Context, Problem Addressed
Cancer remains a major global public health challenge, with millions of new cases and deaths each year. Despite significant advancements, a central obstacle persists: the difficulty in specifically targeting tumor cells without affecting healthy tissues. This limitation is notably manifested by "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 issue due to their lack of specificity, resulting in significant systemic toxicity. Targeted therapies and immunotherapies, while having improved clinical outcomes, remain limited by non-strictly tumor-specific targets, 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 tissues from healthy tissues. In this context, the project aims to develop the protein engineering platform of 9bio Therapeutics (9bio), based on computational and structural biology approaches, to design anti-cancer therapies with conditional activation in the tumor microenvironment, thereby improving the selectivity, safety, and efficacy of treatments.
Innovative Aspect of the Product, Practice, 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 finer discrimination of tumor tissues. Unlike classical structural prediction approaches, the platform integrates the local biochemical context and subtle target variations to predict the behavior of protein interactions under non-standard tumor conditions. This capability allows for the design of biomolecules whose activity is modulated by these contextual characteristics, thereby enhancing the specificity of target-ligand interactions. The technology enables the development of therapeutic candidates with conditionally activated activity in tumors, applicable to several classes of molecules, including antibodies and antibody-drug conjugates (ADCs). It also optimizes the stability, solubility, and manufacturability of candidates, facilitating their progression to clinical stages. This approach paves the way for a new generation of precision anti-cancer therapies, combining improved selectivity, efficacy, and developmental robustness compared to conventional approaches.
Project Impacts
Description of the Strategic Impact of Innovation for the Development of the Partner(s)
The development of this platform represents a major strategic lever for 9Bio, strengthening its differentiation in the field of precision anti-cancer therapies. Competitively, this innovation positions the company in the rapidly growing segment of next-generation antibody-drug conjugates (ADCs). It enables the development of high-value proprietary assets while improving the efficiency of R&D cycles and the translational success rate. The project also supports a structuring 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 durably 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 promotes the development of highly qualified personnel. Beyond technological development, the generated data served as a structuring proof of concept that enabled securing additional collaborations. They 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 for future private capital raises and support the company's financing and growth initiatives.
Description of New Competency Acquisitions in Innovation Management by the Partner(s)
Impact on Internal Innovation Capacity, Impact of the Partnership on R&D Expertise, etc.
The project will significantly strengthen 9Bio's and TransBIOTech's competencies in innovation management. The collaboration will foster the adoption of structured practices integrating applied research, experimental validation, and industrial development constraints, thereby enhancing the ability to manage complex technological projects with high uncertainty. 9Bio will develop a better mastery of AI-based innovation approaches applied to protein engineering, including the integration of multidimensional data, candidate prioritization, and decision-making under uncertain conditions. Exposure to advanced methodologies from the collegiate academic environment will also optimize internal R&D processes, promoting shorter, iterative, and value-oriented cycles. For its part, the CCTT will strengthen its capabilities to align its scientific expertise with industrial needs, particularly in technology transfer and support for commercialization. The partnership will contribute to structuring effective collaboration mechanisms, including joint management of risks, timelines, and deliverables. Overall, the project will increase the partners' internal innovation capacity by consolidating complementary expertise, improving R&D productivity, and fostering the emergence of a collaborative, sustainable, and results-oriented innovation culture.
The project includes the validation of several therapeutic candidates derived from the platform, including an anti-PD-L1 antibody with tumor microenvironment-dependent activation. It will generate key data (binding, biological anti-cancer activity) to support entry into regulatory development. This approach, combining modeling and targeted validation, reduces unnecessary trials and the use of experimental resources, thereby contributing to more sustainable R&D.
The development of this platform represents a major strategic lever for 9Bio, strengthening its differentiation in the field of precision anti-cancer therapies. Competitively, this innovation positions the company in the rapidly growing segment of next-generation antibody-drug conjugates (ADCs). It enables the development of high-value proprietary assets while improving the efficiency of R&D cycles and the translational success rate. The project also supports a structuring 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 durably strengthens the innovation capacity and scientific productivity of both partners. For the CCTT, the project reinforces its expertise in biomolecule development and validation, increases its capacity to support advanced biotech projects, and contributes to the training of qualified personnel. The generated data also served as a 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 strengthen the platform's credibility for future private capital raises and support the company's financing and growth initiatives.
Commitment to Sustainable Development
The project contributes to sustainable development primarily through the improvement of human health and the reduction of side effects associated with anti-cancer treatments. By increasing the specificity of therapies, the platform will enable a reduction in the overall dose of necessary drugs, thereby decreasing the toxic burden on patients and the environmental impact associated with pharmaceutical production. The design of more effective biomolecules would also lead to a decrease in therapeutic failures and prolonged hospitalizations, optimizing the use of healthcare resources. From a scientific and industrial perspective, the use of advanced computational approaches limits the need for extensive experimental cycles, thereby reducing the use of biological materials, reagents, and animal models. Finally, the project promotes more personalized and inclusive medicine, potentially expanding access to innovative treatments for populations currently excluded for safety reasons, thereby contributing to health equity.
The laureate will be announced at the gala on November 26, 2026.
For over 45 years (since 1978), the Association for the Development of Research and Innovation of Quebec (ADRIQ) has played a central role in Quebec's innovation ecosystem.
ADRIQ's mission is to stimulate innovation to enhance Quebec's competitiveness.
We congratulate our researchers Marie-Eve Janelle and Frédéric Couture, as well as their team, for this collaborative project.
