Written by:
数据科学和定量生物学执行董事，Discovery Sciences, R&D
VP and Head of Genome Analytics & Bioinformatics, Centre for Genomics Research, Discovery Sciences, R&D
Artificial Intelligence (AI) is rapidly turning science fiction to science fact. 无人驾驶汽车只是一项以前不可想象的技术的一个例子，它试图利用数据科学和人工智能来彻底改变澳门葡京赌博游戏的出行方式. 人工智能也有可能改变澳门葡京赌博游戏发现和开发潜在新药的方式.
At AstraZeneca, we are using data science and AI across R&D to collate, connect and analyse different data and information. This will help us better understand disease, identify drug targets with a higher probability of success, recruit for and design better clinical trials and, we hope, ultimately speed up the way we design, develop and make new medicines.
Our work focuses on better understanding the fundamentals of disease, enabling AstraZeneca to find new ways to treat, prevent, modify and eventually even cure disease. This, combined with a more data-driven culture, has the potential to really change how we do our science. Here are some of the ways we use data science and AI in our day-to-day work, 帮助澳门葡京赌博游戏追求先进的科学，创造潜在的创新药物;
Building disease understanding through knowledge graphs
如果你曾经问过谷歌或Alexa一个问题，你就会用到知识图谱. 它们是令人难以置信的信息库，可以发现数千个不同来源之间的联系，从而找到你需要的答案.
每年，可供研究人员使用的科学信息和数据的绝对数量都在增长. At AstraZeneca, 澳门葡京赌博游戏现在开始利用这些庞大的科学数据事实网络，为澳门葡京赌博游戏的科学家提供他们需要的有关基因的信息, proteins, diseases and drugs, and their relationships – how they interact, work together or work against each other.
By using AI and machine learning to combine information from multiple sources, 澳门葡京赌博游戏希望得出比人工分析所有这些数据更好更快的结论. 人工智能也有可能发现以前未被探索过的模式，这些模式对人眼来说不是很明显，澳门葡京赌博游戏希望这将导致对疾病和澳门葡京赌博游戏设计治疗疾病的药物的新理解.
Our knowledge graphs allow researchers to ask key questions about genes, diseases, drugs and safety information to help identify and prioritise drug targets. And, as our data and knowledge continues to evolve, 澳门葡京赌博游戏的图表也是如此，这意味着每个新实验都将受益于之前学过的东西.
Ultimately, 澳门葡京赌博游戏想开发个性化的知识图谱，把正确的信息带给正确的科学家, 在适当的时候，这样每个人都可以在促进澳门葡京赌博游戏的理解中发挥自己的作用.
Advancing genomics research with big data and AI
澳门葡京赌博游戏的基因组研究中心(CGR)团队正在努力工作，到2026年分析多达200万个基因组序列. 获得这些丰富的信息意味着澳门葡京赌博游戏希望能够识别出这些变异, genes, pathways or other parts of the genome that are likely to cause disease, predict its progression and response to treatment. All of this, integrated using knowledge graphs, aims to help us better understand diseases and how they work, identify new drug targets and design better clinical trials.
Through access to hundreds of thousands of exome sequences, 澳门葡京赌博游戏的专家团队开发了定制的分析框架来研究人类疾病的遗传基础. 从CGR中产生的见解目前包括确定候选药物靶点, exploring repositioning opportunities, leveraging natural genetic variation for human safety assessment, understanding market opportunities based on population genomics, 并对目标命题进行实时人类基因验证/无效验证.
这些丰富的基因组数据加上专家应用程序使澳门葡京赌博游戏的团队能够专注于分析和解释数据，以推动科学发展. For example, 澳门葡京赌博游戏正在构建新的基于机器学习和深度学习的方法，以更客观地优先考虑可能导致疾病的基因或基因组的其他部分.
Using AI to get the most from every experiment
CRISPR gene-editing technology plays a significant role in drug discovery. We can use the technology in functional genomics screens, 按顺序删除基因组中的每个基因，以了解这些基因在生物学中扮演什么角色. And in cancer research, we use CRISPR to identify which genes, when deleted, lead to resistance or sensitisation to our cancer medicines.
To get the most from every experiment, 澳门葡京赌博游戏正在训练机器学习和深度学习模型，以增加澳门葡京赌博游戏对数据的信心，并分析CRISPR屏幕的基于成像的输出. 这可以增加屏幕上可用的信息，帮助澳门葡京赌博游戏更快地得到答案.
Beyond disease understanding
数据科学和人工智能对澳门葡京网赌游戏的重要性并不局限于疾病理解. AI is already being embedded across our R&D, 使澳门葡京赌博游戏的科学家能够从澳门葡京赌博游戏的成像数据中看到更多，并加快临床试验的设计.
一种潜在的新药在开发过程中失败的一个常见原因是它会对肝脏造成伤害. But it is challenging to predict liver toxicity pre-clinically. 为了解决这个问题，澳门葡京赌博游戏创建了采用贝叶斯方法进行机器学习的模型，即.e. which take a probabilistic approach to inference. 这些模型分析了许多安全性实验的数据，以预测一种潜在的新药是否可能导致肝损伤, 最关键的是在所谓的后验预测分布中捕捉每个估计的不确定性. 这改善了决策，有助于确保只使用具有可接受副作用的药物.
这和许多其他令人兴奋的人工智能应用意味着澳门葡京赌博游戏正在学习如何最好地利用这些新技术并进一步自动化流程, 让澳门葡京赌博游戏的人民有更多的时间做他们最擅长的事情——推动科学的发展，提供改变生活的药物.
