DigiPath AI Secures Nearly RMB 100 Million in Series B1 Funding, Aims to Expand to 1,000 Hospitals by End of Next Year

 VCBeat has learned that Hangzhou Dipath Technology Co., Ltd. (hereinafter referred to as "Dipath") recently completed a financing round of nearly RMB 100 millionB1round of financing, led by Shenzhen Capital Group Co., Ltd. (hereinafter referred to as SCGC). It is understood that the funds raised in this round will be mainly used for comprehensive market promotion and product function optimization.

Including the Series B financing round in June this year, Dipath has completed two consecutive rounds of financing in less than three months.By 2020, the cumulative amount of financing had reached nearly RMB 200 million.

Founded in 2017, Dipath has remained committed to deepening its expertise in “AI + Pathology.” By leveraging fully self-developed AI algorithms to establish core competitiveness, the company has created multi-module AI-assisted diagnostic tools. Building on this foundation, Dipath offers a diverse portfolio of services, including cloud-based pathology storage, pathology information management, and remote pathology consultation/diagnosis. Its solutions comprehensively address all aspects of building digitalized and intelligent pathology departments, with a dedication to providing industry professionals with integrated informatics solutions for smart pathology departments.

Currently,Dipath has extended its services to 300 medical institutions., with positive user feedback. The funds from this round of financing will be used to accelerateDipath is implementing its product pipeline nationwide and continuously iterating and optimizing it, with a plan to expand its user base to 1,000 medical institutions by the end of next year. This initiative aims to better highlight the application value of its products and provide optimal services to pathologists.

With less than three years since its establishment, why has Dipath garnered significant favor from the capital market, and why has its user base experienced explosive growth? What value orientations of the company and the entire industry lie behind this phenomenon?

According to the report from the 2020 World Congress of Pathology, the global pathology market size is projected to rise from $30.3 billion in 2019 to $44.4 billion in 2024, representing a compound annual growth rate (CAGR) of 6.1% over the five-year period. In China specifically, Western Securities predicts that the potential market for the pathology industry currently exceeds RMB 30 billion.

The continuous expansion of the market size demonstrates the substantial demand within this industry. According to authoritative data, in 2018, there were approximately 9,600 licensed pathologists nationwide in China, a figure that severely deviates from the standard ratio of one to two pathologists per 100 hospital beds as mandated by the National Health Commission. Furthermore, since pathological diagnosis often serves as the definitive diagnosis guiding clinical treatment, pathologists bear significant responsibility and face a heavy workload. Statistics show that,A tertiary hospital's pathology department generates approximately 2,000 histopathology slides for processing each day., pathologists often need to spend considerable time and mental effort relying on experience to identify and assess diseased tissues under a microscope, roughly estimate their cell counts, and evaluate patients' cancer risk and grade.

The emergence of artificial intelligence has provided a breakthrough to this dilemma. In Yang Lin’s view, “current AI technology has matured. Compared with the frenzied hype in previous years, expectations for this technology have become more rational, which is beneficial for the entire pathology industry. Additionally, the state has provided substantial support for the application of AI in the field of pathology; therefore, its scale of development will continue to expand. Companies operating in this sector should remain patient.”

AI technology, particularly AI powered by deep learning, could make pathological examinations smarter and simpler. Yang Lin stated,“AI performs initial screening, referring only complex cases it cannot determine to physicians. This effectively reduces the physicians’ image review workload while improving diagnostic accuracy.”

Pathological AI leverages artificial intelligence algorithms to diagnose digitized pathology slides. By employing manual or automatic feature extraction methods, it extracts image features and constructs corresponding detection and analysis algorithms to classify and grade cells, thereby completing diagnostic tasks.

Currently, pathological AI has been applied to the analysis of diseases such as breast cancer, glioma, prostate cancer, and cervical cancer. Its applications mainly include the detection of nuclear features, diagnosis of benign and malignant conditions, cancer grading and classification, staining analysis, early screening, as well as the detection and analysis of blood smears, sputum smears, and urine sediments. 

