The unmet need in rheumatology: Reports from the targeted therapies meeting 2017.

Clinical immunology (Orlando, Fla.)(2017)

引用 73|浏览26
暂无评分
摘要
The 19th annual international Targeted Therapies meeting brought together over 100 leading basic scientists and clinical researchers from around the world in the field of immunology, molecular biology and rheumatology and other specialties. During the meeting, breakout sessions were held consisting of 5 disease-specific groups with 20-40 experts assigned to each group based on clinical or scientific expertise. Specific groups included: rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, systemic lupus erythematous, connective tissue diseases (e.g. Sjogren's syndrome, Systemic sclerosis, vasculitis including Bechet's and IgG4 related disease), and a basic science immunology group spanning all of the above clinical domains. In each group, experts were asked to consider and update previously identified unmet needs in 3 categorical areas: basic/translational science, clinical science and therapeutic development, and clinical care. Overall, similar primary unmet needs were identified within each disease foci, and several additional needs were identified since the time of last year's congress. Within translational/basic science, the need for better understanding the heterogeneity within each disease was highlighted so that predictive tools for therapeutic responses can be developed. Within clinical science and therapeutic trials, a strong focus was placed upon the need to identify pre-clinical states of disease allowing prevention in those at risk. The ability to cure remains perhaps the ultimate unmet need. Further, the need to develop new and affordable therapeutics, as well as to conduct strategic trials of currently approved therapies was again highlighted. Within the clinical care realm, improved co-morbidity management and patient-centered care were identified as unmet needs. Lastly, it was strongly felt there was a need to develop a scientific infrastructure for well-characterized, longitudinal cohorts paired with biobanks and mechanisms to support data-sharing. This infrastructure could facilitate many of the unmet needs identified within each disease area.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要