AI DESIGNED FOR BIOMEDICAL DATA

Reliably find complex patterns in high-dimensionality biomedical data





Our Technology


Biomedical data have a problematic structure

Small numbers of patients in relation to the characteristics examined. Therefore, analyses of such data often result in a high rate of false-positives. biotx.ai's Machine Learning was designed to solve this problem and reliably finds complex interactions biomedical data.

Variants tested 1-by-1


Lack of predictive power

No new insights

Weak connection to drug targets



Next-Generation Biomarkers

While current biomarkers rely on single gene or protein variants, our Next-Generation Biomarkers are based on the complex interactions of multiple variants. They accurately predict disease status, allow for patient stratification and provide decision support in drug development and precision medicine.

Complex interactions


Accurate prediction

Patient stratification

Verified drug targets

Products


Alzheimer's Disease

Current Biomarker APOE4

60%

80%

Data Preparation

AI Analysis

Certification

Crohn's Disease

Current Biomarker NOD2

55%

> 75%

Data Preparation

AI Analysis

Certification

Hypercholesterol

> 80%

Data Preparation

AI Analysis

Certification

Type 1 Diabetes

Current Biomarker MHC

55%

> 75%

Data Preparation

AI Analysis

Certification

Rheumatoids Arthritis

Current Biomarker MHC

55%

> 75%

Data Preparation

AI Analysis

Certification

Multiple Sclerosis

Data Preparation

AI Analysis

Certification

Eczema (Atopic Dermatitis)

Data Preparation

AI Analysis

Certification

Case Studies


Companion diagnostic for the accurate prediction of FH

Our Next-Generation Biomarker identifies patients with Familial Hypercholesterolemia (FH). Once the condition is correctly diagnosed, FH patients can receive the adequate antibody treatment that will manage their disease. This project is the continuation of a pilot project initiated through our participation at SBC Digital Health.

Next-Generation Biomarkers to manage skin diseases

Our Next-Generation Biomarkers are used in LEO's upcoming large-scale patient platform for managing skin diseases. They provide hard evidence helping patients identify the specific subtype of their disease.

Prediction of drug candidate efficacy for neuro-degenerative diseases

In our partnership with Orion, we use our Next-Generation Biomarkers to help develop drugs against Parkinson's disease.

Founders


Dr. Jörn Klinger
Co-CEO / CTO

Data Science
Oxford, UT Austin

During his graduate studies at Oxford and Texas, Jörn investigated human cognition in order to optimize artificial intelligence. Insights from hands-on research in an indigenous community, neural-networks and agent models led to an outside-the-box machine learning understanding. After rounding off his skills with commercial experience at a big data start-up, Jörn brought his data skills to biotx.ai, which, combined with Marco’s genomics expertise, resulted in our AI platform specifically designed for biomedical data.

Dr. Marco Schmidt
Co-CEO / CSO

Biochemistry
FU Berlin, Cambridge

Marco is a biochemist with expertise in chemical synthesis and action of drug molecules. While deeply immersed in several experiments during his Marie Curie Fellowship at the University of Cambridge, he realized that there is great potential of using novel machine learning approaches in drug combinations. When Marco met Jörn, they started discussing the use of machine learning in drug development and arrived at the conclusion that an AI specifically designed for biomedical data was needed to overcome the limitation of current algorithms.

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