LEAPfROG is a scientific study investigating the value of machine learning and big data to optimise pharmacotherapy outcomes in multimorbid patients. Multimorbidility means that a person has 2 or more chronic conditions.

More people with multiple medicines

The number of people with multiple chronic conditions is increasing. Often, patients get multiple medicines for these chronic conditions. This can lead to a complex combinations of medicines, which is called polypharmacy.

Complex medication regimens

Knowledge on the safety of complex medication regimens is limited. People with multimorbidity are regularly excluded from trials studying the effects and adverse drug events of medicines. These scientific studies usually only include healthy volunteers. The effects and adverse drug events in daily practice are therefore not clear. Especially in patients with multimorbidity and polypharmacy.

Learning medication safety system

In the LEAPfROG project, we will create a learning medication safety system. We will use several innovative machine learning techniques. Data from electronic patient records and information from existing knowledge sources will be combined. Through this combination, we expect reliable and explainable advices for individual patients and their medication regimens. Also for people with multimorbidity and polypharmacy.

Case study

To investigate the value of the LEAPfROG approach, we will study drug-induced kidney disease in patients with chronic kidney diseases. This is our case study.


LEAPfROG is a scientific research project and is leveraging real-world data to optimise pharmacotherapy outcomes in multimorbid patients by using machine learning and big data. LEAPfROG is a private-public cooperation between Amsterdam UMC, Vrije Universiteit, Open Universiteit and eight private partners. LEAPfROG is financed by NWO for 70%. The private parties are co-funding the project for 30%.