BostonGene was recently recognized with the “AI-based Drug Discovery Solution of the Year” award in the 8th annual AI Breakthrough Awards program, which drew more than 5,000 nominations from over 20 countries. The award highlights BostonGene’s work in applying artificial intelligence to oncology research and drug development.
BostonGene’s technology comes at a critical moment for oncology drug development, where rising costs and long timelines continue to challenge the industry. By mapping the molecular and immune landscapes of tumors, BostonGene’s system helps oncologists identify the most effective therapies for individual patients. At the same time, it offers drug developers critical insights into the factors that determine whether treatments succeed or fail.
Inside BostonGene’s precision medicine platform
BostonGene is positioning its technology infrastructure as the backbone of next-generation cancer care and drug development. Its AI-powered foundation model unifies clinical and biopharma applications within a single platform. The system integrates molecular profiling, immune and spatial profiling, and multimodal data analytics, supported by a CLIA-certified and CAP-accredited laboratory. This infrastructure enables use of assays such as whole exome and transcriptome sequencing, liquid biopsies, and digital pathology
The platform reflects the push for precision at scale, equipping drug developers to model outcomes, refine biomarkers, and accelerate therapy development, while clinicians gain individualized insights through digital twins. AI-driven analytics translate multimodal data into predictions that streamline trials, guide treatment, and link laboratory precision with computational power to advance personalized medicine.
Scaling through investment and reach
BostonGene’s trajectory has been marked by substantial investor confidence and strategic alliances that highlights the company’s role in reshaping cancer care. In 2019, the company secured $50 million in Series A financing from NEC Corporation, a deal that extended beyond capital. The partnership reflected a shared vision of harnessing artificial intelligence to advance cancer immunotherapy, laying the foundation for joint initiatives in precision medicine.
Momentum accelerated in 2022 with a $150 million Series B round, which valued BostonGene at several billion dollars and established its position among biotechnology’s emerging unicorns. The funding, led once again by NEC with support from additional investors, has enabled the expansion of development programs, clinical collaborations, and international operations.
Part of this growth strategy included the establishment of an office in Yerevan, Armenia, reinforcing BostonGene’s global footprint and providing a base for scaling its technical capabilities. With these milestones, the company has not only strengthened its financial position but also deepened its ability to deliver AI-driven solutions across diverse healthcare markets.
Advancing with research and collaboration
BostonGene has built its reputation not only on technology but also through a network of high-profile collaborations with leading cancer research centers and industry partners. The company’s AI-powered molecular and immune profiling solutions have been validated in joint studies with institutions such as Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Weill Cornell Medicine, Washington University, and Stanford University, among others. These collaborations have yielded landmark publications in top journals, including Nature Medicine, advancing the understanding of tumor biology and informing next-generation therapies.
BostonGene has joined forces with NEC Corporation and Japan Industrial Partners to launch BostonGene Japan, a Tokyo-based venture bringing AI-powered molecular profiling to cancer care. The partnership combines BostonGene’s biocomputational tools with NEC’s digital health infrastructure to accelerate drug development and expand access to personalized treatments in a market where cancer causes one in four deaths.
BostonGene’s AI patents
The following sections highlight patents that apply artificial intelligence to advance precision medicine. These cover AI-powered analysis of gene expression to map cell composition, fusion-specific cancer vaccines tailored to individual patients, and hierarchical machine learning for refined tumor categorization, each contributing to more accurate diagnostics and personalized treatment strategies.
AI-powered gene analysis for mapping cell composition
As precision medicine advances, researchers and clinicians increasingly rely on gene expression data to understand the cellular makeup of tissues. Traditional methods often use broad averages or simple models, which may overlook the detailed interactions among different cell types in health and disease. A more accurate approach to analyzing this data can provide clearer insights into cancer, immune response, and treatment outcomes.
U.S. Patent No. 11,587,642 describes a system that applies artificial intelligence to gene expression data in order to estimate the proportions of different cell types within a biological sample. The method processes RNA expression data using non-linear regression models to calculate percentages of specific cells such as T cells, B cells, and macrophages. By training the models on both simulated and experimental data, the system produces more reliable results than traditional approaches, enabling more precise analysis of complex tissue environments.
The patent, titled “Systems and methods for deconvolution of expression data,” was filed on March 29, 2022, and granted on February 21, 2023. The patent lists Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, and Boris Shpak as inventors.
Fusion-specific vaccines for personalized cancer immunotherapy
Developing effective cancer vaccines requires targeting tumor-specific genetic alterations. Traditional approaches focus on general tumor antigens, which may not capture patient-specific gene fusions driving disease. A fusion-specific vaccine library offers a way to match therapies directly to an individual’s genetic profile, improving precision and therapeutic potential.
