Planning Grant: An Engineering Research Center for the Engineering of Emergent Biocomplexity (ERC-EEB)

规划资助：新兴生物复杂性工程研究中心（ERC-EEB）

• 批准号: 1937105
• 负责人: Jonathan Butcher
• 金额: $ 10万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937105&HistoricalAwards=false
• 关键词: Planning; Grant; Engineering; Research; Center

Engineering Research Center for the Engineering of Emergent Biocomplexity: Draft AbstractPart 1: Persistent societal challenges prohibit broad-based advancement and human flourishing. Cancer and structural heart defects remain prevalent, unpredictable, and destructive to both families and public resources. Habitat challenges limit production of high-value crops like broccoli. Biotechnology employment is oppressively concentrated in a few large cities, restricting economic opportunity and family planning. These diverse grand challenges exhibit complex commonalities that motivate an integrated solution. Specifically, we believe three facets of biocomplexity?developmental, adaptive, and pathological?are governed by as-yet-unknown emergent construction principles or Rules of Life (one of the NSF?s 10 Big Ideas). We propose an Engineering Research Center for the Engineering of Emergent Biocomplexity (EEB). EEB will pursue foundational science, technology enablement, and economic translation of the engineering system of Emergent Biocomplexity. We will identify construction rules that govern emergent biocomplexity by interrogating three engineering test-beds for which we have extensive expertise and established experimental systems: 1) Developmental emergence: heart morphogenesis, 2) Adaptive emergence: inflorescence morphogenesis, and 3) Pathological emergence: Glioblastoma morphogenesis. Multi-scale, systems-level understanding from each test-bed will cross-inform mechanisms in the others, and through convergent research we will achieve transformative engineering outcomes with high impact: 1) A bench-grown robust, structurally advanced ventricle to advance quantitative developmental biology and enable direct evaluation of restorative approaches for malformed hearts. 2) New broccoli amenable to Eastern US climates with consumer-preferred structural architecture and preservation of vital nutrients. 3) An engineered glioblastoma tumor test platform to identify and validate new drug targets based on controlling emergent behaviors inaccessible to current technologies. In the process of achieving these goals, we will innovate next generation quantitative live imaging and multi-scale/multi-valent computational simulation technology that will accelerate and advance the understanding and control of dynamic biological complexity. We will leverage these science and engineering gains with innovative emergence-based STEM training to transform broaden biotechnology related employment access. Tackling this Grand Challenge requires the deep collaboration of many experts across diverse disciplines (e.g. Math, Plant science, Engineering, Epistemology), siloed disciplinary cultures and language barriers, institutional barriers, and geographical distance. Our institutions: Cornell University, City College of New York, University of Pittsburgh, and the Ohio State University, are ideally positioned within key rural and inner-city domains. This planning grant will help coalesce the academic and industrial expertise and collective infrastructure, build lines of community trust, and refine our strategic plan to carry out these goals. Further, this grant will enable us to engage disparate community stakeholders early in the process to improve our unique emergent computational workforce development program.Part 2: We will plan an ERC to pursue a new convergent research field of emergence science and engineering, focused to discover the Rules of Life that are conserved or unique between diverse emergent biological systems. We will apply deep convergence and team science to refine the communication of emergence science across discipline chasms and identify science tools for interrogating variation and robustness within complex biological systems. This will be achieved through cross-collaborative, multi-institutional test bed team meetings whereby the science and engineering frontiers are solidified and well-grounded paths forward with technical and knowledge success milestones are stratified. Through these meetings, we will establish and prioritize shared needs for engineering a new modular multi-valent computational simulation platform and multi-scale quantitative imaging systems. These systems will provide transformative data generation and analysis tools for accelerating the science and engineering of emergent biocomplexity, using each test bed domain to stretch and refine their capabilities. These technology pipelines will additionally serve as engagement nodes for computational biotechnology firms as they seek to expand their footprints into this emerging economic sector. We will engage regional industry leaders through the planning process to further integrate their technology and training desires. Further, our leadership team includes communication and team formation/team performance experts who will study this planning process to develop models for best practices for ideation and team communication within convergent research environments. The success of our planning strategy will establish a compelling cross-platform test case and refine a new process of cross-disciplinary team engagement for transforming science and engineering research for identifying and solving shared highly complex problems. The proposed planning process will also refine stakeholder needs for culturally responsive workforce generation program for a Center-credentialed computational gig-economy. We will work with existing remote workforce talent and their employers to frame training, certification, and advancement ladder ideals for career sustainability and advancement within computational simulation and analysis space. This broad based, branded and securely managed system would eliminate location oppression in the workforce and enable emergent expertise production. This approach will also catalyze rural engagement in STEM education and the economy. We will also coalesce and refine our novel emergence science and engineering concepts through broadly accessible science symposia, from which focused reviews in leading science journals will evangelize the rationale and approaches. These meetings will also help refine how we continue to include diverse voices from across discipline and stakeholder boundaries for sustaining impact through the ERC period. Finally, these components will then be integrated into a formal ERC proposal to implement the research, engineering, and workforce development goals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

