interviews, and insights as we embark on this exciting journey of innovation and learning.  

In today’s blog, dive into the engaging Q&A session with OracleBio, a pioneering CRO in quantitative digital pathology, as they discuss their journey with Visiopharm’s software. 

The interview with Gabriel Reines March (R&D Project Manager at OracleBio) and Karen McClymont (Image Analysis Project Manager at OracleBio) offers an insight into how OracleBio leverages cutting-edge image analysis and AI technologies to enhance research and development in pharma and biotech globally. From innovative algorithm development to their transition to a cloud-based infrastructure, discover the pivotal role Visiopharm plays in OracleBio’s work, especially in the fields of oncology and immuno-oncology.

Visiopharm: Can you tell me a bit about OracleBio and which services you are offering to your customers?

OracleBio: OracleBio is a leading Contract Research Organization (CRO) that provides quantitative digital pathology services to Pharma and Biotech globally. We help our customers by generating accurate and robust data from their histology images, enabling confident interpretation and efficient decision making for their R&D projects.

As well as experienced image analysts, our team is also made up of clinical pathologists, software engineers, and Pharma scientists. This broad expertise base allows us to advise our clients on the best histology staining and analysis approach to ensure relevant image analysis data can be generated in the most optimal manner.

We utilise commercially available image analysis software like Visiopharm and support all stages of the R&D pipeline, from target discovery to clinical trials, with a distinct edge in oncology, immuno-oncology, and fibrosis. Our expertise extends to a diverse range of histological techniques, such as H&E, Immunohistochemistry, Multiplex Immunofluorescence, in situ Hybridization, and Imaging Mass Cytometry. The power and versatility of the software, with the addition of deep learning capabilities, is well-suited to the innovative way OracleBio approaches algorithm development for the multitude of staining profiles that we encounter.

Important to the efficient delivery of data is our image analysis workflow, hosted on our purpose-built, state-of-the-art Amazon Web Services (AWS) cloud that is designed to enable quantitative digital pathology workflows at speed and scale. What’s more, in order to facilitate client engagement and collaboration throughout the study’s lifecycle, we have created our own Visiopharm-powered remote image viewing portal, OBserver, where clients can log on to generate annotations and review analysis overlays.

The power and versatility of the software, with the addition of deep learning capabilities, is well-suited to the innovative way OracleBio approaches algorithm development for the multitude of staining profiles that we encounter.

Visiopharm: Since when have you been using Visiopharm and what led you to Visiopharm originally?

OracleBio: As a Digital Pathology CRO, our primary focus is to generate robust data from our clients’ images. Having a powerful and flexible image analysis software such as Visiopharm provides us with options for innovative solutions to the more challenging image analysis problems. We integrated Visiopharm into our roster of image analysis tools back in 2016. Some of the software features that attracted us were:

• the inclusion of different Deep Learning neural networks to train and deploy tissue classifier and cell segmentation apps;
• the availability of a comprehensive collection of image post-processing steps, useful for customizing apps to suit specific study requirements;
• the flexibility around app development for building bespoke image analysis workflows.

For these reasons, Visiopharm quickly became an integral part of our image analysis workflow.

Visiopharm: Can you describe the process of implementing Visiopharm and how your experience has been working with our team? 

OracleBio: When we first introduced Visiopharm into OracleBio’s image analysis workflow, the software was run locally on our on-premise server, which meant we only had access to two user licenses and finite hardware resources. Although this model suited our needs at the time, the limitations of such a rigid IT infrastructure soon became apparent.

As the company expanded, so did the number of concurrent Visiopharm users. In parallel, developments in Artificial Intelligence (AI) powered image analysis technologies translated into an increased demand for GPU-driven Deep Learning algorithms. In response to this, we migrated our IT infrastructure to a purpose-built AWS cloud environment, with flexibility, scalability and speed at the heart of it. Our proprietary ‘QDPConnect’ cloud management system, built with our sister company Sciento, enables our Image Analysis scientists to launch virtual machines containing Visiopharm, with the desired hardware specifications such as GPU support, processing power and memory, to suit specific study requirements.

It’s always a great experience to interact with the Visiopharm team! Their technical experts are always on hand to answer any questions, from supporting installation of the latest software update, to offering advice on specific software issues. A number of our team have also benefited from attending Visiopharm Academy courses to further develop their knowledge of the software. More recently, we joined Visiopharm’s Beta-Tester partner programme, where we get access to the latest software releases and provide expert feedback on the new implemented features and tools, such as the Phenoplex module and the Guided QC workflow.

It’s always a great experience to interact with the Visiopharm team! Their technical experts are always on hand to answer any questions, from supporting installation of the latest software update, to offering advice on specific software issues.

Visiopharm: What kind of problems or questions of your customers can you address with Visiopharm?

OracleBio: We use Visiopharm on a daily basis to provide answers to the research questions posed by our customers. This can range from a simple tumour-stroma classifier on a single-plex chromogenic IHC study, to more complex cell detection and phenotyping on high-plex immunofluorescence assays.

The Tissuealign™ module within Visiopharm has been very valuable when clients have requested segmentation of the tumour microenvironment of IHC and IF images in the absence of a specific tumour marker or any distinctive tumour morphology. Co-registration of the stained tissue images with their corresponding H&Es has enabled us to establish more accurate segmentation which has subsequently led to the generation of more robust data.

