Background, Issue Addressed
Cancer remains a major global public health issue , with millions of new cases and deaths each year. Despite significant advances, a key obstacle persists: the difficulty of specifically targeting tumor cells without affecting healthy tissue. This limitation manifests itself notably through “on-target off-tumor” toxicities, where targets expressed by both tumors and certain normal tissues lead to often severe adverse effects. Traditional chemotherapies exemplify this problem due to their lack of specificity, resulting in significant systemic toxicity. Targeted therapies and immunotherapies, while having improved clinical outcomes, remain limited by targets that are not strictly tumor-specific, leading to dose-limiting toxicities, treatment interruptions, and, in some cases, patient ineligibility. There is therefore a critical need to develop more precise approaches capable of effectively distinguishing tumor tissue from healthy tissue. In this context, the project aims to develop the protein engineering platform of the company 9bio Therapeutics (9bio), based on computational and structural biology approaches, to design anticancer therapies that are conditionally activated within the tumor microenvironment, thereby improving the selectivity, safety, and efficacy of treatments.
Innovative aspect of the product, practicality, technology, or process
The project is based on a protein engineering platform that integrates computational modeling and AI-assisted structural biology, designed to exploit tumor-specific molecular signatures. These include mutations in key proteins involved in tumor progression, alterations in the tumor microenvironment, and aberrant glycosylation profiles (sugar modifications), enabling more precise discrimination of tumor tissues. Unlike traditional structural prediction approaches, the platform incorporates the local biochemical context and subtle variations in targets to predict the behavior of protein interactions under non-standard tumor conditions. This capability enables the design of biomolecules whose activity is modulated by these contextual characteristics, thereby improving the specificity of target-ligand interactions. The technology enables the development of therapeutic candidates with activity that is conditionally activated in tumors, applicable to several classes of molecules, including antibodies and antibody-drug conjugates (ADCs). It also optimizes the stability, solubility, and manufacturability of the candidates, facilitating their progression to clinical trials. This approach paves the way for a new generation of precision cancer therapies, combining greater selectivity, efficacy, and developmental robustness compared to conventional approaches.
Project Impacts
Description of the Strategic Impact of the Innovation on the Development of the Partner(s)
The development of this platform is a major strategic driver for 9Bio, strengthening its competitive edge in the field of precision cancer therapies. From a competitive standpoint, this innovation positions the company in the fast-growing segment of next-generation antibody-drug conjugates (ADCs). It enables the development of proprietary, high-value-added active ingredients, while improving the efficiency of R&D cycles and the translational success rate. The project also supports a transformative transfer of technologies and expertise between 9Bio and the CCTT, particularly in protein modeling, structural and computational biology, artificial intelligence, and the engineering of biomolecules sensitive to the tumor microenvironment. This collaboration sustainably strengthens the innovation capacity and scientific productivity of both partners. For the CCTT, the project consolidates applied expertise in the preclinical development of complex biologics, increases its capacity to support advanced biopharmaceutical projects, and fosters the development of highly qualified personnel. Beyond technological development, the data generated served as a foundational proof of concept that helped secure additional collaborations. They have facilitated the engagement of international partners involved in the co-development of therapeutic antibodies and ADCs, while accelerating ongoing programs. These results also strengthen the platform’s credibility in the context of future private capital raises and support the company’s funding and growth initiatives.
Description of the new skills acquired by the partner(s) in innovation management
Impact on internal innovation capacity, impact of the partnership on R&D expertise, etc.
The project will enable 9Bio and TransBIOtech to significantly strengthen their innovation management capabilities. The collaboration will promote the adoption of structured practices that integrate applied research, experimental validation, and industrial development constraints, thereby improving the ability to manage complex technology projects with a high degree of uncertainty. 9Bio will develop a deeper understanding of innovation approaches based on artificial intelligence applied to protein engineering, including the integration of multidimensional data, the prioritization of candidates, and decision-making under conditions of uncertainty. Exposure to advanced methodologies from the academic community will also help optimize internal R&D processes by promoting shorter, iterative, and value-driven cycles. For its part, the CCTT will strengthen its ability to align its scientific expertise with industrial needs, particularly in terms of technology transfer and support for commercialization. The partnership will help establish effective collaboration mechanisms, including joint management of risks, timelines, and deliverables. Overall, the project will increase the partners’ internal capacity for innovation by consolidating complementary expertise, improving R&D productivity, and fostering the emergence of a culture of collaborative, sustainable innovation focused on tangible outcomes.
The project includes the validation of several therapeutic candidates derived from the platform, including a tumor microenvironment-dependent anti-PD-L1 antibody. It will generate key data (binding, biological anticancer activity) to support entry into regulatory development. This approach, which combines modeling with targeted validation, helps reduce unnecessary testing and the use of experimental resources, thereby contributing to more sustainable R&D.
The development of this platform is a major strategic driver for 9Bio, strengthening its competitive edge in the field of precision cancer therapies. From a competitive standpoint, this innovation positions the company in the rapidly growing segment of next-generation antibody-drug conjugates (ADCs). It enables the development of proprietary, high-value-added active ingredients, while improving the efficiency of R&D cycles and the translational success rate. The project also supports a transformative transfer of technologies and expertise between 9Bio and TransBIOtech, particularly in protein modeling, structural and computational biology, artificial intelligence, and the engineering of biomolecules sensitive to the tumor microenvironment. This collaboration sustainably strengthens the innovation capacity and scientific productivity of both partners. For the CCTT, the project enhances its expertise in the development and validation of biomolecules, increases its capacity to support advanced biotech projects, and contributes to the training of qualified personnel. The data generated also served as proof of concept for establishing new collaborations. They facilitated the engagement of international partners involved in the co-development of therapeutic antibodies and ADCs, while accelerating ongoing programs. These results bolster the platform’s credibility for future private capital raises and support the company’s funding and growth initiatives.
Commitment to Sustainable Development
The project contributes to sustainable development primarily by improving human health and reducing the side effects associated with cancer treatments. By increasing the specificity of therapies, the platform will make it possible to reduce the overall dose of drugs required, thereby lowering the toxic burden on patients and the environmental impact associated with pharmaceutical production. The design of more effective biomolecules would also help reduce treatment failures and prolonged hospitalizations, thereby optimizing the use of healthcare resources. From a scientific and industrial perspective, the use of advanced computational approaches limits the need for large-scale experimental cycles, thereby reducing the use of biological materials, reagents, and animal models. Finally, the project promotes more personalized and inclusive medicine, potentially broadening access to innovative treatments for populations currently excluded for safety reasons, thereby contributing to health equity.
The winner will be announced at the gala on November 26, 2026.
For more than 45 years (since 1978), the Association for the Development of Research and Innovation in Quebec (ADRIQ) has played a central role in Quebec’s innovation ecosystem.
ADRIQ's mission is to foster innovation in order to enhance Quebec's competitiveness.
We congratulate our researchers Marie-Eve Janelle and Frédéric Couture, as well as their team, on this collaborative project.
