ProteinQure Secures $11M Series A to Advance First AI-Designed Peptide Therapeutic for Triple-Negative Breast Cancer
核心洞察
ProteinQure (搜索) raised $11 million in Series A funding led by Heron Rock Fund (搜索) to advance PQ203, a first-in-class AI-designed peptide-drug conjugate targeting triple-negative breast cancer (搜索).
The lead candidate PQ203 targets the sortilin receptor (搜索) overexpressed in solid tumors (搜索) and is designed for tumors resistant to topoisomerase I (搜索) inhibitors like Trodelvy.
A multicenter Phase 1 clinical trial is planned to begin in Q3 2025, enrolling 70-100 patients across renowned cancer centers including Princess Margaret, MD Anderson, and Yale.
ProteinQure (搜索) Inc., a Toronto-based biotechnology company pioneering computational peptide therapeutics, announced the completion of an $11 million Series A financing round to advance its lead AI-designed drug candidate into clinical trials. The funding, led by Tom Williams of Heron Rock Fund (搜索) with participation from Golden Ventures (搜索), Kensington Capital (搜索), and returning investors, brings the company's total funding to $16 million across seed and Series A rounds.
The proceeds will primarily support the initiation of clinical trials for PQ203, a first-in-class peptide-drug conjugate designed to treat triple-negative breast cancer (搜索) (TNBC (搜索)), while also advancing additional pipeline programs in neurology and nephrology.
Breakthrough AI-Designed Therapeutic
"With this financing, we're advancing what we believe to be the first AI-designed peptide therapeutic into the clinic. It's a defining moment for ProteinQure (搜索) and for the field," said Lucas Siow, CEO and co-founder of ProteinQure. The company's approach represents a significant milestone in the application of artificial intelligence to drug discovery and development.
PQ203 is engineered to target the sortilin receptor (搜索), which is overexpressed in many solid tumors (搜索), including TNBC (搜索). The drug candidate has been specifically developed for tumors that show resistance to topoisomerase I (搜索) inhibitors, such as antibody-drug conjugates like Trodelvy®. This targeting strategy is based on robust preclinical evaluation conducted in patient-derived xenograft models.
Clinical Trial Plans
The company plans to initiate a multicenter Phase 1 clinical trial in the third quarter of 2025, with enrollment of 70-100 patients across Canada and the United States. The trial will be conducted at world-renowned cancer centers, including Princess Margaret Cancer Centre, MD Anderson Cancer Center, and Yale Cancer Center.
This clinical milestone represents the culmination of ProteinQure (搜索)'s computational approach to peptide design, which utilizes their proprietary ProteinStudio™ platform. The platform integrates machine learning, structural biology, and atomic-level simulations to design therapeutic peptides using thousands of non-natural amino acids, enabling tissue-specific delivery and access to novel target classes.
Platform Technology and Future Applications
"We're witnessing the birth of a new drug class – AI-engineered peptide therapeutics – and ProteinQure (搜索) is at the forefront," said Tom Williams, who led the Series A round. Williams highlighted the company's approach to building proprietary data libraries and learning models as key advantages in an AI-driven drug discovery landscape.
The investor noted that ProteinQure (搜索) has demonstrated "true platform capabilities for designing non-canonical peptide therapeutics with exceptional specificity and drug-like properties" and has progressed "from concept-to-clinic with remarkable capital efficiency."
Beyond oncology, ProteinQure (搜索)'s platform technology has potential applications across multiple therapeutic areas. The company is developing pipeline programs in neurology and nephrology, leveraging their precision-designed peptides to deliver diverse payloads and access previously inaccessible targets across oncology, neurology, nephrology, and rare diseases.
The ProteinStudio™ platform's capability extends from cytotoxic payloads to RNA delivery, positioning the company to address a broad range of therapeutic challenges through programmable peptide medicines. This versatility underscores the potential impact of AI-driven peptide design in expanding the druggable target space and enabling new therapeutic modalities.