DALIAN, China, June 24, 2026 /PRNewswire/ — On June 23, at the 17th Annual Meeting of the New Champions (Summer Davos 2026) hosted by the World Economic Forum in Dalian, Gong Yingying, Founder and Chairlady of Yidu Tech, participated in the panel discussion "Faster Drugs, Better Access?". She shared her perspectives on the structural transformation of global pharmaceutical R&D and how AI and healthcare data infrastructure are reshaping drug development and clinical practice.
The session was moderated by Li Xin, Managing Editor of Caixin Global, and featured fellow panelists Giovanni Caforio, Chair of the Board of Novartis, Ren Minghui, Professor at the School of Public Health of Peking University, and Eric Tse S Y, Chief Executive Officer of SBP Group.
From Data to Evidence: The Core Infrastructure Behind Medical AI
China is now the world’s second-largest hub for innovative drug development, with clinical trial activity continuing to expand rapidly. Yet challenges such as fragmented data, lengthy development timelines, patient recruitment difficulties, and inefficient evidence generation continue to limit the accessibility of innovative therapies.
According to Gong, these challenges are not merely issues of process efficiency; they stem from a deeper fragmentation of healthcare data. "Data is scattered, inconsistent, and disconnected," she noted, describing this as one of the biggest barriers preventing AI from delivering its full value in healthcare.
This challenge is precisely why Yidu Tech chose to invest in healthcare data infrastructure from the ground up.
Gong outlined a four-layer architecture for medical AI: the computing layer, foundation models, healthcare-foundational models, and, most importantly, a high-quality data pool. In essence, this data pool serves as an "evidence layer." Raw data alone cannot support clinical decision-making. Only after continuous standardization, governance, and transformation into traceable, verifiable, and structured information can data evolve into a trustworthy clinical evidence system.
Built upon this standardized evidence foundation, healthcare organizations can develop responsible, controllable, and safety-compliant AI agents. This integrated infrastructure, Gong emphasized, has become a critical enabler of more efficient and higher-quality drug development.
The practical embodiment of this vision is Yidu Tech’s proprietary "AI Medical Brain," YiduCore. By transforming fragmented healthcare data into structured disease knowledge and research capabilities, YiduCore supports a wide range of healthcare applications. As of September 30, 2025, YiduCore had cumulatively processed and analyzed nearly 7 billion authorized medical records, connected more than 10,000 healthcare institutions, and built a disease knowledge graph covering virtually all known diseases.
Data Infrastructure Is Directly Improving Drug Development Efficiency
Leveraging its extensive network of leading hospitals and clinical research partners across China, Yidu Tech has extended its healthcare data infrastructure beyond hospitals to support the entire clinical research and drug development value chain, creating systematic applications across real-world studies and clinical trials.
At the early stage of drug development, Yidu Tech’s disease knowledge graph helps researchers identify promising research directions, design clinical trial protocols, and conduct feasibility assessments. This reduces the risks associated with poorly designed studies, implementation challenges, and resource inefficiencies, lowering the cost of trial-and-error in R&D.
During trial execution, the platform enables intelligent patient identification and matching across regions and research centers, significantly improving recruitment efficiency and shortening enrollment timelines. It addresses long-standing challenges such as slow recruitment, low matching accuracy, and insufficient patient diversity.
At the same time, AI-powered quality control, real-time data validation, and intelligent monitoring and early warning of adverse events support dynamic oversight throughout the clinical trial lifecycle. These capabilities improve data quality and compliance while reducing operational risks.
In the post-development phase, the platform’s standardized evidence layer enables efficient real-world data curation, evidence generation, and patient cohort analysis. These capabilities support post-marketing studies, indication expansion, reimbursement decisions, and evidence-based clinical adoption, helping create a complete value cycle from innovative drug development to broader patient access.
Gong noted that while clinical trial optimization historically relied heavily on human expertise, standardized data infrastructure combined with AI has now become a prerequisite for conducting high-quality clinical research and accelerating innovative drug development. What was once viewed as a value-added enhancement has become an essential component of industry innovation.
Taking Medical AI Global: Data Sovereignty and Deep Localization
Addressing global collaboration and data governance, Gong emphasized that healthcare data must always be managed with security and compliance as top priorities.
Under regulatory frameworks around the world, healthcare data is typically stored within sovereign government-controlled cloud environments. Independent third parties are responsible for ensuring data security, managing access permissions, auditing data usage, and enforcing compliance requirements.
She stressed that healthcare is fundamentally different from industries that can deploy standardized global products. Healthcare delivery is deeply shaped by local regulations, policies, and public health needs, making localization essential for any international expansion strategy.
As an example, Gong highlighted Yidu Tech’s collaboration in Brunei. Through a jointly operated venture with the government and a shared technical team, Yidu Tech co-manages BruHealth, Brunei’s national digital health platform. While fully respecting local data sovereignty and privacy requirements, the partnership brings proven AI healthcare capabilities to support digital health services tailored to the needs of local residents.
Gong concluded that Yidu Tech’s long-term investment in healthcare AI infrastructure is driven by a simple objective: ensuring that healthcare innovation translates into tangible benefits for patients. Technology is only a tool; the ultimate goal is to make healthcare systems more efficient, trustworthy, and accessible.
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