WeDoctor-Backed Unicorn Uniyizhe Files IPO Prospectus Highlighting AI-Powered Clinical Trial Platform Serving Nearly 200,000 Medical Experts

In recent years, thanks to the sustained development of the innovative drug market, China’s clinical trial industry has ushered in unprecedented opportunities for growth.

As the approval and regulatory framework continues to be optimized, clinical trial processes are retained with greater efficiency, and data management technologies advance innovatively, the value that domestic enterprises derive from clinical trials is increasingly coming to light. These factors have further propelled the rapid expansion of China’s clinical trial market.

Against this backdrop, improving the efficiency of clinical trials and assisting researchers in managing clinical trial operations have become topics of common interest within the industry. Leveraging its advantages in enhancing the quality of clinical research and data utilization, digital technology has emerged as a key means to reduce costs and improve efficiency in clinical trial operations.

As a leading digital clinical research service provider in China, Wei Tong Yi Zhe has delivered high-quality digital and intelligent academic research services to nearly 200,000 medical experts through its integrated digital-intelligence research platform.

VCBeat was honored to invite Ms. Wei Tian, Founder and CEO of WeiTong YiZhe, to discuss the opportunities and challenges facing digital clinical trial operations management under the new macro environment, as well as WeiTong YiZhe’s practical journey in building its integrated intelligent research platform.

In the interview, Wei Tian first emphasized that the value of AI technology lies in assisting researchers in completing clinical studies more quickly and efficiently.

Based on this, the company has structured and standardized the work processes across all phases of clinical research by referencing relevant domestic and international regulations, guidelines, and standards. Leveraging technologies such as big data, cloud computing, and artificial intelligence, the integrated digital-intelligent research platform enables intelligent extraction and entry, cleaning and analysis, as well as visualized statistical reporting and display of massive datasets, thereby achieving digital and intelligent management of clinical trials and enhancing the quality and efficiency of research.

She shared a real-world study case targeting PD-1 therapy for advanced EGFR-positive NSCLC. Leveraging an integrated digital-intelligence research platform, the research team was able to precisely and efficiently screen for target patients, significantly reducing the costs and time associated with patient recruitment. Meanwhile, through AI-driven patient interactions, WeiTongYiZhu helped the research team collect patient data that are difficult to accurately assess using conventional methods, such as patient-reported outcomes, functional status, and survival conditions. These services and tools safeguard the smooth conduct of clinical trials and provide a “material foundation” for cost reduction and efficiency enhancement in clinical research.

It was revealed that the project leveraged an integrated digital-intelligence research service platform, achieving an approximately 60% increase in overall efficiency and a roughly 52% reduction in research costs.

The “Unimind-Gezhi” large language model plays a pivotal role in data cleaning, analysis, and deep mining. This model can automatically identify outliers within datasets. Leveraging its capabilities for in-depth data mining and analysis, researchers can also conduct timely project quality control, detect potential risks, issue early warnings, and mitigate data errors during clinical trials.

Beyond the underlying technological applications, refined operational management of clinical trials is also critically important.

At the inception of nationwide multi-center clinical trial projects, WeiTongYiZhe proactively leverages advanced digital technologies to conduct comprehensive, forward-looking analyses of human, material, and time resources. Powered by robust big data algorithms, the platform can predict project execution risks at each investigative site in advance and formulate operational contingency plans, thereby enabling precise and rational resource allocation.

During the project execution phase, Weiyitongzhe has established a robust data monitoring and analytics platform capable of conducting real-time, in-depth analysis of data collected from various research centers. By continuously monitoring and deeply analyzing key metrics such as patient enrollment progress, data quality, and protocol deviations, the platform enables prompt issue identification and the immediate implementation of corrective measures.

Throughout the project lifecycle, the platform can also leverage in-depth analysis of historical project data to build precise risk prediction models, identify risk factors affecting project progress, quality, and compliance across the entire process, and formulate effective mitigation strategies. Meanwhile, Weiyi Yizhe employs blockchain technology to encrypt and distributively store research data, ensuring data security and immutability, thereby further strengthening project quality and compliance management.

Two Sides of the Same Coin: The Flip Side of Opportunity Is the Significant Challenge Digitalization Poses to Clinical Trial Operations Management.

First, there are challenges in data security.

In the application of digital technologies to clinical trials, data security is of paramount concern. Each clinical trial involves the transmission, storage, and processing of vast amounts of research data via digital platforms. These datasets contain sensitive information, including patients’ personal identities and health status, as well as corporate trade secrets. To address these risks, we have implemented robust platform security measures and comprehensive data protection strategies.

