3 TechBio business models to watch
TechBio startups combine biology and digital technologies to generate and leverage biological data at scale. As they are fundamentally data-driven, they face several key challenges: a rapidly evolving environment, securing and monetizing data, ensuring the reproductibility of their models, and positioning themselves at the intersection of business and open science. They must therefore develop business models that address all of these challenges, from technology strategy to revenue generation.
In this article, Alcimed examines three promising French TechBio business models that have successfully raised significant funding over the past two years, reflecting strong investor interest.
Cure51: a platform for unlocking the value of biomedical data
Founded in 2022, Cure51 is a TechBio company aiming to build a database from the clinical and molecular profiles of “exceptional cancer survivors,” with the goal of developing treatments to combat the disease. To achieve this, Cure51 relies on an international network of more than 100 healthcare centers across over 40 countries, which has enabled the identification of more than 1,500 “exceptional survivor” patient profiles. In 2024, Cure51 notably conducted a clinical study approved by the NHS in the United Kingdom, in collaboration with Cambridge Hospital and seven other UK centers, to analyze the biological factors behind these extended survival outcomes.
Cure51’s development strategy is built around data collection: clinical information, biological samples, and multi-omics data from cancer survivors. The startup has then developed a platform based on computational modeling and artificial intelligence to identify biological markers associated with prolonged survival. The diversity of data sources and associated modeling enables Cure51 to adopt an integrative approach, combining in silico (AI-based), in vitro, ex vivo (patient-derived biological samples), and in vivo models (clinical research).
Although Cure51 is currently still focused on data collection, the company ultimately aims to implement two value-generation models. The first is based on establishing R&D partnerships with pharmaceutical and biotechnology companies, collaborating with labs to co-develop treatments or biomarkers based on its discoveries. This is already the case with Explicyte, a Bordeaux-based company that supports pharmaceutical and biotech firms in developing therapies for solid tumors and processes the samples collected by Cure51. The second is based on a licensing model, leveraging its proprietary technology and databases with major pharmaceutical players.
Cure51 therefore relies on a network of partners to build its proprietary database. The associated platform can then be commercialized through partnerships or licensing agreements. The company’s ambition is to develop a proprietary database to support its revenue model, with 10% of revenues redistributed to partner healthcare centers. Licensing would enable the generation of initial revenues before moving toward a longer-term and more capital-intensive partnership strategy. With this strategy in place, Cure51 successfully raised €15 million in seed funding in March 2024 from Sofinnova Partners, Hitachi Ventures, and Life Extension Ventures.
Bioptimus: generative AI applied to biology
Founded in 2023 and incubated by Owkin, Bioptimus aims to apply generative AI to the life sciences sector. Starting with an initial model trained solely on biological tissue images to detect cancer cells and anomalies with high precision, the company’s goal is to develop foundational AI models.
Bioptimus is thus training multimodal models on massive volumes of heterogeneous biomedical data. The objective is to design a model capable of understanding and simulating how a living organism functions in all its complexity. To achieve this, Bioptimus relies on several technological pillars:
- Proprietary, high-quality data obtained through partnerships with numerous laboratories and hospitals, as well as access to Owkin’s database;
- Computing infrastructure and advanced algorithms, made accessible through a partnership with Amazon Web Services, enabling model training without the need to build proprietary infrastructure.
For now, Bioptimus has chosen to release its initial models as open source to contribute to the scientific community and build its reputation. These models will remain open source for the entire academic ecosystem. Subsequently, multimodal models will be monetized through two channels:
- Custom research partnerships with industry: Bioptimus aims to collaborate with pharmaceutical, biotech, and even companies from other sectors (cosmetics, food industry) to apply its AI models to their specific challenges. The company will position itself as an R&D service provider, leveraging its platform on client data.
- Cloud-based model access: similar to solutions such as OpenAI’s ChatGPT, Bioptimus plans to offer access to its models via APIs or cloud services. Developers, researchers, and companies will be able to call Bioptimus models on demand and integrate them into their own applications or workflows, paying on a usage basis.
Bioptimus thus positions itself at the intersection of open science and monetization. To generate early revenues, monetizing its models via the cloud appears essential and would enable the creation of recurring revenue streams.
The strategy implemented by Bioptimus has already enabled the company to raise €76 million since 2024 across two funding rounds: an initial €35 million seed round from Sofinnova Partners, Bpifrance, Cathay Innovation, Hummingbird, NJF Capital, and Frst, followed one year later by a €41 million round from Cathay Innovation, Bpifrance, Andera Partners, Sofinnova Partners, Hitachi Ventures, Sunrise, and three U.S.-based funds.
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Orakl Oncology: AI for cancer modeling
Founded in 2023, Orakl Oncology is a startup leveraging AI and experimental biology to model cancers in patients. Originating from the Gustave Roussy Institute, the company focuses on two of the most aggressive gastrointestinal cancers: colorectal cancer and pancreatic cancer.
The company’s technical strategy is built on three main pillars:
- Models based on patient-derived tumor avatars: Orakl creates an avatar for each patient—a biological model representing their tumor, primarily in the form of tumor organoids. These organoids can be exposed to various compounds in the lab to observe responses.
- Integration of patient data and artificial intelligence: beyond organoids, Orakl integrates multiple real-world clinical data points from patients. By combining these data with in vitro test results on the avatar, and using machine learning algorithms, the company builds predictive models of tumor response. The goal is to develop an AI engine capable of anticipating which patients will respond to which treatments.
- Proprietary platforms: the technological platforms associated with tumor avatar models and AI enable Orakl Oncology to build and leverage its own biobank.
As with Cure51, Orakl Oncology’s revenue model is designed to rely on partnerships with pharmaceutical companies and on making its technological platform available through licensing or co-development agreements. On the partnership side, Orakl offers to collaborate with drug developers by testing their compounds on collections of tumor avatars representative of target patient populations. On the second front, companies could access its technological platforms under licensing agreements to conduct their R&D activities.
From a short-term revenue generation perspective, Orakl will primarily need to rely on licensing its technology before expanding into partnerships and co-development initiatives.
With this strategy, the startup has completed two successive funding rounds: an initial €3 million round in October 2023 from Speedinvest, HCVC, and Verve Ventures, followed by an €11 million round in December 2024 from Singular, supported by Bpifrance.
These three TechBio companies rely on similar models: collecting data to train modeling algorithms, with the ultimate goal of monetization through partnerships or R&D services. Licensing provides them with short-term, relatively low-risk revenue, enabling a subsequent shift toward co-development—longer, riskier, but offering greater revenue potential.
These business models have enabled the three startups to raise a total of €105 million since October 2023, in a context where the number and size of funding rounds are declining—demonstrating strong investor interest and the relevance of their strategies.
Building a robust business model is a key step toward successful fundraising. At Alcimed, we support you on these topics. Don’t hesitate to contact our team!
About the author,
Pierre, Consultant in Alcimed’s Innovation and Public Policy team in France