Computational Lifescience

Data science for a better future – the exploration of complex biological systems

What Computational Life Science brings you

Computational life science is an important factor for all companies in the healthcare sector that want to optimise their research and development and develop innovative solutions. Computational life science can offer significant advantages in the following areas:

  • Medication development
  • Personalised medicine
  • Diagnostics and Prognostics
  • Biotechnology
  • Health economics

Computational Life Science is an interdisciplinary field that combines knowledge of computer science, statistics, genetics, medicine, chemistry, agriculture and other related fields. Using data-driven AI approaches, biometric data can be systematically and precisely analyzed and identified.

Through data comparison, damage patterns can be identified at an early stage. More serious consequential damage to the respective biosystem can thus be prevented at an early stage. The Supper & Supper BIO team has extensive professional experience in hospitals and various biological institutions and organizations. We deliver customized AI and Machine Learning solutions.

In the analysis of biometrics, we combine classical statistical methods with our innovative machine learning models. Our procedures aim to identify hidden factors that improve the effectiveness of a product or minimize potential risks and dangers. Possible areas of application are:

  • Early detection of cancer using X-rays
  • Optimization of the pesticide effect in botan
  • Trial planning for clinical studies and field trials
  • Analysis of the interaction between genes and the environment

Supper & Supper’s BIO Data Science team can provide data-driven AI solutions to companies in virtually all bio-related industries. Our processes, techniques and products offer particularly great potential for:

+ Clinics and hospitals
+ Pharmaceutical industry
+ Plant protection companies
+ Research institute in the biological field
+ Seed companies
+ Companies in the field of medicine and biotechnology

Success Stories

S&S supports us in the preparation, modelling and visualization of complex data in field trial analysis. In doing so, in-depth knowledge in classical biostatistics plays just as an important role as modern machine learning methods, programming environments such as R/Shiny or the handling of Neo4j graph databases. With the help of S&S, holistic analysis tools could be developed and interfaces to users could be created, whereby the time from an idea to the analysis results was significantly reduced.

Dr. Julian Heinrich

Computational Lifescience Use Cases – Data Science in Application

Discover the possibilities

More Solutions


Exploiting new potentials of geodata with AI solutions


Mechanical Engineering


Data analytics meets machine learning


Stefanie Supper

Book an appointment?

click here!