写的:
数据科学副总裁 & 人工智能、澳门在线赌城娱乐
Chief Data Scientist Advisor, AstraZeneca; Professor of Public Health & Clinical Informatics and Associate Pro Vice Chancellor for Innovation, University of Liverpool
Our scientists are using data science and artificial intelligence (AI) to engineer new and better ways to discover and test the potential medicines of tomorrow, 并将他们与关怀联系起来. 在这里, we examine some examples for how we are applying data science and AI in the discovery and development of the potential next wave of innovative medicines.
用于药物发现的人工智能和知识图谱
药物的发现是通过生物化学进化而来的, 生物, 最近, biotechnical实验. In 2012, 谷歌引入了“知识图谱”这个术语。, drawing from previous decades of computer science – to depict how knowledge can be organised, 表达和推理. 知识图谱为生活带来了不可思议的信息库, 帮助用户发现成千上万个不同来源之间的联系.
药物发现, we are using Knowledge Graphs to harness vast networks of scientific data to give our scientists the information they need about genes, 蛋白质, 疾病和药物, 以及它们之间的关系——它们是如何相互作用的, 一起工作, 或者相互对抗. Having a better understanding of these relationships can assist research teams in finding important connections across the latest web of 生物 mechanisms and candidate medicines. 例如, we are now using disease-specific Knowledge Graphs to better understand complex multi-factorial diseases such as idiopathic pulmonary fibrosis and chronic kidney disease, 与BenevolentAI合作.
这种网络也可以通过新兴的人工智能驱动的语言模型生成, 比如ChatGPT, GatorTron and ClinicalBERT – technologies that could enable the analysis of vast amounts of clinical text and scientific literature. 重要的是, use of such types of models has the potential to help scale up the continuous improvement and repurposing of medicines for new disease indications.
数据科学改善临床实践和临床试验
Advances in data science and data utilisation are key to improving clinical trials and real-world evidence through which medicines are regulated and optimised. The quest for inclusive trials seeks fair representation of patient groups across all lived-experiences – including people from low- and middle-income countries or communities – who may be more likely to have an earlier onset of a wide range of medical conditions and be more at risk of having multiple long-term conditions.
电子健康记录是更好地了解患者的关键数据源, 无论是个体还是群体. 因为电子健康记录数据可以更好地获取, 链接和策划, 了解疾病风险和轨迹的机会有所改善.1-3 Such data also allow for optimised data processing that could be reused to improve clinical trials’ feasibility analyses, 招聘, 安全监督, 经济评估, 概括性研究和长期结果监测.
因果机器学习的最新进展有可能改善患者护理, 公共卫生措施, 服务质量管理, 规划和研究——包括临床试验. 例如, 机器学习方法，如卷积神经网络(cnn), 长短期记忆网络(LSTMs), and Generative Adversarial Networks (GANs) are starting to enable innovations such as the estimation of treatment effects or the generation of synthetically balanced case-control populations and ‘virtual control groups’. By using machine learning methods (and using data from collected from past clinical trials, 自然历史研究, 电子健康记录, 索赔数据, 或者疾病登记)来创建虚拟控制组, 澳门第一赌城在线娱乐可以将更多的研究设计从安慰剂对照组中移开. 减少对人为控制的依赖, more participants receive the innovative treatment rather than a placebo or standard care.
规划不仅仅是处方
Personal health information is evolving from passive clinical records into interactive combinations of records, 数据流和算法. 在世界的许多地方, the public are coming to expect more self-service access to healthcare and interaction with human or AI-driven services, between their in-person contacts with clinicians – increasingly reflecting how people live their daily lives in a connected world. 例如, phone apps that integrate and enhance care are becoming more and more common in regular clinical practice as well as part of clinical trials. 此外, it is theoretically possible to produce a companion AI for medicines that augments drug regimens (e.g. 通过药物基因组学实现个性化), 支持用药经验，并为研究人员和监管机构提供丰富的反馈.
为了满足患者的需求，澳门第一赌城在线娱乐的目标是交付 无摩擦的临床试验经验 在试验期间和之后无缝地融入参与者的生活. 澳门第一赌城在线娱乐实现这一点的一种方式是通过Unify. Unify是一款汇集了一系列应用程序的应用程序, 将网站和设备整合为一个易于使用的单一工具，使数据收集成为可能, streamline the experience for trial sites and support patients during the trial and beyond. Unify is designed to foster the connection between the physician and patient and enhance the effectiveness of their relationship to achieve the best clinical trial experience possible.
完全连接的药物可以被认为是药物和人工智能的治疗包. 对于最佳患者, 药物的提供者和社会结果, 这些技术和更广泛的框架需要在全球范围内采用. 尽管这带来了内在的挑战, we are confident that we can make progress by listening to and learning from patients while continuing to innovate with our digital and AI-led technologies that bring us closer to connected medicines.
澳门在线赌城娱乐的数据科学和人工智能
在澳门在线赌城娱乐, 澳门第一赌城在线娱乐利用数据和技术加速潜在新药的交付, 创新驱动效率和成功, 开拓工具和技术，保持澳门第一赌城在线娱乐的竞争优势. 澳门第一赌城在线娱乐是 嵌入数据科学和人工智能 在所有的R上&D活动, 从目标识别到临床试验, to identify new opportunities to push the boundaries of science to deliver life-changing medicines.