第1部分：持续的社会挑战阻碍了广泛的进步和人类的繁荣。癌症和结构性心脏缺陷仍然普遍存在，不可预测，对家庭和公共资源都具有破坏性。栖息地的挑战限制了西兰花等高价值作物的生产。生物技术就业集中在少数几个大城市，限制了经济机会和计划生育。这些不同的大挑战表现出复杂的共性，从而激发了集成解决方案。具体来说，我们相信生物复杂性的三个方面？发展性、适应性和病理性？是由尚不为人知的紧急构造原则或生命规则(NSF？（10大创意）。我们建议建立紧急生物复杂性工程研究中心（EEB）。EEB将致力于新兴生物复杂性工程系统的基础科学、技术实现和经济翻译。我们将通过询问三个我们拥有丰富专业知识和建立实验系统的工程试验台来确定控制新兴生物复杂性的构建规则：1)发育性出现：心脏形态发生，2)适应性出现：花序形态发生，以及3)病理出现：胶质母细胞瘤形态发生。来自每个试验台的多尺度、系统级理解将交叉告知其他试验台的机制，并通过聚合研究，我们将实现具有高影响力的变革性工程成果：1)一个试验台生长的稳健、结构先进的心室，以推进定量发育生物学，并能够直接评估畸形心脏的修复方法。2)适应美国东部气候的新型西兰花，具有消费者喜欢的结构结构和重要营养成分的保存。3)一个工程胶质母细胞瘤肿瘤测试平台，基于控制当前技术无法达到的突发行为来识别和验证新的药物靶点。在实现这些目标的过程中，我们将创新下一代定量实时成像和多尺度/多价计算模拟技术，这将加速和推进对动态生物复杂性的理解和控制。我们将利用这些科学和工程成果，通过创新的基于应急的STEM培训，拓宽生物技术相关的就业机会。应对这一重大挑战需要不同学科（如数学、植物科学、工程、认识论）的许多专家的深入合作，也需要学科文化和语言障碍、制度障碍和地理距离。我们的机构：康奈尔大学、纽约城市学院、匹兹堡大学和俄亥俄州立大学，都位于关键的农村和内城领域。这项规划补助金将有助于整合学术和工业专业知识和集体基础设施，建立社区信任，并完善我们的战略计划，以实现这些目标。此外，这笔拨款将使我们能够在早期参与不同的社区利益相关者，以改进我们独特的新兴计算劳动力发展计划。第二部分：我们将规划一个ERC，以追求新兴科学和工程的一个新的融合研究领域，重点发现不同新兴生物系统之间保守或独特的生命规则。我们将应用深度融合和团队科学来完善跨学科鸿沟的涌现科学的交流，并确定用于询问复杂生物系统中的变异和稳健性的科学工具。这将通过交叉协作、多机构的测试平台团队会议来实现，通过这种会议，科学和工程前沿得到巩固，并且技术和知识成功里程碑的良好基础路径得到分层。通过这些会议，我们将建立并优先考虑新的模块化多价计算仿真平台和多尺度定量成像系统的工程共享需求。这些系统将提供变革性的数据生成和分析工具，以加速新兴生物复杂性的科学和工程，使用每个试验台领域来扩展和完善其能力。这些技术管道还将作为计算生物技术公司的参与节点，因为它们正在寻求扩大在这一新兴经济领域的足迹。我们将通过规划过程与区域行业领导者接触，进一步整合他们的技术和培训愿望。此外，我们的领导团队包括沟通和团队组建/团队绩效专家，他们将研究这一规划过程，为融合研究环境中的创意和团队沟通开发最佳实践模型。我们计划策略的成功将建立一个引人注目的跨平台测试用例，并细化跨学科团队参与的新过程，以转化科学和工程研究，以识别和解决共享的高度复杂的问题。拟议的规划过程还将细化利益相关者对文化响应性劳动力生成计划的需求，以满足中心认证的计算零工经济。我们将与现有的远程劳动力人才及其雇主合作，为计算模拟和分析领域的职业可持续发展和发展制定培训、认证和晋升阶梯理想。这种基础广泛，品牌和安全管理的系统将消除劳动力中的位置压迫，并使紧急专业知识的生产成为可能。这种方法还将促进农村参与STEM教育和经济。我们还将通过广泛的科学研讨会来整合和完善我们的新兴科学和工程概念，主要科学期刊上的重点评论将传播其基本原理和方法。这些会议还将有助于改进我们如何继续包括来自不同学科和利益相关者边界的不同声音，以在整个ERC期间保持影响。最后，这些组件将被整合到正式的ERC提案中，以实现研究、工程和劳动力发展目标。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。