RESUMEN
At present, China is still in the exploratory stage in the field of electronic informed consent (eIC), and relevant policies, regulations and application guidelines have not yet been established and improved. While the traditional informed consent supervision system is difficult to meet the needs of the innovative development of eIC, such as subject privacy and data security. Through sorting out and analyzing the legal norms and construction system of eIC supervision in Europe and the United States, combined with the current development status, problems, and challenges of eIC in China, this paper targeted proposed the path to construct the supervision of eIC in clinical research in China from the aspects of restricting the signing form and process of eIC, adjusting the ethical review paradigm of eIC, enhancing the strength of eIC ethical review, improving the construction of eIC legal system, and strengthening the training of relevant researchers.
RESUMEN
The electronic informed consent (eIC) system is a product of modernization development of electronic and intelligent technology. In the context of COVID-19, the eIC system can adapt to the epidemic prevention and control requirements, showing its time-space advantages. By introducing the concept, form and the use of eIC system, this paper analyzed the challenges of acceptance, understanding, consent and information security faced by the eIC system. Based on this, some suggestions were put forward, including strengthening the training of the relevant personnel involved in the eIC system, enhancing and improving the functions of the eIC system, and perfecting the relevant laws and regulations of the eIC system, so as to provide reference for the future research and application of eIC.
RESUMEN
The development of artificial intelligence is becoming more and more mature, and has penetrated into every field of clinical trials. Artificial intelligence has brought new development opportunities for clinical trials. However, the application of artificial intelligence in clinical trials is still in the exploratory stage, facing many ethical issues, including trial risk caused by data quality, privacy protection caused by data regulation, and contradiction between data authorization and informed consent. We should precisely position the realizable application of artificial intelligence in clinical trials, understand its practical ethical issues, and formulate corresponding coping strategies to ensure the maximum improvement of the whole process performance of clinical trials, including strengthening data quality management and reducing clinical trial risks; optimizing data monitoring mechanisms to ensure data security and privacy; building a data authorization platform and improving judicial protection of informed consent, etc.