Avenna LifeBook (AvLB): A bioinformatics system to support a real world, life-course approach to precision medicine for inflammatory bowel disease (IBD)

** 愿景 ** 该项目旨在开发Avenna LifeBook（AvLB）的关键组件，AvLB是一个生物信息学系统，用于支持我们针对高负荷慢性炎症性疾病（cID）的精准医学（PM）计划。AvLB是Avalon中的第一个模块，Avalon是我们的生物信息学系统，用于生成cID患者健康和疾病轨迹的真实世界证据（RWE）。AvLB的功能是收集、清理和准备每个人的真实世界数据（RWD）和其他相关健康信息，以便通过Avalon的PM建模系统转换为RWE。目标 ** 在这个项目中，我们将开发核心AvLB数据结构和算法，以清洁，策划和注释炎症性肠病（IBD）患者的数据集。然后，清理后的数据将准备好由ProDroma-IBD进行分析，ProDroma-IBD是我们正在开发的一种新型人工智能系统，用于预测IBD患者未来可能的健康轨迹及其对抗炎治疗的反应。焦点 ** 通常，AvLB要清理和管理的RWD会很大、复杂、不完整、不对称和部分损坏。在这个项目中，我们将专注于广泛的IBD患者数据集，包括：* 基因组学概况。相关组学数据-例如Avenna的GlyHealth-IBD检测和表观遗传学、微生物组学、代谢组学和蛋白质组学测试的概况。GlyHealth-IBD是我们与Ludger共同开发的新型预后和预测性糖组学生物标志物。IBD特异性临床数据-包括内窥镜图像、血液和粪便分析。*患者提供的数据-包括数字信息，例如来自Ampersand Health的MyIBD Care应用程序的症状跟踪信息，食物，运动和睡眠数据。大多数数据集将是与IBD疾病进展和肠道愈合相关的时间序列曲线，以响应有效的抗炎治疗。该项目的患者数据将由我们的一些临床和Medtech开发合作伙伴提供。其中包括NIHR IBD生物资源，Barts医院和Ampersand Health。创新 **AvLBD必须管理患者数据，以简化ProDroma-IBD的复杂AI分析。为了实现这一目标，我们使用了基于新系统科学框架的方法，以支持将PM技术系统地转化为CID。新系统科学框架涉及人类生活模式，特别是那些塑造个人生活轨迹的健康决定因素。它的主要原则是，我们生活中的复杂模式来自简单组件的相互作用。Questiré使用数学模型和工具来帮助我们处理RWD和RWE的混乱和复杂性。我们必须有效地分析这些问题，以推进慢性炎症性疾病的精准医学，包括IBD的PM。

**Vision**This project is to develop critical components of Avenna LifeBook (AvLB) -- a bioinformatics system to support our precision medicine (PM) programmes for high-burden chronic inflammatory diseases (cIDs).AvLB is the first module in Avalon, our bioinformatics system to produce real-world evidence (RWE) on cID patients' health and disease trajectories. AvLB's function is to gather, clean, and prepare real-world data (RWD) and other relevant health information on each individual for transformation to RWE by Avalon's PM modelling systems.**Objectives**In this project, we will develop core AvLB data structures and algorithms to cleanse, curate, and annotate datasets on patients with inflammatory bowel disease (IBD). The cleansed data would then be ready to be analysed by ProDroma-IBD, a novel AI system we are developing to predict the likely future health trajectories of IBD patients and their responses to anti-inflammatory treatments.**Focus**Typically, the RWD to be cleansed and curated by AvLB would be large, complex, incomplete, skewed, and partially corrupted. In this project, we will focus on a wide range of IBD patient datasets including :* Genomics profiles.* Relevant omics data -- e.g. profiles from Avenna's GlyHealth-IBD assay and epigenetic, microbiome, metabolomics, and proteomics tests. GlyHealth-IBD is our novel prognostic and predictive glycomics biomarker being co-developed with Ludger.* IBD-specific clinical data -- including endoscopy images, and blood and stool analyses.* Patient-supplied data -- including digital information, e.g. symptoms tracking information from Ampersand Health's MyIBDCare app, food, movement, and sleep data.Most of the datasets would be time-series profiles relevant to IBD disease progression and gut healing in response to effective anti-inflammatory therapy.The patient data for this project will be provided by some of our clinical and Medtech development partners. Those include the NIHR IBD BioResource, Barts Hospital, and Ampersand Health.**Innovation**AvLBD must curate patient data to ease complex AI analyses by ProDroma-IBD. To achieve that, we use methods we built on Emoiré, our novel systems science framework to support the systematic translation of PM technologies for cIDs.Emoiré deals with patterns in human life, particularly those for health determinants that shape an individual's life trajectory. Its main tenet is that complex patterns in our lives arise from interactions of simple components. Emoiré uses mathematical models and tools to help us deal with the chaos and complexity of RWD and RWE. We must analyse these effectively to advance precision medicine for chronic inflammatory diseases, including PM for IBD.