Ardigen research leverages Artificial Intelligence in various therapeutic areas, including: immunology, microbiome, and biomedical imaging. Working with us allows you to effectively use AI in drug discovery accelerating the process. Starting from the identification of biological targets, through their validation, optimization, and all the way to clinical trials, accelerating translational studies and the development of the diagnostics. With our team’s combined expertise in both AI and therapeutic areas, your research is expedited like never before.
Microbiome research can be taken to the next level by applying machine learning methods to metagenomic and other -omics data.
With Ardigen as your partner on the path to demystify the complexity of microbiome, you will effortlessly unlock the secrets of your data.
As Microbiome is a part of a bigger system we integrate sequencing data analysis with other measured parameters which leads to multidimensional findings. Such complex datasets usually leave standard analytical technologies clueless, but not Ardigen’s Microbiome Translational Platform powered by cutting-edge AI algorithms.
Deep learning-based Function discovery enables translation of identified microbial signatures into biologically meaningful information. Our technology has proven its value aiding multiple companies with improvement of their clinical trials, design of biomarkers or start of the development of novel therapeutics.
Is your microbiome data a mystery? At Ardigen we:
Decoding microbiome with AI. With us you can:
We are always excited to work in one of a kind projects that stimulates our development!
Ardigen is harnessing advanced Artificial Intelligence methods for novel precision medicine. The Immunology Team is rooted in biology and holds deep expertise in bioinformatics, machine learning, and software engineering. Ardigen’s in-house datasets together with advanced AI platforms empower the development of effective therapies. Our technologies unlock fast track to therapies driven by engineered TCRs, TCRm-Abs, immunogenic neoepitopes, as well as AI-based biomarker discovery.
We are open to partnerships and scientific collaborations. We focus on solving problems. Let’s talk and see how we can help you with your challenges.
We have created an artificial intelligence platform dedicated to be a part of the cancer vaccine development process.
ArdImmune Vax AI Platform uses sequencing data to generate and prioritize antigen targets of cancer vaccines and T-cell therapies. The platform comprises of bioinformatics and machine learning set of algorithms that generate putative antigens, assess patient’s MHC, antigen(peptide)-MHC binding affinity, likelihood of peptide presentation by the MHC molecules on the cell surface, likelihood of pMHC attracting T-cells to generate functional responses described as immunogenicity.
Following the unique opportunity for curing patients provided by the development of cell therapies, Ardigen has set on a path to advance the field with the application of its artificial intelligence platform.
Ardigen’s TCRact AI Platform uses target peptide and MHC sequences, as well as TCR sequences, to assess target fitness for the use in TCR therapy. The scope of the platform entails also the following analyses: pMHC:TCR complex binding affinity, stability, suggestions of TCR sequence improvements, assessment of potential off-target activity of TCR, generation of novel TCR sequences matching the desired specificity and safety profile.
Throughout many years, information contained in images was underappreciated and unused due to the limitations of human capabilities. However, thanks to recent breakthroughs and our own expertise in Computer Vision, we are able to guide you through the effective analysis of vast amounts of images, which are an especially rich source of information.
Our Technology Platform for Biomedical Imaging, provides you with reliable and interpretable AI models, for both clinical and preclinical usage.
Example applications of the technology platform include:
Histology images are one of the most challenging to be analyzed automatically. This is due to multiple factors, such as super-resolution, variation in magnification, different tissue preparation techniques between laboratories, and the necessity to provide prediction explanations despite the relatively small number of samples.
Our platform enables you to process whole-slide biopsy images in a scalable manner, without any loss of information contained in the image. Moreover, it highlights areas that contain pathological changes. This process can be applied for various scoring systems, such as the Nancy and Geboes Histological score (for inflammatory bowel disease data) or the Gleason score (for prostate cancer data).
The goal of High Content Phenotypic Screening is to identify morphological patterns in cell populations and to probe the causes and cures for various diseases. For instance, one particular application is to characterize interactions between multiple cell lines and compounds.
This can be achieved by generating a vast number of images, which cannot be analyzed by the human eye, and even standard image processing techniques may bring unsatisfactory results. Our platform solves this challenge by providing modular deep learning pipelines that generate image based compound descriptors, predict selected molecular properties and automatically retrain to fit newly generated data.
Over the past few years, the microarray technology has gained momentum in the drug and biomarker discovery fields. Extracting information from microarrays requires precision and reliability, and our microarray analysis system delivers it all.
It performs quality checks and applies image correction techniques, such as distortion correction or flat-field correction. It also finds the grid of features on the array and extracts their pixel intensities. Additionally, the system can be deployed in the cloud and easily integrated into the already existing analytic pipelines.