Data Intelligence Solution Breaks Through the Bottleneck of Traditional Quality Control Mode of Clinical Trials
In order to empower the quality control of clinical trial data, Happy Life Technology (HLT) proposes a digital quality control solution. Under the premise of obtaining authorization, through in-depth analysis of clinical trial source data, combined with lightweight algorithm services, AI technology is used to conduct test data analysis. Comprehensive verification, accurate traceability, and quantitative evaluation are not only convenient and safe to operate, but also significantly improve the efficiency of test data management.
Bringing Down Real-World Evidence Barriers in China
BY LAUREN MARTZ, SENIOR EDITOR AND RIMMEL SHEKHA, BIOPHARMA ANALYST
China’s Opportunity to Become a Real-World Evidence Leader
How Hainan’s free trade zone is creating a standardized real-world evidence infrastructure BY LAUREN MARTZ, SENIOR EDITOR
Study Results of Peking Union Medical College Hospital’s Intensive Care Unit Artificial Intelligence Collaboration by Yidu Tech’s Affiliate HLT Published in International Journal
Recently, the research team of Director Yun Long of Peking Union Medical College Hospital (PUMCH) published the paper “Using Machine Learning Algorithms to Predict Candidaemia in ICU Patients With New-Onset Systemic Inflammatory Response Syndrome” in Frontiers In Medicine. The paper introduces a prediction model of Candida infection established by Director Yun Long's research team in collaboration with Happy Life Tech (HLT), an affiliate of Yidu Tech.
Considerations on the Application of Real-World Data for Post-Marketing Safety Studies in China
In recent years, the fusion of big data and medical science supported by relevant policies leading to more use of real-world data (RWD) in medical studies. Real-world evidence (RWE) from real-world data has been used for post-marketing assessment of medical products to support decision-making on safety supervision. In this article, we will discuss the application of RWD on post-marketing safety studies.
A New Chapter in Pharmacovigilance – Post-Marketing Safety Studies
On July 15, 2021, the 3rd Annual China Pharmacovigilance Conference and GVP Landing Practice Experience Dialogue was held in Wuxi. Tan Ruixin, director of HLT Innovative Medical Solutions and Real-World Evidence, attended as a guest speaker. She presented on the topic of post-marketing safety studies based on real-world data.
Real-World Evidence: Successful Cases Using Synthetic Control Methods
For single-arm clinical trials, it is possible to use an external control with real-world data. This is especially helpful in trials for rare disease where recruitment is difficult due to the scarcity of cases. Using real-world data as a control is also helpful for trials of life-threatening diseases that lack effective treatment. External controls can be divided into two main groups. The first type, historical controls, are based on real-world data obtained prior the trial. The second type, parallel controls, use data from the same period as the single-arm trial.
Feasibility Assessment and Governance of Real-World Data in China
Recently, the Guidelines for Real-world Data Used in the Generation of Real-world Evidence (referred to below as the Guidelines) issued by the Center for Drug Evaluation (CDE) of the National Medical Products Administration (NMPA) were offered to the public for comments . The Guidelines comprehensively elaborate the definitions, sources, evaluations, governance, standards, safety compliance, quality assurance, applicability, and other aspects of real-world data (RWD), to provide specific requirements and guiding recommendations for RWD. They provide a guidance on how RWD can be used to generate real-world evidence (RWE) to support drug development and how feasibility assessment and data governance should be done.
Evidence Leads the Future: Real-World Evidence Empowers Clinical Development
On June 17–19, 2021, the Clinical Data Management (CDM) 2021 China Conference was held in Shanghai with the theme of “Drive CDM with Digital Transformation.” Many scholars, experts, and industry leaders gathered in Shanghai to discuss areas of interests. Dr. Haijun Cao, Vice President of Happy Life Technology, was invited to attend the conference and gave a keynote speech entitled “Exploration and Prospects of Clinical Development Empowered by Real-World Data.”
Switching regimens without relapse? Explore the truth of multiple myeloma patients with real-world study
Multiple myeloma (MM) represents a big challenge for health care providers. Treating MM is complex and often involves several medications including immunotherapies, chemotherapy agents, and proteasome inhibitors. MM patients usually switch therapies when the disease progresses or shows drug resistance. However, physicians also switch medications for patients whose disease has not progressed. In fact, up to 50% of the MM patients in real-world settings experience a regimen switch without a relapse in China. Change of therapy adds to the complexity of treating MM and makes it challenge for physicians to choose the right therapies at the right time for the right patients. Real-world data helps HCPs and researchers estimate the true impact of each treatment options. HLT analyzes real-world treatment patterns and patient outcomes to provide valuable information about a product’s market impact.