COGNANO - Providing Novel Biomarkers for Drug Discovery Decision-Making

Discover new biomarkers to accelerate therapeutics

We leverage antibody data and cutting-edge AI technology to develop highly accurate drug discovery seeds and diagnostic tools. By utilizing our extensive datasets, we efficiently identify promising therapeutic candidates, significantly accelerating the drug discovery process. Our work addresses unmet medical needs, delivering new hope to patients worldwide.

About us

Problem

Developing a new drug typically requires an investment of over $2 billion and takes more than 10 years to complete. Moreover, the success rate from preclinical trials to market approval is less than 10%, highlighting the significant challenges in ensuring both safety and efficacy. In the case of cancer drug development, it is particularly challenging to design drugs that do not harm normal cells, resulting in a success rate of approximately 3–5%.

As a result, many areas, such as rare diseases and specific types of cancer, still lack adequate treatment options. Drug discovery is not only time-consuming and expensive but also a highly risky endeavor.

Solution

We raise alpacas and sharks in-house, and utilize the vast amount of VHH data that we obtain from them. Using this valuable dataset, we have developed a cutting-edge technology called IBMET (Inverse Biomarker Exploring Technology) that leverages statistics and large-scale language models (LLMs) to efficiently identify novel antigens.

This advanced approach allows for precise epitope-targeting to increase the probabilities of approval and further unveils novel biomarkers to address unmet medical needs.

Proof

We have developed a biomarker for TNBC (triple-negative breast cancer), one of the critical unmet medical needs, and published our findings in a peer-reviewed academic journal. This research has now progressed to the mouse experimentation phase.

Additionally, we have released a dataset of VHH and antigen-binding interactions generated from two alpacas immunized with human IL-6 protein and the spike protein of SARS-CoV-2. This dataset is provided alongside a corpus for AI pre-training, making it a valuable resource for researchers and developers across the field.

View datasets

Research on VHH Antibodies

15Years

Antigens

50Types

Antibody Genes

300MReads

Labeled Antibody Sequences

30MClones

Frequently Asked Questions

Cognano employs a highly unique and groundbreaking approach to creating drug discovery seeds. As a result, we receive numerous questions from a wide range of individuals. Here, we provide answers to some of the most common inquiries.

Is Cognano considered an AI-driven drug discovery company?

Many companies are leveraging AI-driven drug discovery approaches based on chemical compounds, and AlphaFold's seed prediction technology, which relies on existing protein 3D structures, has garnered significant attention. However, AlphaFold's objective is to predict seed compounds for specific target molecules, not to identify the target molecules themselves.COGNANO's IBMET operates further upstream in the drug discovery process, serving as a proprietary algorithm that focuses on discovering critical target molecules—a domain beyond AlphaFold's scope. In this sense, AlphaFold and IBMET are complementary, working together to realize the potential of AI-powered drug discovery. COGNANO brings unprecedented insights to the field of drug development.

Does Cognano sell antibodies?

Cognano generates a vast amount of antigen-antibody pair data, enabling us to identify and provide comprehensive information on target molecules. This exhaustive target information serves as a highly accurate drug discovery seed, significantly reducing the cost and time required for drug development.