Our clients are often interested in the downstream application of bioinformatics. The flexibility in custom-built apps allows us to generate a large amount of useful information defined by the output variables; from a simple cell count (including positive and negative cell populations) to specific x-y coordinates for each cell and mean intensity data for all marker layers present. The exported data can be compiled into formats compatible with a client’s bioinformatics platform for subsequent data analysis.

Visiopharm: What specific features of our product do you find most helpful?

OracleBio: The flexibility in app development is one of the most useful features of Visiopharm and allows us to undertake a variety of projects ranging from single-plex IHC to challenging multiplex IF analysis. Being able to custom-build algorithms to address image analysis challenges is a major advantage of the software. There are a number of routes to take during algorithm development and depending on the tissue type, marker staining and required outputs, algorithms can be easily adapted to optimise the results for each study.

The flexibility in app development is one of the most useful features of Visiopharm and allows us to undertake a variety of projects ranging from single-plex IHC to challenging multiplex IF analysis.

More specifically, the addition of AI to the software has greatly improved our experience, especially with regards to nuclei segmentation. Variable stain intensity is a common factor seen within and between batches of samples, predominantly in clinical studies. The implementation of AI tools has allowed us to develop more robust algorithms that can be applied across a greater range of staining and tissue types. Additionally, the continual software updates, which have recently included improvement to marker visualization and the usability of the colour adjustment tools, provide an enhanced overall user experience.

Visiopharm: Can you share any recent results/outcomes that you have achieved using the platform?

OracleBio: Last year, our collaborative poster with Akoya Biosciences was presented at AACR 2023. OracleBio performed image analysis on samples stained with one of Akoya’s signature mIF panels. We used Visiopharm to profile the immune contexture and tumour spatial interactions in a set of tissue cores, covering a range of NSCLC subtypes and tumour staging. Our approach started with the generation of CD8, CD68 and DAPI cell objects using a Deep Learning algorithm trained on a range of TMA cores. A hierarchical post processing approach was then applied to create CD8, CD68, PanCK and remaining DAPI cell objects for downstream phenotyping. We generated cell object data per core using Visiopharm and carried out spatial analysis using an OracleBio proprietary program (PhenoXplore) to perform neighbourhood analysis for selected phenotypes.

For more details on how we’ve used Visiopharm to analyse samples by incorporating a hierarchal approach to cell detection and phenotyping, check out this case study where we analysed 8-plex multiplex IF staining in CRC & NSCLC tissue. Tissue segmentation using AI deep learning is also demonstrated within Pathology-defined tumour microenvironment regions.

Another poster, presented at the Digital Pathology & AI Congress US 2022, demonstrates how we utilised Visiopharm to develop image analysis techniques to quantify HBV on liver samples. The study samples were stained using a 12-plex multiplex IF assay to provide a better understanding of the liver viral burden and immune cell types involved in this disease. To ensure the most accurate detection of all required phenotypes, customized cellular analysis algorithms were developed to detect and phenotype individual cells. T-cells (CD3) and B-cells (CD20) were identified, along with macrophages (CD68) and these populations were further classified to identify immune cell phenotypes of interest. Hepatocytes were formed using the NaK-ATPase membrane marker and grouped into HBcAg-positive and HBsAg-positive populations. The workflow demonstrates the capabilities of Visiopharm in tackling high-plex studies where precise segmentation of sub-cellular structures is vital to generate robust data and support our clients’ needs.

Since 2020, OracleBio has been a partner in the INCISE project, a triple helix collaboration between industry, academia and the UK’s National Health Service. The goal of the project is to develop an AI-powered risk stratification tool that will predict polyp recurrence using data from pathology, genomics, transcriptomics and clinical records. As the Digital Pathology lead, OracleBio was responsible for configuring the image analysis pipeline, which was built around Visiopharm. Using the software’s Deep Learning capabilities, we build, train and run a selection of apps, including tissue classifiers and cell detection algorithms, on IHC and multiplex sections. Thanks to Visiopharm’s built-in parallel processing feature, supported by our scalable AWS cloud infrastructure, we are able to concurrently process multiple apps across several sections from the 2,700-patient cohort at speed, and deliver the results back to the consortium in a timely manner.

Transform Your Research with Cutting-Edge Image Analysis 

As we wrap up the overview of OracleBio’s journey with Visiopharm, it’s clear that this collaboration brings pivotal benefits to the CRO and its clients. Key advantages include: 

Robust Data Generation: The integration of Visiopharm’s software into OracleBio’s processes has enabled the generation of more accurate and reliable data from histology images, enhancing the quality of R&D outcomes for their clients. 

Tailored Analytical Capabilities: Visiopharm’s flexible software allows OracleBio to develop customized image analysis algorithms. This adaptability is crucial for meeting the diverse and specific needs of their clients in various research areas. 

Expanded Operational Capacity: The adoption of Visiopharm’s technology, particularly its cloud-compatibility, has significantly increased OracleBio’s analytical capacity. This allows for handling larger-scale projects more efficiently, thereby expanding their service offerings and client base.

