Office of the Senior Vice President Health Sciences, University of Arizona Health Sciences, Drachman Hall, Room B207, 1295 North Martin Avenue, P.O. Box 210202, Tucson, AZ, 85721-0202, USA.
Center for Applied Genetics and Genomic Medicine, University of Arizona, 1295 North Martin Avenue, Drachman Hall, Room B207, Tucson, AZ, 85721-0202, USA.
J Transl Med. 2018 Feb 15;16(1):28. doi: 10.1186/s12967-018-1401-2.
While the promise of the Human Genome Project provided significant insights into the structure of the human genome, the complexities of disease at the individual level have made it difficult to utilize -omic information in clinical decision making. Some of the existing constraints have been minimized by technological advancements that have reduced the cost of sequencing to a rate far in excess of Moore's Law (a halving in cost per unit output every 18 months). The reduction in sequencing costs has made it economically feasible to create large data commons capturing the diversity of disease across populations. Until recently, these data have primarily been consumed in clinical research, but now increasingly being considered in clinical decision- making. Such advances are disrupting common diagnostic business models around which academic medical centers (AMCs) and molecular diagnostic companies have collaborated over the last decade. Proprietary biomarkers and patents on proprietary diagnostic content are no longer driving biomarker collaborations between industry and AMCs. Increasingly the scope of the data commons and biorepositories that AMCs can assemble through a nexus of academic and pharma collaborations is driving a virtuous cycle of precision medicine capabilities that make an AMC relevant and highly competitive. A rebalancing of proprietary strategies and open innovation strategies is warranted to enable institutional precision medicine asset portfolios. The scope of the AMC's clinical trial and research collaboration portfolios with industry are increasingly dependent on the currency of data, and less on patents. Intrapeneurial support of internal service offerings, clinical trials and clinical laboratory services for example, will be important new points of emphasis at the academic-industry interface. Streamlining these new models of industry collaboration for AMCs are a new area for technology transfer offices to offer partnerships and to add value beyond the traditional intellectual property offering.
虽然人类基因组计划的承诺提供了对人类基因组结构的重要见解，但个体层面疾病的复杂性使得 -omics 信息难以用于临床决策。通过技术进步，一些现有限制已经得到了最小化，这些技术进步使测序成本降低到远远超过摩尔定律（每 18 个月单位产量成本减半）的速度。测序成本的降低使得创建捕获人群中疾病多样性的大型数据公有变得在经济上可行。直到最近，这些数据主要在临床研究中使用，但现在越来越多地被考虑用于临床决策。这些进展正在打破围绕学术医学中心（AMC）和分子诊断公司在过去十年中合作的常见诊断业务模型。专有生物标志物和专有诊断内容的专利不再推动行业和 AMC 之间的生物标志物合作。越来越多的是，AMC 通过学术和制药合作的纽带可以组装的数据公有和生物库的范围正在推动精准医学能力的良性循环，使 AMC 具有相关性和高度竞争力。为了实现机构精准医学资产组合，有必要重新平衡专有策略和开放创新策略。AMC 与行业的临床试验和研究合作组合的范围越来越依赖于数据的时效性，而对专利的依赖则越来越小。例如，对内部服务提供、临床试验和临床实验室服务的内部创业支持将成为学术-工业界面的新重点。为 AMC 简化这些新的行业合作模式是技术转让办公室提供合作并提供超越传统知识产权服务的附加值的一个新领域。
