DeepStone Biosciences Files IPO Prospectus: Leveraging AI and Neoantigen Platforms to Pioneer Personalized Cancer Vaccines

According to the latest 2020 global cancer burden data released by the International Agency for Research on Cancer (IARC) of the World Health Organization, there were 4.57 million new cancer cases and 3 million cancer deaths in China in 2020. As a country with the world’s largest population, China ranks first globally in both the number of new cancer cases and cancer-related deaths.

To address the challenge of cancer, conventional therapies such as surgery, radiation, and targeted therapy are commonly employed. However, these traditional approaches have limitations, including high risks of recurrence, metastasis, drug resistance, and collateral damage to healthy cells. The emergence of immunotherapy offers a solution to these pain points. According to Frost & Sullivan data, the market size of immuno-oncology products in China is projected to grow from RMB 1.3 billion in 2021 to RMB 10.2 billion in 2023, representing a compound annual growth rate (CAGR) of 181.5%. By 2030, the market is expected to reach RMB 58.4 billion, with a CAGR of 28.3% from 2023 to 2030.

Neoantigen immunotherapy and cancer vaccines have emerged as new frontiers in immunotherapy, with leading international biopharmaceutical companies such as Moderna and BioNTech actively entering the field; some of their pipelines have already advanced to Phase III clinical trials.“At this critical juncture, if domestic companies fail to establish a presence in this sector, we will find ourselves at a significant disadvantage once competitors gain traction over the next couple of years. Chinese research teams have amassed substantial scientific expertise, and many of the current weaknesses exhibited by international competitors happen to be our areas of strength. This presents an excellent opportunity for us to leapfrog the competition,” Professor Shi Yi, Founder and President of Depushi Biotechnology (hereinafter referred to as “Depushi”), told VCBeat New Medicine.

Depu Stone is a biotechnology company driven by IT+BT technologies, dedicated to the field of cancer immunotherapy and focused on the independent research and development of personalized therapeutic tumor vaccines. It was founded by Dr. Shi in 2022.

Dr. Shi earned his Ph.D. from the Alberta Machine Intelligence Institute (Amii) at the University of Alberta, the birthplace of AlphaGo, under the supervision of Dale Schuurmans, a Fellow of the Royal Society of Canada and a leading expert in machine learning, and Professor Guohui Lin, a renowned scholar in bioinformatics. He completed his postdoctoral training at the Department of Molecular and Computational Biology, founded by Michael Waterman, a Fellow of the National Academy of Sciences and widely regarded as the father of computational biology, at the University of Southern California. His research primarily focuses on machine learning and computational biology, including studies on the correlation between 3D genome architecture and cancer, neoantigen-based cancer immunotherapy, personalized tumor mRNA vaccines, discovery of clinical biomarkers, early disease prediction, and single-cell analysis of tumor clonal evolution.

Professor Shi has presided over multiple national and provincial/ministerial-level projects, including the Key International Cooperation Project of the Ministry of Science and Technology, the Key Special Project on Artificial Intelligence of the Shanghai Municipal Science and Technology Commission, the Young Scientists Fund of the National Natural Science Foundation of China, and the Pujiang Talent Program. He has been invited by many internationally renowned universities and research institutions, such as Georgia State University (USA), The Chinese University of Hong Kong, Kyoto University (Japan), and the Japanese Cancer Association, to deliver academic keynote addresses.

Throughout Professor Shi’s extensive and distinguished research career, what left the deepest impression on him was not his numerous achievements, but rather two “setbacks” he encountered along his scientific journey.

His first “setback” occurred during his doctoral studies. At the time, he was working on applied research topics in computational biology and bioinformatics, whereas his supervisor, Academician Schuurmans, was an expert in artificial intelligence with a focus on machine learning and computational theory.

“At first, I was actually a bit confused because my advisor’s research area did not align closely with mine; we were both working in areas outside our respective expertise.”“However, through our weekly exchanges, he would first ensure I thoroughly understood the biological issues at hand. He then helped me review and reverse-engineer key mathematical formulas, ultimately working with me to effectively model several critical biological problems into computational frameworks. Step by step, we tackled the most challenging aspects of the mathematical derivations. This experience profoundly impacted me. Since then, whether teaching students from diverse disciplines or collaborating with cross-functional colleagues after starting my own venture, I have taken a more proactive approach to exploring unfamiliar interdisciplinary fields. Only by achieving a deep understanding of each component within these intersecting domains can one generate truly valuable insights,” Professor Shi told VCBeat New Medicine.

The second event occurred after Professor Shi returned to China. Adhering to the consistent philosophy of scientific research, Professor Shi joined a university research institute upon completing his studies abroad and commenced research in the field of AI plus 3D tumor genomics.“To be honest, at that time, almost no one in the international scientific community was combining 3D genomics with cancer research. I myself did not know how significant a role 3D genomics might play in tumor models, or whether there was even an association between the two.”

Through extensive research and analysis, Professor Shi’s team ultimately discovered a strong association between the two at the pan-cancer level. Leveraging chromatin conformation capture technology (Hi-C), the research team constructed 3D genome models to elucidate the regulatory mechanisms of numerous oncogenes within the 3D genome, thereby facilitating improved screening for tumor biomarkers and neoantigens.

He remarked, “In some interdisciplinary fields, we can uncover intriguing patterns through careful consideration, validation, and big data analysis.”

