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At INNOVHEM we are developing innovative biomarkers and algorithms to predict sickle cell disease severity and assess the efficiency of treatments in development

Developing research innovations to improve the health and quality of life of sickle cell patients

Sickle cell disease is the most prevalent genetic disease worldwide, affecting around 5 million people. Even though it was discovered at the beginning of the 20th century, therapeutic options are still limited, and disease monitoring is poorly adapted leading to a global reduction of patients' life expectancy by almost 30 years.

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Why prediction matters:

Sickle cell disease is a debilitating chronic disease whose manifestations can lead to sudden death.


Prediction will enable medical intervention to prevent these manifestations, thus improving patients' quality of life.

How INNOVHEM predicts:

Using a unique combination of biomarkers and machine learning, INNOVHEM is the first to develop a clinical score that will predict the occurrence of painful crises, the most common manifestation and leading cause of death in sickle cell disease.

Image by Alexandr Podvalny
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