We Are Building The Next Generation Tool Box For Life Science organizations 


Our Services

Our life science experts work together with specialists in machine learning, deep learning, natural language processing, and data visualization to deliver tools and solutions addressing challenges at different stages of healthcare product development.

HTA in silico

Using machine learning, we develop algorithms to predict HTA decision at early stages of product development. Our pharma and biotech clients can test alternative product profiles
in no time.

HTA compendia

To accelerate HTA reviews, we use natural language processing to generate structured compendia of published assessments for specific agencies and therapeutic areas or product classes.

Regulatory assessment in silico

Our machine-learning based tools can predict decisions of major regulatory agencies, including the FDA and EMA. These tools help pharma and biotech companies In decision-making related to clinical development program planning.

Regulatory assessment compendia

To accelerate regulatory assessment reviews, we use natural language processing to generate structured compendia of published assessments for specific agencies and therapeutic areas or product classes.

Real-world and clinical data analysis

We explore the use of novel approaches from data science in areas where statistical approaches fail or have major limitations. This includes, for example, the use of machine learning for generating synthetic control arms.

Synthetic data generation

Ensuring the privacy of health data is paramount for data owners as well as the source subjects. In order to enable researches to access data without compromising privacy, we can generate artificial data mimicking the properties of actual data. Analyses of the synthetic data will provide similar results to analyses of the actual source data.

Modelling and simulation

Using machine learning and deep learning to detect patterns based on clinical or other medical data, we can develop models to predict outcomes in virtual patients. These techniques may be used to conduct clinical trials in silico, which are useful to test drug candidates or alternative study designs before running real trials. They may also serve to extrapolate clinical trials.

Semi-automated systematic literature reviews (SLRs)

A number of tools have been developed to accelerate and reduce the costs of SLRs, including the use of AI. However, the performance of existing tools, in terms of automating data extraction, remains generally limited. We aim to improve upon existing algorithms for specific applications within life sciences.

Virtual reality simulation

We generate virtual reality simulations help patients or members of the general public in appreciating the effects of a healthcare intervention. Virtual reality simulations allow for the collection of data on their perceptions of intervention effects and on their preferences.


Areas of expertise

Machine Learning

Natural Language Processing

Data Visualization

Life Science

our goals

We help life sciences stakeholders 

to reach their goals in a smarter and faster way for the ultimate benefit of patients, with solutions using AI as an ubiquitous and invisible tool.


We deliver AI-based services to pharma and biotech companies along the full drug value chain.


We integrate AI in supporting public decision-makers to achieve optimal outcomes.


We empower patients to become actors in their disease management through the use of AI tools.


We help healthcare professionals integrate AI in their daily practice.


 We inform healthcare providers and help them optimize their offerings according to patient and societal needs.

Get in Touch

Give us a call or drop by anytime, we endeavour to answer all enquiries within 24 hours.