Data Anonymization
Our technology facilitates anonymized data sharing and data analysis without disclosing the original data. We provide a set of software and analytical tools based on over 10 years of research in algebraic topology. The resulting data transformations can be freely shared and used for analysis without revealing any aspects of the data which may be proprietary or protected by legal frameworks
Anonymize data
Our methods do not just de-identify, they remove any possibility of recovering the original data in any way
Deployable platforms
Anonymize and jointly analyze data in any cloud or on-premises
Molecular signatures in cancer
Our Patient Responder website demonstrates our technology in a free to use example for cancer cell-line treatment
Our Services
Patient Responder For patient clinical or experimental data, we anonymize and analyze data to idenify subgroups of response and relevant biomarkers. This can be applied to one, or mutliple, sets of clinical trial data,
Comparative data signatures Our anonymization create signatures, which can be used in clinical trials to find patient responders. These groups can then be compared across trials and further interrogated across multiple datasets.
Over 80% of clinical trials fail, and in oncology the failure rate is reported to be over 95%.
We detect Patient Responders to increase the chances of successful Phase II/III trials
Want to learn more? See our Whitepaper
WhitepaperOur Team
A group of scientists combining mathematical and biomedical research, providing innovative solutions to anonymize, analyze and share data.
Co-Founder and CTO
Wojciech Chachólski
Professor at the Mathematics Department, Royal Institute of Technology, KTH and head of the Topological Data Analysis Group (TDA) at KTH. Prof. Chachólski’s research has been supported by the Swedish Research Counsel, Wallenberg AI autonomous Systems (WASP), and Digital Futures KTH.
Co-Founder and CEO
Ryan Ramanujam
Associate Professor at the Karolinska Institute. Dr. Ramanujam has a multidisciplinary background comprising advanced degrees in science, engineering and business, including a Ph.D. in Medical Science from the Karolinska Institute.
CSO
Sandra Di Rocco
Dean of the School of Engineering Sciences at Royal Institute of Technology, KTH. Professor Di Rocco heads a research group at the Mathematics Department, Royal Institute of Technology, KTH.
Get in Touch
We are currently onboarding customers into our analysis pipeline.
Our partners and funders