Are you curious to hear more about our image analysis software? Don’t hesitate to contact us for more information.

For more information about OracleBio’s services, contact the team at enquiries@oraclebio.com 

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Today, we are excited to bring you an in-depth conversation with StageBio, a leading CRO based in Virginia, US, that has embraced Visiopharm software as its primary image analysis platform. StageBio provides GLP-compliant research, preclinical and clinical histology, pathology, and specimen archiving services for the biopharmaceutical, medical device, and contract research industries. 

Join us in this dialogue with Derick Vollmer, Digital Pathology Manager at StageBio, and discover the key reasons behind StageBio’s adoption of Visiopharm software, the challenges they had with previous solutions, and unique use cases that streamlined their operations and boosted client collaborations. 

Visiopharm: Welcome, Derick. Can you tell us about StageBio, your services, and how you differentiate yourselves from other CROs?

Derick Vollmer: Absolutely. At our core, StageBio is a CRO with multiple sites in the US and one in Germany, and as we expanded, we’ve incorporated a lot of specialized services. These include a medical device team, histology labs, pathology, neurology, molecular departments, toxpath labs, and archival services. Our key strength is, that we have a lot of specialized and experienced resources under the StageBio umbrella. As a result, we’re equipped to offer everything from standard histology lab work to advanced IHC or molecular work. On the digital pathology front, where I’m deeply involved, we can provide diverse imaging capabilities, including slide scanning, specialty scanners, and micro-CT. We operate internationally with clients from all over the world, which is working nicely, since we host all digital slides and results in the cloud.   

Currently, Visiopharm serves as our primary analysis package. While in the past we have utilized other tools, we have found Visiopharm to be more suited to our evolving needs. 

Visiopharm: What led you to search for a solution like Visiopharm?

Derick Vollmer: When the new groups merged into StageBio, the digital pathology team was suddenly presented with an influx of new types of work that required innovative solutions. One prominent task that comes to mind is the multiplex co-localization analysis on an immunofluorescence slide. It was a macrophage M1/M2 identification analysis.  Although we had conducted these stains successfully, we hadn’t performed such an analysis before. In the beginning, we were exploring the tools we had at our disposal, since at that time, we didn’t have access to Visiopharm. We did experiment with other software, which simply did not meet our requirements. It felt like we were pushing these tools to their limits without achieving our desired outcomes. So we reached out to our new team in Freiburg, Germany, who were already using Visiopharm and discovered they were developing an APP specifically for M1/M2 analysis. With their foundational work and significant contributions from the US-based Visiopharm support team, we tailored the analysis further. The combined efforts resulted in the successful M1/M2 macrophage co-localization analysis.  

This project showed us, that Visiopharm is an excellent piece of software for remote work and cross-site collaboration. Its capacity for co-development across diverse teams and the exceptional support we received from the Visiopharm technical team were invaluable. Their responsiveness to our inquiries has always been prompt, aiding us in designing and tweaking apps for specific analytical needs. 

We were previously also using different software, including freeware and although they remain useful for certain tasks, they are complicated. When we tested different software, none seemed to completely align with our needs. Many excelled in one area but fell short in another, they seemed very specialized in one type of thing. Visiopharm’s flexibility, especially with its AI and deep learning tools, has proven incredibly helpful for us. Visiopharm not only saves time in analysis, it’s also more intuitive to use, it’s flexible and easier to train other users. While the software is comprehensive with numerous features – many of which we were initially unaware of -, the resources available on the Visiopharm website, especially the training videos, have been incredibly helpful, and of course, reaching out to the team for questions.  

Today, we continue to explore new analyses, especially at our Marlborough, MA site. With each new challenge, our proficiency with the software grows. Given the diversity of our company and the wide range of specialized fields, the software’s flexibility is precisely what we need. It is an incredibly productive software to meet any of the needs that we came across to this point.

“Visiopharm’s flexibility, especially with its AI and deep learning tools, has proven incredibly helpful for us. Visiopharm not only saves time in analysis, it’s also more intuitive to use, it’s flexible and easier to train other users.”

Visiopharm: Do you recall specific capabilities you were missing in your previous solutions, limiting your analysis potential?

Derick Vollmer: Certainly. Deep learning was one of the most significant features and a key selling point when we initially considered Visiopharm. Let me give you an example: On the medical device side, we often work with bone studies, including dental and femoral defects. Our objective in these studies is to observe new bone growth in response to the implant material or treatment within a particular region of interest. Previously, the software tools we had access to, couldn’t handle the variability in the morphology of bone growth. Their color-based tissue detection approach often led to inaccuracies, requiring many hours of manual adjustments. Analyzing elements such as residual implants within these defects became increasingly complex, particularly with those typical histological artifacts. We’ve always emphasized accuracy in our work, often taking extra time to achieve the most precise results. When it comes to the bone growth analysis, the Visiopharm’s deep learning AI has been a fantastic resource. We trained models on new bone growth and this has proven incredibly efficient in capturing detailed bone analysis. In essence, the deep learning capabilities of Visiopharm have significantly improved our analysis process compared to tools that only offer color segmentation. 

