High Throughput Screening
In Silico Virtual Screening
Our AI-driven approach is accelerating drug discovery by leveraging our proprietary virtual screening platform across human health, agriculture, and environmental targets. Applying our vast databases of molecular structures and biological data, AI-driven virtual screening methods simulate and predict interactions between small molecules and target proteins/receptors. Through machine learning and deep learning models, AI sifts through immense datasets to predict the molecule's effectiveness in binding to a target, identifying potential drug candidates. Our approach significantly accelerates the identification of promising drug candidates, streamlining the early stages of drug discovery while reducing costs and laboratory time.
Drug Discovery at Scale
Integrative platform using AI
Netellis is an AI-driven biotech company that is accelerating drug discovery by leveraging our proprietary virtual screening platform across human health, agriculture, and environmental targets. Applying our vast databases of molecular structures and biological data, AI-driven virtual screening methods simulate and predict interactions between small molecules and target proteins/receptors. Through machine learning and deep learning models, AI sifts through immense datasets to predict the molecule's effectiveness in binding to a target, identifying potential drug candidates, and even predicting their properties and potential side effects. Our approach significantly accelerates the identification of promising drug candidates, streamlining the early stages of drug discovery while reducing costs and laboratory time.
Facile Research and Development Integration
Powering the Next Generation of Drug Discovery
Cost Effective
Virtual screening significantly reduces costs associated with traditional laboratory methods. By utilizing computer simulations and algorithms, we can virtually test millions of compounds against a target, narrowing down the selection of potential drug candidates. This approach minimizes the need for synthesizing and physically testing each compound in a lab, thereby saving time and resources.
Fast and Scalable
Virtual screening accelerates the drug discovery process. With powerful computational algorithms, screening a vast library of compounds against specific targets can be done rapidly. This speed allows researchers to analyze a larger number of compounds in a shorter period, potentially identifying promising candidates faster than traditional methods. Additionally, the process is highly scalable, enabling researchers to expand screening efforts without significant increases in time or resources.
Compound Diversity
​Virtual screening enables the exploration of a wide range of chemical space and compound libraries. Researchers can analyze diverse structures and properties of compounds virtually, allowing for the identification of molecules with unique characteristics that might not have been considered through traditional screening methods. This approach broadens the scope of potential drug candidates, increasing the chances of discovering novel and effective therapies.
Gene Atlas
Ultra High Resolution Microbiomics
Microbial gene catalogs serve as valuable resources for functional annotation, taxonomic profiling, comparative genomics, novel gene discovery, metabolic reconstruction, biomarker identification, and systems biology studies. They contribute to a better understanding of microbial communities and their ecological functions, as well as providing practical applications in various fields. However, a major limitation has been the relatively small size of these catalogs given the vastness of the gene diversity in bacteria. To address this limitation we have constructed a gene catalog with over 200M full length genes. This allows us to integrate the microbiome at scale. Coupled with XAI we are able to integrate samples and find hidden patterns in the noise that are associated with health and disease states. We are currently expanding this effort to included disease specific catalogs in cancer and neurodegenerative disease that will further enhance our high resolution microbiomics studies.