AI assisted genomic profiling for the personalisation of treatment and control of infections

具有成本效益的快速全基因组测序（WGS）技术目前正在临床环境中推广，以预防疾病、诊断和个性化治疗患者。WGS已成为传染病环境中使用的常规、快速和负担得起的诊断工具，彻底改变了临床决策、公共卫生监测和感染控制。在COVID-19大流行期间，这种效用得到了证明，SARS-CoV-2基因组的快速WGS有助于检测临床上重要的变异（例如，组粒），了解传播动态并辅助疫苗开发。更普遍的是，对WGS数据的分析可以快速推断病原体的“毒性”菌株类型，预测药物或抗菌素耐药性（AMR），并确定疫情。为了协助这种基于wgs的分析，可以获得分子条形码，以描述抗菌素耐药性的病原体、地理来源（例如，用于识别输入事件）和传播性，并将其与快速信息软件工具联系起来。然而，随着临床环境中WGS的使用越来越多，需要人工智能方法来挖掘由此产生的大数据，以（近）实时地更新条形码并推断传输动态。我们在疟疾和结核病中的WGS分析工作已经建立了信息性的条形码突变，并开发了世界领先的信息学平台（例如TB-Profiler），这些平台已在全球范围内应用（在35个国家中分析了100万株WGS结核细菌）。我们还应用人工智能方法（例如，神经网络）来检测和识别与AMR相关的已知和新基因，从而提高对潜在抗性机制的了解，以改进条形码。在这里，我们将基于人工智能的AMR突变和传播发现工具整合到我们的信息分析软件中，使它们动态，并有可能改善临床和感染控制决策。在英国卫生安全局（UKHSA）和亚洲（菲律宾、泰国、越南）卫生部的既定合作下，我们将在英国和传染病流行环境中实施由此产生的人工智能信息平台，并有可能将其扩展到其他感染，从而带来相关的健康和经济效益。此外，生成的所有WGS数据以及开发的人工智能和信息学软件将进入公共领域，从而对其他生物医学研究和医疗保健领域产生积极影响。

Cost-effective and rapid whole-genome sequencing (WGS) technologies are now being rolled-out in clinical settings to prevent disease, diagnose and personalise treatment of patients. WGS has become a routine, fast and affordable diagnostic tool used in infectious disease settings, revolutionizing clinical decision making, public health surveillance and infection control. This utility has been demonstrated during the COVID-19 pandemic, where rapid WGS of SARS-CoV-2 genomes has assisted the detection of clinically important variants (e.g., omicron), informed transmission dynamics, and aided vaccine development. More generally, analysis of WGS data can rapidly infer pathogen "virulent" strain-types, predict drug or antimicrobial resistance (AMR), and identify outbreaks. To assist this WGS-based analysis, molecular barcodes to profile pathogens for AMR, geographical source (e.g., for identification of importation events) and transmissibility can be derived and linked to fast informatic software tools. However, with increasing WGS use in clinical settings, there is a need for AI methods to mine the resulting big data to update barcodes and infer transmission dynamics in (near) real time. Our WGS profiling work in malaria and tuberculosis disease has established informative barcoding mutations, and developed world-leading informatics platforms (e.g., TB-Profiler) that have been applied globally (>100k tuberculosis bacteria with WGS, profiled across >35 countries). We have also applied AI methods (e.g., neural networks) to detect known and identify novel genes linked to AMR, thereby improving knowledge of underlying resistance mechanisms to improve barcodes. Here, we will integrate AI-based AMR mutation and transmission discovery tools into our informatic profiling software, making them dynamic and potentially improving clinical and infection control decision making. Working within established collaborations involving The UK Health Security Agency (UKHSA) and Health ministries in Asia (Philippines, Thailand, Vietnam), which are routinely using WGS-based diagnostics, we will implement the resulting AI-informatics platforms in UK and infectious disease endemic settings, with the potential of extending them to other infections, leading to associated health and economic benefits. Further, all WGS data generated, and AI and informatics software developed, will put in the public domain, leading to positive impacts in other biomedical research and healthcare areas.