Furthermore, we needed a flexible software solution tailored to our regular tasks, such as the bone defect analysis and the Multiplex analysis, among others. But with our business evolving, we also wanted a solution that could adapt to new challenges. 

For instance, we also conduct numerous ocular studies, especially retinal cell layer analysis, so we needed software that could distinctly recognize and analyze them. With the help of deep learning, we trained a system to identify these layers swiftly and effectively. Then, by applying this trained model, we could isolate particular areas of an ocular section and perform a better, more focused analysis. This showcases the adaptability and precision Visiopharm offers.  

Before this, we manually outlined these regions, a tedious process. We used Photoshop for image masking, a method that consumed a lot of time and often involved pathologists to determine the regions of interest. In conclusion, Visiopharm not only optimizes the time of analysts but also significantly reduces the workload for pathologists, as it allows team members to focus on other critical tasks.  

So, in essence, it’s the software’s flexibility that not only meets our diverse needs but also saves us time.

“When it comes to the bone growth analysis, the Visiopharm’s deep learning AI has been a fantastic resource.”

Visiopharm: Could you share some insights into how the software has added value to your business and your customers?

Derick Vollmer: Much of the value comes from the software’s flexibility. Here’s an example: Last week, a client approached us with just a histology request, specifically for pathologist evaluation. The slides they provided had a multiplex chromogenic stain, which is still rather rare. After the initial evaluation, both our pathologist and the client felt the performed standard assessment did not fully meet their needs. They wondered if a more precise, quantitative analysis could determine the cell count in the tissue. 

My answer was: “Yes, we can do that”. I hadn’t done this before and I hadn’t even seen the slides yet, but I have a lot of faith in Visiopharm’s ability to distinguish unique stains.  So that’s part of the exciting thing about using Visiopharm. It allows us to explore beyond the initial request, to enhance the customer’s research and its results. It has added value to our business and to our customers.  

Our approach is collaborative. Instead of merely executing a client’s request and returning the data, we actively engage with them, exploring how we can further enrich their findings. We tap into our expertise, propose potential enhancements, and experiment with the resources we have. If our investigations show promise, we’ll suggest an expanded scope of work. Many of our clients are receptive to this proactive approach, pushing us to help them push their research further as well. That’s how it adds value in all cases around the board.

“So that’s part of the exciting thing about using Visiopharm. It allows us to explore beyond the initial request, to enhance the customer’s research and its results. It has added value to our business and to our customers.”

Accurate and flexible tissue research requires the right tools.

StageBio’s decision to integrate Visiopharm software into its workflow has proved to bring multiple benefits to the CRO and its clients, allowing them to get more and better research done: 

• AI deep learning has transformed how the CRO handles routine tasks, allowing for enhanced precision and efficiency. 
• The intuitive interface of the software and the excellent support team facilitate training new users and developing new algorithms. 
• The flexibility to solve a broad range of tasks and thus enabling more in-depth and focused analyses, has added extra value to the CRO’s offers and to their customers’ research.  

Curious to hear more about StageBio services? Check out their website. 

If you would like to hear more about Visiopharm’s image analysis software, contact us here.

As we enter October, the breast cancer awareness month, we had the privilege of sitting down with Dr. Jan Trøst Jørgensen to discuss the 25th anniversary of HER2 targeted therapy – a revolutionary approach that has transformed the landscape of breast cancer treatment.

Dive into our enlightening conversation as we explore this milestone and its lasting impact on patient care. 

Visiopharm: Welcome Jan, can you tell us a little bit about you and your background?

Jan Trøst: Certainly. My academic background includes an MSc in Pharmaceutical Science and a Ph.D. in Clinical Pharmacy. I have over 40 years of experience in clinical development encompassing both drugs and diagnostics, mainly in oncology. For the past 10-15 years, I have worked as an independent researcher at the Dx-Rx Institute, where I advise both pharmaceutical and diagnostic companies, engage in research, and have had the freedom to publish a number of scientific papers. 

I have maintained a long-standing interest in companion diagnostics and have been involved in research in this field for many years. My interest in this area dates back 45 years to my lectures in basic pharmacology at the University of Copenhagen, where I was introduced to the concept of “rational use of drugs” or “rational pharmacotherapy.” This concept was already at that time translated as “the right drug to the right patient at the right time, in the right dose.,” However, it was easier said than done, due to the limited knowledge of pathophysiology and drug mechanisms of action at that time. However, with the advances in molecular medicine over the past 30-40 years, we have gradually begun to practice what was once known as rational pharmacotherapy, now referred to as precision or personalized medicine. This has been enabled in part by the development and use of new molecular diagnostic methods, including companion diagnostics. 

Visiopharm: This year marks the 25^th anniversary of HER2-targeted therapies. We have come a long way, haven’t we?

Jan Trøst: Yes, we have. The approval of the monoclonal antibody trastuzumab (Herceptin®) and the immunohistochemical assay HercepTest marked the beginning of a new era in treatment of cancer. This is the first time that we see a simultaneous approval of a drug together with a companion diagnostic assay. During the preclinical development of trastuzumab, a link between HER2 positivity and its tumor-inhibitory effect was discovered, and the subsequent parallel clinical development of drugs and diagnostic seemed obvious. Furthermore, as only 20% of women with breast cancer are HER2 positive, initiating treatment with trastuzumab without testing for HER2 has very little meaning. 

