At Scienta Lab, we are harnessing the potential of artificial intelligence to seize the biggest challenges in immunology today.

With cutting edge datasets, breakthrough capabilities in machine learning and world-class scientific collaborations, we are building a library of groundbreaking predictive algorithms.

Our library caters to academics and life-science companies involved in immunology to identify patient subgroups, predict patient prognosis, and treatment response for auto-immune diseases.

Discover our prototype: prediction of non-response to treatment in rheumatoid arthritis

Scienta Lab presented its proprietary model, able to identify non-responders to MTX and TNFi based on limited number of clinical and lab variables, at the 2021 French Rheumatology Congress.

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Our mission

The burden of auto-immune diseases

There are more than 80 different auto-immune diseases, affecting 3 to 5% of the population around the world. Type 1 diabetes, lupus, rheumatoid arthritis, inflammatory bowel disease and multiple sclerosis are the most common of these conditions.

Despite significant advances in understanding and classifying auto-immune diseases in the past decades, the challenge of heterogeneity remains a considerable. Heterogeneity impact both the onset and progression, diagnosis and prognosis of these diseases.

The data revolution

A multitude of anonymized data about patients with auto-immune conditions are generated everyday, including demographic information, disease activity index, biological data, images, treatments amongst others.

With breakthrough advancements in artificial intelligence and machine learning techniques, the possibility of translating this abundance of information into clinically relevant patterns is slowly becoming a reality.

The Scienta Lab expertise

At Scienta Lab, we are training our algorithms to identify patients, predict diagnosis and risk scores, and classify patients within auto-immune disease subgroups.

We are doing this by translating chaos into insights; yielding the largest ecosystem of datasets, scientific partnerships and machine learning capacities known to date.

The similarity of data across auto-immune diseases allows us to target develop a disease-targeted aproach, yet scale our models across the whole therapeutic area of immunology.

They trust us

“The models developed by Scienta Lab help us to gain deep insights on auto-immune diseases. It paves the way to a better disease management and more favorable therapeutic outcomes for patients.”

Pr. Xavier Mariette, Head of Rheumatology Service, CHU Bicêtre, Paris, France

“Working with Scienta Lab enables us to have access to a whole new field in epidemiology and will help take better care of patients in the near future.”

Dr. Samuel Bitoun, Rheumatology fellow, CHU Bicêtre, Paris, France


EULAR Congress 2022

Machine learning predicts response to TNF inhibitors in rheumatoid arthritis: results on the ESPOIR and ABIRISK cohorts

J.Duquesne, V.Bouget, P-H. Cournède, B.Fautrel, F.Guillemin, H.Signe, M.Pallardy, P.Bröet, S.Bitoun, X.Mariette

View abstract
2 June

EULAR Congress 2022

Machine learning predicts response to methotrexate in rheumatoid arthritis: results on the ESPOIR, t-REACH and Leiden cohorts

V.Bouget, J.Duquesne, P-H. Cournède, B.Fautrel, F.Guillemin, P.H. De Jong, M.Verstappen, A.Van Der Helm Van Mil, S.Bitoun, X.Mariette

View abstract
2 June

Meet the team

Scienta Lab is a French startup based in Paris, co-founded by a team with complementary skills and experiences.

Camille Bouget

Business development, marketing & communication.

Vincent Bouget

Biomedical partnerships, scientific & technical development.

Julien Duquesne

R&D, Technical development & data management.

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