




By using our bioinformatics expertise we optimise antibodies, so that researchers can design antibodies that are more effective in targeting specific antigens, have improved pharmacokinetic properties, and are less likely to cause adverse effects in patients. This approach can help to accelerate the development of new and effective immunotherapies for a range of diseases, including cancer and autoimmune disorders.
Our highly trained interdisciplinary team use state-of-the-art AI technologies to identify potential targets, pathways, and mechanisms of action of small molecules, which can help to accelerate the development of new and effective immunotherapies for a range of diseases, including cancer and autoimmune disorders.
Our highly trained interdisciplinary team use state-of-the-art AI technologies for developing novel approaches for Hit-to-lead identification and optimisation for an accelerated drug development workflow
Extremely committed team of biostatisticians, statistical programmers and AI engineers who help to deliver faster and meaningful information from your clinical studies
Our team of healthcare data engineers help in structuring and analysing big data to develop precision treatment solutions
Who we are?
Aomics GmbH is a deep-tech healthcare startup based in Europe, with its headquarters located in Frankfurt, Germany. Our focus is on utilising big biological data, deep learning, AI, and blockchain technologies to develop Immuno-Oncology and Immuno-Informatics Solutions.
Our company has created a personalised immuno-oncology tool called Onco-Cure. Using patient-derived tumour microenvironment (TME) data, the Onco-Cure analytical dashboard predicts specific immune biomarkers for each patient and enables oncologists to select and plan the best targeted therapies. Our goal with Onco-Cure is to provide the most insightful, approved, and personalised therapy options to oncologists within a 48-hour timeframe.
Compounds in Pipeline
Program
Monoclonal antibody
Monoclonal antibody
Small molecule
Small molecule
Discovery/Research
Preclinical
Clinical PoC Trials
Clinical Trial
Phase-I
Clinical Trial
Phase-II
Clinical Trial
Phase-III
NDA Filed
(FDA filing)
Technologies under development
Phase-1
Conceptualization
Phase-2
Proof of Concept
Phase-3
Testing & Validation
Phase-4
Launch & Marketing
Phase-5
Scaling & Establishing
Single-Cell Analysis for understanding Spatial Heterogeneity
Single-cell analysis is a valuable tool for understanding the spatial heterogeneity of the tumor microenvironment (TME). The TME is a complex and dynamic ecosystem composed of cancer cells, immune cells, stromal cells, and extracellular matrix components that interact with each other and shape the tumor's growth and progression. Single-cell analysis techniques, such as single-cell RNA sequencing (scRNA-seq) and imaging mass cytometry, can be used to analyze the gene expression and protein levels of individual cells within the TME. These techniques enable the identification of different cell types, such as tumor-infiltrating immune cells, cancer-associated fibroblasts, and endothelial cells, and can reveal the cellular heterogeneity within the TME.
Single cell sequencing for studying the immune system
Single-cell sequencing is a powerful tool for studying the immune system at the single-cell level. The immune system is composed of diverse cell types, including T cells, B cells, natural killer cells, dendritic cells, and macrophages, which work together to defend the body against pathogens and other threats. Single-cell sequencing techniques, such as single-cell RNA sequencing (scRNA-seq), can be used to analyze the gene expression of individual immune cells. This enables the identification of different immune cell types, as well as the identification of subsets and states within each cell type. For example, scRNA-seq can reveal the different types of T cells, such as CD4+ helper T cells and CD8+ cytotoxic T cells, and the different subsets of these cell types, such as memory T cells and regulatory T cells.
Artificial intelligence & Machine Learning for Immuno-informatics
Artificial intelligence (AI) and machine learning (ML) techniques are increasingly being used in immuno-informatics to analyze and interpret large amounts of data generated from high-throughput experiments. Immuno-informatics involves the application of computational and informatics methods to study the immune system, including the analysis of immune responses, vaccine design, and immunotherapy development. AI and ML techniques can be used to analyze high-dimensional datasets generated from techniques such as single-cell sequencing, mass spectrometry, and flow cytometry. These techniques can identify complex patterns and relationships between variables in the data that may be difficult or impossible to detect through manual analysis.
How we use Multi-omics data for Immuno target identification?
Multi-omics data integration is a powerful approach for identifying potential targets for immunotherapy development. Multi-omics data refers to the integration of multiple types of molecular data, such as genomics, transcriptomics, proteomics, and metabolomics, to provide a more comprehensive view of the molecular mechanisms underlying a disease or biological process. In the context of immuno target identification, multi-omics data integration can be used to identify potential targets for immunotherapy development. For example, by integrating genomics and transcriptomics data from patient samples, researchers can identify genes that are differentially expressed in tumor cells compared to normal cells. These differentially expressed genes may represent potential targets for immunotherapy development.
"AI empowered immuno-oncology solutions "
Who We Are
We are a German based company, specialized in the area of drug discovery and drug target identification. By leveraging state-of-the-art artificial intelligence, multi-omics and cheminformatic techniques, we efficiently reduce the time and cost of the drug development process to several folds.
Our Mission
“Make the best use of the state-of-the-art digital technologies, scientific knowledge and resources to accelerate the effective development of new diagnostic techniques and therapeutics for global health”
Our Vision
“To develop highly efficient and effective diagnostic and therapeutic techniques for a healthy future“
Our Values
- Respect
- Honesty
- Innovation
- Integrity & Ethics
- Goal oriented
- Environmental responsibility
- Employee growth
- Customer satisfaction
Our Role
“To serve the patients who are unfortunately suffering with diseases with unmet medical needs by accelerating the development of highly efficient and effective diagnostic and therapeutic techniques“
Our key priority
“Our key priority is to ensure that everyone has access to safe, affordable, fast and efficient solutions to the healthcare problems, especially for the disease areas with huge unmet medical needs”
What We Do
- Biological/healthcare data analytics
- Immunoinformatics solution development
- Drug target identification
- Hit-to-lead optimisation of compounds for drug discovery
- Drug development
- Drug repositioning
- Bioinformatics Software Development
- Biological Big data analytics
- Blockchain Solution development
- AI/ML model development
- Tech Support
Would you like to start a project with us?
Reach out on the given number or write us an email for further queries regarding project requirements