“The approval of the monoclonal antibody trastuzumab (Herceptin®) and the immunohistochemical assay HercepTest marked the beginning of a new era in treatment of cancer.”

A few years after the approval of trastuzumab, the importance of the parallel drug-diagnostic development was emphasized by former ASCO president Gabriel Hortobagyi, who stated that without the assay, trastuzumab would likely have been dropped during clinical development due to insufficient efficacy in an unselected patient population. This was subsequently supported by a sample size calculation performed by the National Cancer Institute based on outcome data from the phase III trial of trastuzumab in patients with metastatic breast cancer. In this study, 469 HER2-positive patients were randomized and the trastuzumab group showed superiority over the chemotherapy group. These calculations by the National Cancer Institute showed that a similar study without testing for HER2 would have required more than 8,000 patients to reach the same efficacy outcome as that in the original phase III trial. Given my background in drug development, I strongly doubt that such a large-scale clinical trial would have ever been conducted. 

This example emphasizes the significance of the drug-diagnostic co-development model and the clinical enrichment trial design. Using this design, patients are enrolled based on specific molecular tumor characteristics associated with the efficacy of the drug. By employing this type of design, the statistical power is increased, allowing meaningful clinical trials to be conducted in a relatively small number of patients. Consequently, drugs have been granted conditional approval by the FDA based on trials involving fewer than 100 patients, which was uncommon in the past. I think we can say that some of these drugs are standing on the shoulders of trastuzumab. 

This year marks the 25th anniversary of HER2-targeted therapy. This is a significant milestone in the history of cancer treatment and one that we should celebrate. Trastuzumab, the first HER2-targeted therapy, was approved alongside the companion diagnostic assay, HercepTest, in 1998, which is another anniversary to celebrate this year. To describe this achievement, we in fact published an article in Frontiers in Oncology two years ago. 

Visiopharm: What have been the primary challenges during these 25 years of HER2?

Jan Trøst: Cancer remains a life-threatening disease with significant unmet medical needs despite the progress made over the past 25 years. One of the challenges associated with cancer is its heterogeneous nature. For instance, lung cancer has traditionally been classified into two main groups based on its phenotypic characteristics (small-cell lung cancer and non-small-cell lung cancer). However, in recent decades, molecular medicine has revealed that lung cancer can be further divided into several subgroups based on their molecular characteristics. Along with this understanding, several drug-diagnostic combinations have been developed, enabling more effective treatment of patients with lung cancer.

“Cancer remains a life-threatening disease with significant unmet medical needs despite the progress made over the past 25 years.”

In general, the molecular classification of cancers has become increasingly important, and a few drugs with pantumor activity, are now classified as tissue agnostic, and for these drugs, it is a biomarker that solely determines their indication. A tissue agnostic drug refers to a drug that targets a specific molecular alteration across multiple cancer types, as defined by organ, tissue, or tumor type. For HER2, a drug such as trastuzumab deruxtecan (Enhertu®) also seems to possess pantumor activity and may likely in the future be classified as a tissue agnostic drug. 

Development of drug resistance is another major challenge in cancer treatment. This phenomenon is commonly observed with most cancer drugs over time. However, increased attention is now being paid to understanding the mechanisms leading to drug resistance and to the development of drugs to counteract it. The ultimate goal is to find a cure for cancer; however, in the meantime, the objective is to manage cancer as a chronic condition. In this scenario, if a drug fails due to development of resistance, another drug can be used as a replacement that does not show cross-resistance with the previous. 

Visiopharm: Can you discuss the challenges with HER2 interpretation?

Jan Trøst: Certainly. Breast and gastric cancer tissues possess intrinsic heterogeneity, with gastric cancer exhibiting the greatest degree of heterogeneity, which poses challenges and is the reason for the differences in HER2 scoring algorithms. Misinterpretation or discrepancies in scoring can lead to false-positive or false-negative test results, which can subsequently result in an incorrect treatment decision.  It is important to keep this in mind that the reported test result can have significant implications for the patient. Several papers and results from proficiency testing have documented discrepancies in scoring between laboratories, which emphasizes the need for new tools and techniques that can improve accuracy and reproducibility. It is always important to keep in mind that what is done in the laboratory can have a direct impact on patient treatment and outcomes.

“Misinterpretation or discrepancies in scoring can lead to false-positive or false-negative test results, which can subsequently result in an incorrect treatment decision.“

“Several papers and results from proficiency testing have documented discrepancies in scoring between laboratories, which emphasize the need for new tools and techniques that can improve accuracy and reproducibility.“

Visiopharm: Why are low levels of HER2 clinically relevant now?

Jan Trøst: HER2-low is now relevant because a new antibody-drug conjugate, trastuzumab deruxtecan, has demonstrated efficacy in patients with metastatic breast cancer with low HER2 expression, defined as IHC1+ or IHC2+, and negative for HER2 gene amplification. Both the FDA and EMA have approved this indication based on data from the DESTINY-Breast04 trial, where trastuzumab deruxtecan demonstrated benefits over chemotherapy in terms of progression-free survival in patients with otherwise limited treatment options. However, the accurate identification of these patients is challenging. One of the challenges in assessing HER2-low status is that current IHC HER2 assays are not designed to distinguish low levels of HER2 expression.  Recent data have shown a 41% discordance among pathologists in distinguishing between IHC0 and IHC1+. This is not sufficient, so there is room for improvement in both assay technology and training, potentially with the support of digital pathology tools.