U.S. Patent No. 11,904,002 describes methods for constructing and applying therapeutic fusion-specific vaccine libraries. The system identifies tumor-specific gene fusions from patient samples, determines binding potential with patient HLA alleles, and selects or constructs vaccines accordingly. This enables both library-based and de novo vaccine development, ensuring that even rare or unique gene fusions can be targeted. The approach supports a wide range of cancers, including melanoma, lung, breast, and colorectal cancers, as well as metastatic tumors.
The patent, titled “Construction and methods of use of a therapeutic cancer vaccine library comprising fusion-specific vaccines,” was filed on November 1, 2019, and granted on February 20, 2024. The patent lists Maksym Artomov, Feliks Frenkel, Igor Golubev, and Olga Zolotareva as inventors..
Hierarchical machine learning for molecular categorization
Accurate classification of tumors and other biological samples is essential for guiding precision medicine. Conventional diagnostic methods often treat expression data as a flat dataset, missing the layered biological relationships between molecular categories. A hierarchical machine learning approach instead mirrors biological taxonomy, using classifiers arranged in parent–child structures to refine categorization. This enables more precise identification of cancer subtypes and other disease states, improving diagnostic accuracy and treatment selection.
U.S. Patent No. 12,254,961 describes methods and systems for identifying candidate molecular categories from RNA expression data using a hierarchy of machine learning classifiers. Expression data from different gene sets are processed by classifiers aligned with corresponding molecular subcategories (e.g., adenocarcinoma, sarcoma), all nested under broader parent categories (e.g., solid neoplasms, breast cancer). Outputs from multiple classifiers are combined to identify the most likely molecular category for a given biological sample.
The patent, titled “Hierarchical machine learning techniques for identifying molecular categories from expression data,” was filed on December 4, 2021, and granted on March 18, 2025. The inventors are Nikita Kotlov, Zoia Antysheva, Daria Kiriy, Anton Sivkov, Aleksandr Sarachakov, Viktor Svekolkin, and Ivan Kozlov.
All three patents were represented by Wolf Greenfield & Sacks, P.C. with John Welch, Edward Gates, Jason Honeyman et al. listed on the application.
BostonGene: Patenting Activity
BostonGene’s global patent filings rose sharply in 2017, with 61 applications that highlighted the company’s early push to secure intellectual property for its AI-powered molecular and immune profiling technologies. That same year, a Nature Biotechnology study highlighted BostonGene’s work in defining tumor microenvironment types and combining them with tumor mutational burden to predict immunotherapy response, research that laid the foundation for its precision oncology platform.
BostonGene continued to build momentum in 2019 and 2020, filing 21 and 32 patents respectively, while forging high-profile collaborations. In January 2020, the company joined forces with Massachusetts General Hospital’s Vaccine and Immunotherapy Center to showcase the impact of its tailored treatment platform. By July, it partnered with NEC Corporation to bring its tumor profiling expertise into NEC’s AI-driven cancer trials, an alliance that was elevated in December 2021 into a global partnership aimed at accelerating BostonGene’s international expansion.
BostonGene: Top Legal Representatives
BostonGene’s patent portfolio is supported by a wide network of legal representatives, with Wolf, Greenfield & Sacks at the forefront of its IP strategy. Attorneys Kevin MacDonald, Daniel Rudoy, and Kylee Sullivan at Wolf Greenfield have guided much of this U.S.-based work. The firm is complemented by Mewburn Ellis LLP in Europe and Inaba Yoshiyuki in Japan, reflecting the company’s cross-regional approach to intellectual property protection.
BostonGene also works with Smart & Biggar in Canada and RnB IP in Australia, along with Sanford T. Colb & Co., Pizzeys, Murayama Yasushiko from Shiga International Patent Office, and Linda Liu & Partners, reflecting the range of firms handling its patent filings across different regions.
BostonGene: Top Technology Areas
BostonGene’s patent filings are heavily concentrated in bioinformatics (G16B), followed closely by healthcare informatics (G16H) and measuring or testing processes involving enzymes, nucleic acids, or microorganisms (C12Q). This reflects the company’s core focus on data-driven medicine, genomic analysis, and precision diagnostics. Electric digital data processing (G06F) also accounts for a substantial portion, highlighting the computational backbone supporting BostonGene’s AI-powered healthcare solutions.
Beyond these dominant categories, the portfolio extends into image or video recognition (G06V) and adaptation to climate change (Y02A), suggesting applications of its data technologies in broader contexts. Smaller shares in areas such as image data processing (G06T), material analysis (G01N), and specific therapeutic activities of chemical compounds (A61P) further showcase diversification.