Today, Depu Stone’s core technology is derived from the scientific achievements previously discovered by Professor Shi Yi’s team in the IT+BT field.By leveraging multidisciplinary integration and technological innovations across cancer biomarker discovery, neoantigen prediction, 3D genomics, mRNA sequence design, clinical data, epigenetics, and customized AI algorithms, Depu Stone has rapidly established its own scientific and technical barriers, thereby enhancing the success rate of project R&D.

Under the leadership of the team,Currently, Depu Stone has established an mRNA development platform (neoantigen immunotherapy technology platform), an algorithm development platform, and a 3D genomics drug development platform.

Notably, Depu Shi leverages its mRNA development platform to address the three core challenges currently facing the industry in mRNA vaccine development.

First, the sequence design of mRNA is the most critical core issue.Taking the S protein of the novel coronavirus as an example, if all possible mRNA sequences corresponding to its amino acids were enumerated, there would be 2.4 x 10^632 types of mRNA that could encode the S protein,“We need to transform this complex challenge into a mathematical problem and leverage our expertise in computational biology to solve it. However, most companies currently prefer to validate and address such issues through experimental approaches. In fact, tackling the problem from a computational perspective can help avoid many detours.”

The second pain point is the issue of mRNA modification.mRNA itself possesses inherent immunogenicity that can lead to adverse effects, causing T cells to attack cells that should not be targeted. This phenomenon needs to be controlled through mRNA modification. “Regarding mRNA modification, the industry has not yet accumulated extensive data; Depu Shi will monitor and refine its approach by reviewing publicly available literature.”

The third pain point is the delivery of mRNA.mRNA is inherently unstable and susceptible to degradation by nucleases in the body; therefore, the development of efficient and non-toxic delivery systems is key to the success of mRNA vaccines. Through independent R&D and external collaborations, Depu Stone is actively developing suitable delivery formulations. “We are currently conducting preclinical studies with at least three CRO companies.”

Overall, DepuShi’s mRNA development platform leverages machine learning algorithms and 3D genomics technology to optimize codon combinations within mRNA molecules. This approach enhances mRNA stability, extends its intracellular half-life, and increases ribosomal affinity, ultimately improving the translation efficiency and total yield of proteins and peptides.

Based on this platform,Currently, Depu Shi has established in-house R&D projects for individualized tumor mRNA vaccines and shared tumor mRNA vaccines, as well as joint R&D initiatives focusing on non-LNP and LNP-based mRNA delivery systems, and collaborating with Atostek to build a comprehensive neoantigen vaccine database in Finland.Although the two great scientists Katalin Karikó and Drew Weissman have won this year’s Nobel Prize for their work on mRNA vaccine technology, there is still considerable room for improvement in mRNA technology, thereby truly benefiting a larger number of cancer patients.

In addition, Depu Stone’s other two technology platforms are also distinctive.

Algorithm Development PlatformKey features include customized feature engineering, sparse learning (classification prediction models based on feature selection), and the integration of state-of-the-art supervised and unsupervised learning algorithms. This platform provides algorithm development and consulting services for the field of computational biology, and can also develop diagnostic methods or products for complex diseases.

3D Genomics Drug Development PlatformBy elucidating the three-dimensional structure and regulatory mechanisms of the genome, this approach provides new perspectives and methodologies for deciphering disease mechanisms, drug development, personalized medicine, and pharmacotherapy, with applications in industrial drug discovery and target identification.

However, 3D genomics research involves complex experimental techniques and data analysis methods. The data generated by 3D genomic sequencing and imaging technologies are vast and intricate, requiring advanced analytical and interpretative approaches. This field demands highly skilled personnel and sophisticated equipment, and currently, research progress and knowledge accumulation are largely confined to academic and research institutions. Furthermore, due to the need for interdisciplinary collaboration and substantial expertise, it is difficult for general commercial companies to enter this domain.

Depu Shi applies its core technologies in machine algorithms and 3D genomics, developed for personalized therapeutic cancer vaccines, to fields such as gene therapy, synthetic biology, vaccines, prediction of complex diseases, drug target development, and protein-protein interactions. The company adopts a technology platform model to pursue business strategies including co-development, licensing, and contract research of its pipeline assets.

Strong technologies and application scenarios naturally attract investor interest. In an interview, Professor Shi remarked, “We are currently discussing the company’s first round of market-oriented financing, with several investment institutions already in active discussions.”

Upon completion of this market-oriented financing round, Depu Shi will leverage its three major technology platforms built on IT+BT integration to prioritize the advancement of cancer neoantigen mRNA vaccine projects, including personalized neoantigen mRNA vaccines, personalized neoantigen peptide vaccines, shared neoantigen mRNA vaccines, and shared neoantigen peptide vaccines.

It is understood that due to high technical barriers, the number of enterprises capable of developing tumor vaccines is currently very limited. Furthermore, the personalized nature of tumor vaccines means that the existing number of R&D companies falls far short of market demand. Although several domestic immunotherapy biotechnology companies have laid out strategies for neoantigens, a shortage of talent with interdisciplinary backgrounds in biology and artificial intelligence has constrained neoantigen prediction and presentation technologies, resulting in delayed clinical outcomes. Leveraging the founder’s prior interdisciplinary expertise and the team’s multidisciplinary coverage, Depu Stone is poised to achieve rapid advancement and overtake competitors.

Regarding future development, Professor Shi stated,“Following the completion of its first round of market-oriented financing, Depu Shi will rapidly advance investigator-initiated trials (IITs), with IITs expected to be launched and progressed in 2024, and an Investigational New Drug (IND) application anticipated one year thereafter.”We look forward to Depu Shi bringing accessible, personalized cancer neoantigen immunotherapy—“one patient, one drug”—to patients soon.