“One of the challenges in assessing HER2-low status is that current IHC HER2 assays are not designed to distinguish low levels of HER2 expression.  Recent data have shown a 41% discordance among pathologists in distinguishing between IHC0 and IHC1+.”

Visiopharm: Can you elaborate more on companion diagnostics?

Jan Trøst: Absolutely. Companion diagnostics belong to the group of predictive biomarkers. While there are various types of biomarkers, such as prognostic and diagnostic biomarkers, predictive biomarkers can predict the outcome related to a specific event, such as a pharmacological intervention. The FDA and EMA define a companion diagnostic as an in vitro diagnostic device that provides information that is essential for the safe and effective use of a corresponding therapeutic product. Companion diagnostic assays has demonstrated their value in both drug development and in the treatment of patients in clinical settings for the past 25 years. These assays play a crucial role, particularly in the case of cancer, where early diagnosis and early intervention are vital, and companion diagnostics help to select the right treatment. In the US, between 60 and 70 drugs or drug combinations have a companion diagnostic assay linked to their use, primarily in oncology and hematology. It is essential that the companion diagnostic assay is developed in parallel with the drug to obtain simultaneous regulatory approval, so it is available in the clinic to support patient selection. However, in recent years, targeted drugs have been approved without a companion diagnostic despite the use of a predictive biomarker assay during clinical development. This discrepancy prompted me to write an article addressing this concern, which was published in the Journal of Clinical Oncology Precision Medicine last year.

“It is essential that the companion diagnostic assay is developed in parallel with the drug to obtain simultaneous regulatory approval, so it is available in the clinic to support patient selection.“

The development of companion diagnostics has primarily been driven by genomic biomarkers, utilizing technologies such as in situ hybridization, polymerase chain reaction, and next-generation sequencing, which account for approximately 75% of the analytical platforms. The remaining 25% is covered by IHC . However, we might see a shift towards protein-based assays in the future. The complexity of the human molecular landscape is substantial, with approximately 22,000 coding genes and with an exponentially growing numbers in the transcriptome and proteome, with approximately 100,000 transcripts and 1,000,000 proteins, respectively. The National Cancer Institute has recently advocated for the integration of proteomics with genomic data, termed “proteogenomics,” to address the additional complexity that proteins and their post-translational modifications add, which are not fully captured by genomic data. Furthermore, proteins are the primary targets of pharmacological interventions. 

Visiopharm: What should we expect in terms of future research in this area?

Jan Trøst: When it comes to drug targeting HER2, it looks interesting. A recent article published in Nature Review Drug Discovery discussed HER2 targeted therapy and its future direction and it looks like we should expect a lot. The drug pipelines across various pharmaceutical and biotech companies are brimming with innovations. In the years to come we will likely see the introduction of new monoclonal antibodies, bispecific antibodies, and newer antibody-drug conjugates like trastuzumab deruxtecan and trastuzumab emtansin. Additionally, new tyrosine kinase inhibitors, and therapeutic vaccines are also to be seen in the horizon.

“The drug pipelines across various pharmaceutical and biotech companies are brimming with innovations.”

HER2 targeted drugs are currently used to treat breast, gastric, and esophageal cancer, and recently also non-small cell lung cancer. However, HER2 overexpression is found in several other solid tumors, such as colorectal, bladder, cervical, and biliary tract tumors. Preliminary data from the DESTINT-PanTumor02 trial presented at the recent ASCO meeting showed high response rates, particularly in patients with IHC3+ tumors. Furthermore, a number of other trials with trastuzumab deruxtecan are currently ongoing in patients with different HER2 solid tumors; so, we might expect to see several new indications approved for HER2 targeted therapy in the future.   

Visiopharm: How do you see the role of digital tools and AI in diagnostics and treatment?

Jan Trøst: With respect to the utilization of slide-based assays, I foresee a promising future for the integration of digital tools and AI. For IHC and ISH assays, several challenges exist, including issues related to reproducibility and repeatability. I am confident that the implementation of image analysis and AI will help to mitigate these concerns and improve the overall accuracy and reliability of these assays. I think we can say that digital pathology adds a new dimension to this type of assay. For companion diagnostics, incorrect test results can have significant implications on patient safety, and it is imperative to ensure the accuracy and reliability of these assays to avoid potentially harmful treatment errors.

“For IHC and ISH assays, several challenges exist, including issues related to reproducibility and repeatability. I am confident that the implementation of image analysis and AI will help to mitigate these concerns and improve the overall accuracy and reliability of these assays.”

Visiopharm: Thank you Dr. Jan Trøst for sharing your knowledge and experience with us in this insightful conversation.

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Curious to learn more about Visiopharm’s AI-driven precision pathology solution for HER2?

Contact us here, and download our whitepaper to learn more about Visiopharm’s continuous scoring of the connectivity of the membranous HER2 staining.

