Created by Pangaea Data Limited


Data Science 

New insights are only the beginning: We gain concrete recommendations for action from biomedical data.


New insights only bring value if they lead to new action. Therefore, we pursue a holistic data science approach. Our goal is to extract knowledge and value inherent in the data. To succeed, we combine in-depth analytical skills with a comprehensive understanding of the scientific or clinical context. Our customers value the broad range of competencies of our data scientists and our collaborative project approach.


Bioinformatics Tools and Analysis

We are developing bioinformatics tools and analytical workflows for various biomedical datasets per specific scientific and clinical contexts at Pharmaceutical, Biotechnology and Healthcare organisations. 

We are also helping configure existing Bioinformatics tools and systems in the context of our customers' data sets and scientific (or clinical) objectives.

Easily executable analysis

We are making analytical algorithms and bioinformatics tools available through Pangaea's platform so end users with little or no technical experience (such as scientists, researchers and clinicians) are able to execute their analysis at the click of a button through a single web portal.

Training and Education

We are helping our customers and end users work with their analytical tools effectively and understand their significance in the context of their scientific or clinical pursuits.

Artificial Intelligence and Machine Learning

We are building supervised and unsupervised machine learning algorithms for automating current manual processes and identifying patterns within the context of specific datasets and use case which otherwise would go unnoticed. 

Through our expertise, we are also enabling predictive and AI driven models for hypothesis generation, quality assurance and process simulation.

Semantic Interoperability

Data Classification and identifying the unknown

We are building metadata vocabularies and ontologies to enable classification of biomedical datasets in specific scientific or clinical contexts. We are also helping our customers extend existing ontologies based on new information and contexts. We extend these efforts by using such metadata vocabularies and ontologies to semantically annotate datasets for easier findability, accessibility and usability (F.A.I.R principles).

Our semantic expertise is helping discover new cohorts and previously unknown associations within our customers datasets which is critical for generation of new scientific and clinical hypothesis.

Data and Systems Integration

We are enabling integration of data from different systems and databases (or data lakes) such that the inherent knowledge can be easily extracted and used for analysis and interpretation.