Artificial intelligence is gradually establishing itself in one of the most complex areas of modern medicine, namely the diagnosis and stratification of cancers. The Parisian start-up Waiv announces its official launch accompanied by a fundraising $33 millionor approximately 30 million eurosto accelerate the development and deployment of its precision oncology tests based on artificial intelligence.
Coming from Owkin’s diagnostic division, the company wants to transform the way clinicians analyze cancers and guide treatments. Its objective is to industrialize a new generation of tests capable of simultaneously exploiting digital pathology data, clinical data and biological information in order to identify the most suitable treatments for each patient.
This approach is part of the rise of so-called medicine precisionwhere the therapeutic choice is no longer based on an isolated biomarker but on the analysis of multiple biological and clinical signals. In this context, the ability to interpret these volumes of data becomes decisive, going beyond traditional diagnostic methods.
Transform pathology slides into actionable data
The technological heart of Waiv is based on the analysis by artificial intelligence of digitized pathology slidesa growing field called digital pathology. These slides, historically analyzed under a microscope by pathologists, can now be scanned and interpreted by machine learning models capable of detecting biological signatures invisible to the human eye.
🚨 SMARTJOBS
- MISTRAL – Account Executive, Enterprise, France – Paris
- ANTHROPIC – Startup Partnerships – France & Southern Europe
- CONTEXT – HR Director – Human Resources Director
- ECOLE POLYTECHNIQUE – Director/Deputy Director of International Relations (F/M)
- CLAROTY — Sales Development Representative
- FRACTTAL — Account Manager (France)
- BRICKSAI — Founding Growth Manager
👉 Find all our offers on the DECODE MEDIA Jobboard
đź“© Are you recruiting and want to strengthen your employer brand? Discover our partner offers
The tests developed by the company make it possible to predict the response to certain treatments, identify biomarkers and improve patient stratification. Among the products already deployed are notably RlapsRisk BC, MSIntuit Suite or even BRCAura BCdedicated in particular to breast cancer.
By relying on data from current clinical practices, the technology aims to simplify diagnostic pathways and reduce the need for certain additional examinations, while accelerating therapeutic decision-making.
To support these developments, Waiv relies in particular on the PortrAIt consortium, a European precision medicine data network, as well as on a technological platform integrating proprietary models and multimodal analyses. The company also offers Destraan interoperable digital pathology platform allowing laboratories and pathologists to directly access tests within their existing work tools.
A rapidly accelerating market
Waiv’s initiative comes in a context where artificial intelligence is gradually transforming oncological diagnosis. Automated analysis of histological images is today considered one of the most promising fields of application of medical AI.
Globally, several companies are competing for this emerging market.
In the United States, PathAI has established itself as one of the pioneers of the sector. Founded in 2016, the company develops artificial intelligence models capable of analyzing tumor tissues to improve diagnosis and optimize clinical trials for pharmaceutical laboratories.
Another major player, Tempus has built a platform combining clinical, genomic data and AI analyzes to guide therapeutic decisions in oncology. The American company relies on one of the largest clinical and molecular data sets in the sector.
In Europe, Ibex Medical Analytics is a benchmark in the automated analysis of pathology slides, with solutions already deployed in several hospitals to detect different types of cancers.
In this competitive environment, differentiation relies largely on data quality, clinical validation of models and the ability to integrate these tools into hospital workflows.
A strategy at the crossroads of diagnostics and pharmaceutical research
Beyond clinical use, Waiv is also developing collaborations with the pharmaceutical industry to identify new biomarkers and improve patient selection in clinical trials. The company is working in particular with Merck & Co. to identify, using artificial intelligence, MSI biomarkers in colorectal cancer.
This dual approach, clinical diagnosis and pharmaceutical research, constitutes one of the preferred economic models in the medical AI sector. The technologies developed can both guide treatments in clinical practice and accelerate the development of new drugs.
A spin-out driven by a new generation of entrepreneurial researchers
Waiv is headed by Meriem Sefta, polytechnician and MIT graduate, former Institut Curie and former Chief Diagnostic Officer at Owkin. The company capitalizes on more than a decade of research in artificial intelligence applied to oncology.
According to the director, “precision medicine only works if patients are guided with certainty towards the treatment that suits them best”, highlighting the current complexity of therapeutic decisions in oncology.
Fundraising to accelerate international expansion
To support its development, Waiv announces a fundraising $33 millionor approximately 30 million eurosled by OTB Ventures and Alpha Intelligence Capital, with participation from Serena Data Ventures, Karista and Sista Fund.
This financing will help expand the portfolio of clinical grade tests, strengthen collaborations with the pharmaceutical industry and accelerate the company’s international expansion.
As volumes of medical data continue to grow and new targeted therapies emerge, artificial intelligence tools capable of analyzing this information are gradually becoming a central component of precision medicine. In this global race for diagnostic AI, Waiv now intends to establish itself as one of the European players capable of transforming these technologies into clinical solutions deployable on a large scale.