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Main references related to the interview with Dr. Jan Trøst Jørgensen  

• Jørgensen JT, Winther H, Askaa J, Andresen L, Olsen D, Mollerup J. A Companion Diagnostic with Significant Clinical Impact in Treatment of Breast and Gastric Cancer. Front Oncol. 2021; 11: 676939. Read more
• Jørgensen JT. Twenty-five years with HER2 targeted therapy. Ann Transl Med 2023. doi: 10.21037/ atm-23-153. Read more
• Jørgensen JT, Hersom M. Clinical and Regulatory Aspects of Companion Diagnostic Development in Oncology. Clin Pharmacol Ther. 2018;103: 999-1008. Read more
• Jørgensen JT. The potential of trastuzumab deruxtecan as a tissue agnostic drug. Oncology. 2023. doi: 10.1159/000533866. Epub ahead of print. Read more
• Modi S, Jacot W, Yamashita T, Sohn J, Vidal M, Tokunaga E et al.; DESTINY-Breast04 Trial Investigators. Trastuzumab Deruxtecan in Previously Treated HER2-Low Advanced Breast Cancer. N Engl J Med. 2022; 387: 9-20. Read more
• Helwick C. Challenges of Accurately Identifying HER2-Low Breast Cancers. The ASCO Post. February 25, 2023. Read more
• Jørgensen JT. Oncology drug-companion diagnostic combinations. Cancer Treat Res Commun. 2021; 29: 100492. Read more
• FDA. List of Cleared or Approved Companion Diagnostic Devices (In Vitro and Imaging Tools). Read more 
• Jørgensen JT. Missing Companion Diagnostic for US Food and Drug Administration-Approved Hematological and Oncological Drugs. JCO Precis Oncol. 2022; 6: e2200100. Read more 
• Jørgensen JT. The current landscape of the FDA approved companion diagnostics. Transl Oncol. 2021; 14: 101063. Read more 

• Rodriguez H, Zenklusen JC, Staudt LM, Doroshow JH, Lowy DR. The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment. Cell. 2021; 184: 1661-1670. Read more 
• National Cancer Institute. Molecular Diagnostics for Cancer Treatment: Completing the Picture. Read more 
• Swain SM, Shastry M, Hamilton E. Targeting HER2-positive breast cancer: advances and future directions. Nat Rev Drug Discov. 2023; 22: 101-126. Read more 
• Meric-Bernstam F, Makker V, Oaknin A, Do-Youn O, Banerjee SN, Martin AG, et al. Efficacy and safety of trastuzumab deruxtecan (T-DXd) in patients (pts) with HER2-expressing solid tumors: DESTINY-PanTumor02 (DP-02) interim results. J Clin Oncol. 2023;41 (suppl 17; abstr LBA3000). Read more 

Today, we delve into a captivating dialogue with HistologiX, a prominent UK-based CRO that has adopted Visiopharm software to supercharge its image analysis capabilities and add value to its customers. HistologiX specializes in histology and immunohistochemistry services for pharma and biotech. Recently, their digital pathology team has been on a quest for a software solution that enhances their offering and optimizes their capabilities. Let’s learn more about their journey to find the ideal image analysis solution, the hurdles they once faced, and the enhanced offerings they can now present to their customers

Visiopharm: Welcome, James and Connor. Can you tell us about HistologiX, your services, and how you differentiate yourself from other CROs?

James Clay: We are a UK-based CRO, heavily concentrating on preclinical and developmental studies. From routine toxicology to complex assays like chromogenic and multiplex fluorescence. We do quite a lot of tissue cross-reactivity studies of therapeutic monoclonal and novel antibody constructs like nanobodies for regulatory submissions, and FDA drug submissions. In the last couple of years, we’ve been focusing much more heavily on immunofluorescence and multiplexing. We have a lot of fourplex assays up and running as well as Ultivue’s Immuno8 panel and have recently been doing studies where we are multiplexing RNAScope with IHC immunofluorescence.

Connor McCracken: There’s been a big demand from clients for us to use image analysis on their studies to gain as much information as possible. We are offering it as a service for most studies, especially the ones where the images are quite complex and there’s lots of data to generate.

James Clay: Our distinction lies in our bespoke client-focused approach. Answering the specific questions and challenges the clients have, rather than offering a big bucket list of our services. We get heavily involved with the study design, concepts, data outputs, and questions that they have. It’s always a two-way approach to working with the clients.

Visiopharm: What problems were you trying to solve and what was the limitation you experienced?

Connor McCracken: The main thing we were also missing was flexibility with the platform. With the solutions we had before, the modules are built in a way that “it’s for this or it’s for that”, whereas we were getting questions from clients that required a very specific approach that was not possible with what we had. We couldn’t answer some of the questions we were getting asked from clients unless we had the full open tool set available to us. For instance, in one study, we collected muscle biopsies and had to segment these muscles into individual fibers and then detect RNAscope signals within them, but also a membrane-based protein marker. This tailored analysis was previously impossible because we couldn’t connect these different analyses.

