HKEX and LinkDoc Collaborate on Secure Data Fusion: Exploring Encryption and Privacy-Preserving Technologies for Healthcare Innovation

“China’s annual total expenditure on cancer patients amounts to approximately RMB 400 billion, with around 4 million new cases diagnosed each year and a misdiagnosis and missed diagnosis rate as high as 40%.” On September 22, at the 4th China Pharmaceutical Innovation and Investment Conference, Zhang Tianze, CEO of LinkDoc, used these striking figures to illustrate that conquering cancer is no easy task. In his view, big data and artificial intelligence (AI) will become powerful weapons in the fight against cancer.

At the conference, Zhang Tianze approached the topic from the perspective of pharmaceutical industry applications, offering new insights and practical experience by highlighting breakthroughs in innovative oncology drug development driven by big data and AI technologies.

In recent years, with continuous technological breakthroughs, rising market demand, and an influx of capital, the research and development of new oncology drugs has presented a thriving landscape; however, numerous hidden concerns lie beneath the surface.

The slow, costly, and low-success-rate nature of oncology drug development poses significant challenges to clinical trials. “The trend toward precision therapy is the root cause of many clinical challenges in the development of new oncology drugs,” analyzed Zhang Tianze. Under the influence of precision medicine, deepening understanding of diseases has led to the continuous emergence of new and niche targets, transforming a single disease entity into N subdivided subtypes. This shift has created two major problems for pharmaceutical companies: “First, R&D has become more difficult, as the narrowing scope of patient enrollment and the refinement of patient stratification have significantly increased the time and financial costs of individual clinical trials. Second, the target patient population for drugs has become fragmented and dispersed, making physician education and patient management more difficult and posing challenges to post-launch sales.”

Big Data + AI: The Breakthrough Point for Innovation in Healthcare and Scientific Research

In 2018, Roche successively acquired Flatiron Health, an oncology big data company, and Foundation Medicine, a cancer genetic testing company. Roche aims to possess the capability to observe, analyze, and evaluate the clinical performance of drugs based on healthcare big data, thereby facilitating clinical trial design and the development of additional indications. This approach would significantly enhance the certainty of research outcomes and the accuracy of predictions compared to previous methods. Zhang Tianze believes that “once such capabilities are unlocked, an increasing number of people will seek to acquire them.”

Leveraging high-quality medical big data, AI technologies have begun to be applied in clinical research. For instance, Acornai has developed AI solutions based on clinical trial data to help pharmaceutical companies and contract research organizations (CROs) design and execute clinical trials more efficiently. In the preclinical drug discovery phase, pharmaceutical companies are also utilizing AI technologies to accelerate the pace of drug discovery. Furthermore, China’s drug regulatory authorities have started to encourage the exploratory application of real-world data in clinical trials. This May, the Center for Drug Evaluation (CDE) publicly solicited comments on the Basic Considerations for Real-World Evidence Supporting Drug Development, which outlined six major application scenarios for real-world evidence.

However, the key to realizing clinical application research driven by medical big data and AI technology lies in research-grade data. To forge such research-grade data, Zhang Tianze and his team conducted nearly a decade of exploration in this field, ultimately developing a data intelligence structuring solution that surpasses traditional methods. This has also been the core driving force behind the rapid development of LinkDoc’s business.

“We help clinical experts manage medical records and unlock the value of data, while also assisting pharmaceutical companies in developing new drug indications to accelerate the market launch of new drugs.”Zhang Tianze used the term “bilateral” to describe this model. Overall, LinkDoc possesses the capability to provide services across the entire drug lifecycle, offering solutions at every stage—from target identification, indication selection, and clinical trial strategy, to patient recruitment during clinical study implementation, physician awareness post-launch, pharmaceutical care, medication support, patient management, and evidence collection for indication expansion. Meanwhile, it provides Virtual Trial Simulation based on specialized oncology data cohorts to optimize trial protocol design and offer preliminary strategies for patient recruitment and Real-World Studies (RWS). Its data insights business helps pharmaceutical companies better execute their launch strategies, completing the “last mile” of new drug development.

“Of course, data security is the foundation of all this,” said Zhang Tianze. He emphasized that during the application of data, it is essential to strictly adhere to standardized protocols such as “physical data isolation, access control, tiered management of application data, and informed patient consent.”

LinkDoc believes that, currently,The development of big data is, in essence, the advancement of data security.Under the traditional requirements of data security (CIA), LinkDoc has established its own standards for timeliness, traceability, non-repudiation, and compliance. Diverse security requirements and an increasingly stringent regulatory environment have brought unprecedented challenges to the big data era. In response to these challenges, building a more compliant, secure, and efficient data ecosystem is a critical prerequisite for the development and survival of big data companies like LinkDoc.

At the opening ceremony of this venture capital conference, Charles Li, CEO of Hong Kong Exchanges and Clearing Limited, stated that the large-scale use of medical data currently faces four major challenges: difficulties in data standardization, rights confirmation, protection, and pricing.

“If the two major challenges of protection and pricing can be effectively addressed, the government and society will have the motivation and capacity to further resolve the difficulties in standardization and rights confirmation. The era in which big data is widely applied to pharmaceutical innovation and the enhancement of human health is just around the corner,” emphasized Li Xiaoqiang.

Thus, it is evident that addressing the challenge of “difficult protection” by leveraging technology to ensure data security, protect privacy information, and handle sensitive data is another key factor in further promoting integrated data applications and accelerating the transformation of business models in the pharmaceutical and healthcare industries.

In this regard, Wang Dong, Co-Head of the Strategic Projects Execution Division within the Market Development Department of Hong Kong Exchanges and Clearing Limited (HKEX), stated that HKEX is currently collaborating with LinkDoc and Huakong Qingjiao to conduct in-depth research on leveraging Secure Multi-Party Computation (MPC) to enable multi-party data analysis while maintaining data encryption, and has undertaken exploratory pilot initiatives.

In the collaboration, LinkDoc will leverage its strengths in standardized data governance and build upon its sustained practical achievements in “data crowdsourcing” to provide simulated application scenarios, enabling data integration, analysis, and application in an encrypted state through secure multi-party computation.

This multi-party collaboration jointly promotes technological innovation and application in data fusion and sharing, aiming to address the long-standing concerns of regulators, data owners, and processors. By prioritizing ethical considerations, it enables disruptive transformations such as broader-scope research designs, thereby breaking traditional drug development pathways and significantly accelerating clinical trials and new drug development. Under the premise of ensuring safety and privacy protection, this initiative allows big data to better serve pharmaceutical innovation and human health.