PARIS—The Quinten Group, an artificial intelligence/machine learning (AI/ML) services and products company, recently announced the launch of a new spin-out company, Quinten Health, an offering for global, integrated analytical services and tools development.
“While healthcare has been the major focus for Quinten so far, it was time to gear up and specialize as a genuine HealthTech company, serving and promoting synergies between drug developers, care providers, and public health decision makers through artificial intelligence and machine learning solutions developed with and for them,” stated Alexandre Templier, president and cofounder of the Quinten Group.
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PARIS—The Quinten Group, an artificial intelligence/machine learning (AI/ML) services and products company, recently announced the launch of a new spin-out company, Quinten Health, an offering for global, integrated analytical services and tools development.
“While healthcare has been the major focus for Quinten so far, it was time to gear up and specialize as a genuine HealthTech company, serving and promoting synergies between drug developers, care providers, and public health decision makers through artificial intelligence and machine learning solutions developed with and for them,” stated Alexandre Templier, president and cofounder of the Quinten Group.
Quinten Health’s AI-based technologies will reportedly enable earlier and better diagnosis of rare diseases, drug response profiling, weak safety signals identification, optimal and precision treatment pathways, and the augmentation and rationalization of critical medical decisions at the point of care.
The Quinten Group has launched a new spin-out company, Quinten Health, to offer integrated analytical services and tools development
According to Billy Amzal, CEO of Quinten Health, “Quinten has been a French pioneer in actionable data science since 2008. Back then, being a pure player in machine learning/AI made sense, regardless of the industry to focus on. Nowadays, and more than ever in healthcare, interpretable data science has to rely on deep and hands-on knowledge of data to analyze. This is why Quinten spun off a dedicated team of data scientists and biomedical experts, specializing in real-world healthcare data and combining backgrounds such as pharmaco-epidemiologists, [and] public health or clinical experts. Technologies aiming at augmenting care have to be designed and developed with care providers from the start.”
Quinten Health incorporates a mix of 50 data scientists, data engineers, and biomedical and digital health experts. The team is aiming for impactful and interpretable healthcare data science.
“One structural difference is that Quinten Health develops AI/ML technologies for public health agencies, healthcare providers and industry, and masters in real-world data science,” said Amzal. “Serving and interfacing with those three [groups] (which are often siloed one from each other) allows us to unlock value from real-world data to all three.”
“For example, being connected to hospitals and developing regulatory-grade AI-based tools for evidence synthesis in health agencies makes us better placed to design solutions for industry which can be applied in care practice, or which align with regulatory standards,” he continued. “Another difference is that our analytical technologies, such as our Q-Finder for responders identification and progressors profiling, are by design interpretable and actionable by clinicians.”
Quinten Health is currently working on a product pipeline that includes precision oncology solutions, universal and General Data Protection Regulation (RGPD)-compliant hospital data networks, and natural language processing (NLP)-based medical literature analysis.
“Our pipeline includes: custom-made solutions that leverage NLP to automate literature review and evidence synthesis; dedicated machine learning algorithms based on real-world data for earlier and better disease diagnosis, to be used by industry or at point of care; and a platform encompassing a suite of algorithms to hypothesize and confirm new indications for existing drugs (repositioning or repurposing), integrating literature data on disease pathways and mechanisms of action with large real-world data processed by state-of-the-art NLP or pharmaco-epidemiological methods,” explained Amzal.”These products have been identified as critical unmet needs for patient care, [and could solve] some of the key pain points of industry, physicians, and health agencies.
“Actionable AI/ML is fascinating for its (scalable) potential to augment physicians’ practice and impact on patients, and to generate very fast return on investment, for patients and all decision makers serving patients.”
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