To address the challenges in the current field of pathological diagnosis, including heavy workloads, staff shortages, and low efficiency, Dipath has proposedAn integrated intelligent solution meeting the digitalization needs of pathology departments, featuring a built-in AI pathology analysis system equipped with nearly 30 analytical modules covering various areas including histopathology (immunohistochemistry, H&E staining), cytopathology, and molecular pathology.

Guided by clinical practice needs and the industry’s overarching pain points, Dipath has conducted in-depth exploration across various domains and successfully developed a cloud storage solution with a high compression ratio.Pathology Planet (D-PathPlanet), High-Throughput Pathology-Assisted Diagnostic System D-PathAI, and China’s First Intelligent Microscope ZhiJie (D-CleverEye)and other products.

According to Yang Lin, these core products are built upon powerful artificial intelligence algorithm systems. By performing a series of procedures—including automated detection, rapid identification, precise segmentation, and efficient analysis of pathological images—they enhance the intelligence of pathological diagnosis, thereby enablingPathologists see faster, calculate most accurately, and think further ahead.

On the other hand, as the product processes large volumes of patient data during operation, information security is an indispensable consideration. Dipath attaches great importance to this aspect. By leveraging cutting-edge technological frameworks, we have established a rigorous protection network within the product to safeguard data security and patient privacy.

The rapid growth of a company is inseparable from the sincere collaboration of its team. Dipath boasts a highly skilled and professional talent pool. Among its nearly 100 members, 70% hold master’s or doctoral degrees, and all possess over 15 years of experience in fields such as technology R&D, core algorithms, digital pathology, and marketing and sales.

A highly professional and capable team is also a key factor attracting investment institutions to Dipath. A representative from SCGC stated, “Professor Yang Lin is a rare top-tier scientist at the intersection of medical imaging and artificial intelligence, as well as an entrepreneur with strong execution capabilities. The Dipath team he leads has already accumulated massive datasets and advanced algorithmic models that are ahead of the industry. The company can rapidly build AI-powered pathology analysis capabilities tailored to clinical scenarios, and has been among the first to gain regulatory approval and industry support. Dipath Technology is increasingly becoming the most trusted brand partner for multinational pharmaceutical companies, major domestic healthcare institutions, and leading cancer hospitals in their practical efforts toward the industrialization of artificial intelligence.”

In Yang Lin’s view, Dipath has entered a phase of rapid market expansion and will therefore focus its efforts on this segment in the future, andThe plan is to expand the number of product service coverage from the current 300 to 1,000 by the end of next year.

To achieve this goal, Dipath has already taken action by building and optimizing its sales team, laying a solid foundation for future market promotion.

Meanwhile, perfecting its product portfolio is also a top priority in Dipath's future strategic roadmap.

Currently, Dipath has developed nearly 30 analytical modules in its product portfolio, and is poised towill be completed by the end of next yearThis number increased to 40 sectors., thereby achievingComprehensive coverage from immunohistology to molecular pathology in remote research.

Guided by the value proposition of becoming the world’s most comprehensive provider of pathology solutions, Dipath has initiated data collection and preliminary R&D efforts and established collaborative partnerships with relevant medical institutions.

This funding round marks the first collaboration between Dipath and SCGC, holding extraordinary significance for both parties. From Dipath’s perspective, this partnership will help establish a competitive advantage in hospital engagement, laying a solid foundation for expanding its product coverage across China. From SCGC’s standpoint, this represents its inaugural investment in the “AI + Healthcare” sector, underscoring the immense growth potential of this field and signaling that it is likely to attract greater support and attention from the capital market in the future.

Shenzhen Capital Group Co., Ltd. (SCGC) was established in 1999 with capital from the Shenzhen Municipal Government, which also guided social capital investment. With a mission to discover and empower great enterprises, SCGC is committed to uncovering and nurturing innovative value. It has grown into a comprehensive investment group centered on venture capital. As of the end of May 2020, the total assets under management amounted to approximately RMB 350 billion, and it had helped 164 portfolio companies achieve public listings.