In addition to improving efficiency and reducing client costs, digital clinical trial services must strictly adhere to the red line of compliance and regulatory requirements. Weiyi Tongche consistently upholds the principles of safeguarding platform data security and protecting personal information and trade secrets.

In response, VCBeat has invested substantial resources in the independent research and development of its encryption systems. In addition to implementing customized encryption tailored to the characteristics of clinical trial data, the system has established rigorous data access control mechanisms. Only authorized personnel can access and decrypt data after undergoing identity verification and obtaining authorization within specific scenarios. Furthermore, the system maintains comprehensive logs of all data access and operations to facilitate subsequent traceability and auditing.

In addition to technical safeguards, Weiyitongzhe has also established a data security management system, ensuring the protection of personal information and data security through rigorous control of security standards across all stages of data processing.

Next is the quality of the cited data.

While digital technologies enhance the efficiency of data collection and processing, their improper use may also lead to a decline in data quality, such as accuracy issues caused by system failures or network latency. Furthermore, during the conduct of multi-center clinical trials, inconsistencies in data formats and standards from different sources may also adversely affect data quality and analytical outcomes.

In response, Weiyitongche has established a comprehensive data quality control system, implementing quality checkpoints and review mechanisms at every stage of data collection, entry, transmission, storage, and analysis. Leveraging the “Unimind-Gezhi” large language model, the system performs real-time validation of entered data, including format checks, logic checks, and range checks. Researchers receive timely alerts regarding errors and anomalies, enabling prompt data verification. During data integration and analysis, the platform employs a Common Data Model (CDM) to standardize and integrate multi-source heterogeneous data, ensuring data consistency and comparability.

Finally, the user-friendliness of digital technology products and systems is also quite important.

The user-friendliness of digital technologies and products also affects user experience and work efficiency. Systems with complex operational workflows and unfriendly interfaces can, to some extent, increase the difficulty of use for researchers and subjects, thereby impacting trial progress and data accuracy.

In this regard, Weiyitongche adheres to the principle of being “user-centric” in product design and development. Through in-depth research into clinical study scenarios, the company has gained extensive insights into users’ habits and pain points, and has accordingly optimized the product’s interactive interface and operational workflows. Furthermore, the company provides comprehensive user guides and training services to help users quickly master and utilize the system. Meanwhile, catering to different user groups, the company supports the development of personalized features and interfaces to meet individualized needs.

Wei Tian stated bluntly that as the digitalization of clinical trials advances, related regulatory issues are becoming increasingly prominent. To address this, regulatory policies must keep pace with the times to foster the high-quality development of digital clinical trials.

On one hand, regulations and standards need to be improved. Relevant authorities should closely monitor the developments and trends of digital technologies in clinical trials, promptly grasp the application characteristics and potential risks of emerging technologies such as artificial intelligence and blockchain, engage in frequent exchanges with representative enterprises in the industry, and balance technological development and application with safety supervision and governance.

Another aspect is international cooperation on regulatory standards. Wei Tian believes that China has entered the era of innovative drugs, with the global expansion of new drugs becoming a major trend; launching overseas requires meeting regulatory requirements in various regions. Regulatory authorities need to actively engage in cooperation and exchanges with relevant domestic and international institutions, draw on international regulatory experience and standards, and formulate a regulatory framework that aligns with both China’s national conditions and international practices by taking into account the actual application of digital technologies in clinical trials within China, thereby safeguarding the global development of Chinese pharmaceutical companies.

VCBeat firmly believes that in the era of large language models, AI is reshaping the field of clinical trials with unprecedented momentum, leveraging its powerful learning and analytical capabilities, and is destined to become the core driver of transformation in this sector.

In protocol design, AI can provide reference guidance tailored to research directions, thereby enhancing the efficiency and feasibility of study protocol development.

In subject recruitment, AI can optimize eligibility criteria, precisely screen suitable participants, and improve recruitment efficiency.

In subject management, AI can monitor medication adherence, enhance participant engagement, and reduce dropout rates.

In data management, AI can enhance the efficiency of data acquisition and quality control, thereby reducing service costs.

Here, Wei Tong Yi Zhe is actively embracing the wave of the new era, increasing R&D investment, and exploring the deep integration of AI with clinical trials to create a new model that is efficient, scientific, and reliable. By optimizing data security systems, enhancing understanding of algorithms, strengthening cross-disciplinary collaboration, and promoting the establishment of industry standards, Wei Tong Yi Zhe is committed to leveraging AI technology to usher in a new chapter for clinical trials and creating value for the cause of human health.