James Clay: We already had analysis capabilities with existing platforms, but one of the major things we lacked was AI/deep learning capabilities, which feed heavily into ROI (region of interest) segmentation, mining the images as much as possible, increasing the reliability of nuclear detections, and things like that. That was one of the main areas we were lacking in our current toolsets. We were always heavily dependent on excessive amounts of manual annotation, which is very time-consuming.

“After trying multiple providers, Visiopharm stood out with its intuitive design and efficient workflows.”
– James Clay, HistologiX

Visiopharm: How did Visiopharm’s software fulfill your needs? Which features were most relevant for you?

Connor McCracken: Having flexibility now with Visiopharm in the way that you can build your own apps, either using one of the prebuilt ones or building it from scratch and then chaining them together in a very nice and logical way – that’s the kind of thing we were missing before. Being able to go under the hood of algorithms is what we wanted and what we’ve got with Visiopharm’s Oncotopix Discovery. We can now just tell our clients “give us your question and we will figure something out, that meets it specifically.” Now we are able to offer something bespoke, that fits whatever questions our clients have.

James Clay: Primarily, just that ability to go beyond the pre-canned algorithms and develop things that were much more biologically relevant to the questions that our customers were asking. Offering individual solutions, which aligns very well with the way we like to work with the clients.

Connor McCracken: Also, the ease of training and applying deep learning has been really great. It’s super easy to use because there’s the pre-trained nuclear segmentation, which works nicely, but it’s easy to go and add extra training regions. Moreover, if we’re building the deep learning from scratch, it’s a similar workflow and we’ve been really impressed with how quick and easy it has been to work with it. We were concerned that it would be hard to work with it and would take lots of training, but it’s been very easy.

James Clay: After trying multiple providers, Visiopharm stood out with its intuitive design and efficient workflows.

Connor McCracken: Additionally, it kind of extends beyond just the software itself, but the support is really good. The training we’ve had from the academy team has been really good and really in-depth. And now, we just go to them with questions, and they just work through it with us and that’s been really helpful. A first-rate service really.

“With Visiopharm’s AI, we can now offer more in-depth and histologically relevant data, more structures, and functional regions of interest.”
– Connor McCracken, HistologiX

Visiopharm: How does Visiopharm’s software impact the way you now work with clients?

Connor McCracken: There are studies where everything, from tissue segmentation to nuclear detection benefits from having AI. Highly accurate nuclear segmentation can really increase the integrity of the data, especially for complex fluorescent samples. With Visiopharm’s AI, we can now offer more in-depth and histologically relevant data, more structures, and functional regions of interest. Moreover, our client’s needs are evolving, they want more complex questions to be answered through images rather than just a very general quantification. Now, we can offer that.

Another study we had was a multiplex IF with a variety of immune and macrophage markers in a xenograft model. We had planned to use Pan-Cytokeratin as a tumor marker, but realized after staining, that 50-75% of the tumor had differentiated to a state, that it was no longer expressing PanCK.Before Visiopharm, this would have meant weeks of manual annotations.

“Before we were always having to fit the study design to the analysis capabilities, whereas now we can fit the analysis approach to the requirements of the study.”
– James Clay, HistologiX

James Clay: This refined methodology has wide applications. We’ve begun exploring its use in multiplex fluorescence. By integrating registered H&E in the same section or adding other fluorophores, we can provide more cellular histological context. This level of detail, especially when combined with deep learning, enables more refined regions-of-interest analysis and a higher data granularity. We are doing many more studies now in the spatial biology sphere, like immune-oncology with lots of multiplex markers. The ability to build the spatial relationships how we want, not how it is pre-canned in an algorithm already, is really helpful. Visiopharm has transformed our approach. Not only does it enable deeper morphometric analysis, but it also allows for more precise quantification of protein expression within detected objects. One of the driving factors for our switch was the software’s ability to offer in-depth customized filtering, something our previous solution didn’t provide. But mostly, being able to design the right tool for the right job.
Before we were always having to fit the study design to the analysis capabilities, whereas now we can fit the analysis approach to the requirements of the study.

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Transform your image analysis approach with Visiopharm

Navigating the complex waters of histology and immunohistochemistry requires more than just knowledge—it demands the right tools. In a rapidly evolving market landscape, a flexible software solution is not just an asset—it’s a competitive edge. The transformative journey of HistologiX stands as a blueprint for the potential of the right technological integration. The adoption of Visiopharm has been more than a mere upgrade—it’s been a catalyst.

The benefits for the CRO have been manifold: 

1. Precision & Efficiency: From reducing manual annotations to implementing AI for tissue classification, the software has significantly streamlined workflows, allowing the CRO to deliver results with greater accuracy in reduced timeframes. 

2. Client-centric Solutions: With the flexibility of Visiopharm, the CRO can now tailor solutions to address specific challenges posed by clients. Whether it’s building from scratch or chaining algorithms, the CRO has newfound agility to meet diverse analytical needs. 

3. Business Growth & Diversification: The CRO’s capability to tackle more complex questions and provide detailed image analyses, facilitated by Visiopharm, opens doors to new project types and a broader client base. 

If you would like to learn more about the flexibility of Visiopharm software, contact us here. 

Curious to learn more about HistologiX’s services in histology and IHC? Get in touch with the HistologiX team at info@histologix.com or visit their website for more information.