Project description:As China assumes a more and more dominant role in global science, this mini-review attempts to provide a bird's eye view on how the bio-digital revolution impacts China's biosciences and bioindustry. Triggered by top-down political programs and the buildup of an impressive infrastructure in science, information technology, and education, China's biomedical and MedTech industries prosper. Plant and animal breeding programs transform agriculture and food supply as much as the Internet of things, and synthetic biology offers new opportunities for the manufacturing of specialty chemicals within the Chinese version of a "bioeconomy." It is already becoming apparent that the new five-year period "145" (2021-2025) will further emphasize emission control, bioenvironmental protection, and more supply of biomass-derived energy. This review identifies key drivers in China's government, industry, and academia behind these developments and details many access points for deeper studies. KEY POINTS: Biotechnology in China Biomedical technology New five-year period.
Project description:At a meeting of the EU/US/Clinical Trials in Alzheimer's Disease (CTAD) Task Force in December 2016, an international group of investigators from industry, academia, and regulatory agencies reviewed lessons learned from ongoing and planned prevention trials, which will help guide future clinical trials of AD treatments, particularly in the pre-clinical space. The Task Force discussed challenges that need to be addressed across all aspects of clinical trials, calling for innovation in recruitment and retention, infrastructure development, and the selection of outcome measures. While cognitive change provides a marker of disease progression across the disease continuum, there remains a need to identify the optimal assessment tools that provide clinically meaningful endpoints. Patient- and informant-reported assessments of cognition and function may be useful but present additional challenges. Imaging and other biomarkers are also essential to maximize the efficiency of and the information learned from clinical trials.