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TetraScience

TetraScience

, the Scientific Data and AI Cloud, announced a key new collaboration with Microsoft that aims to accelerate the adoption of scientific AI to radically improve workflows across the entire biopharmaceutical value chain: drug discovery, development, manufacturing, and quality control. This collaboration combines the power of Microsoft’s secure Azure platform with the Tetra Scientific Data and AI Cloud.

科学数据和人工智能云（Scientific Data and AI Cloud）宣布了与微软的一项重要新合作，旨在加速采用科学人工智能，以从根本上改善整个生物制药价值链的工作流程：药物发现、开发、制造和质量控制。这种合作将微软安全Azure平台的强大功能与Tetra Scientific数据和人工智能云结合在一起。

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to empower scientific organizations with the ability to extract scientific insights from complex experimental data at an enterprise scale.

赋予科学组织从企业规模的复杂实验数据中提取科学见解的能力。

The collaboration arrives at a critical moment when pharmaceutical companies are racing to adopt AI but wrestle with unprecedented volumes of complex scientific data, much of it locked in proprietary formats and scattered across disconnected systems. Given the scope and urgency of the data challenge, the path forward for life sciences organizations is to migrate their scientific data into an open and modern technology stack purpose-built for scientific AI..

这项合作正值制药公司竞相采用人工智能的关键时刻，但却面临着前所未有的复杂科学数据量，其中大部分数据都被锁定在专有格式中，分散在断开连接的系统中。鉴于数据挑战的范围和紧迫性，生命科学组织的前进道路是将其科学数据迁移到专门为科学AI构建的开放和现代技术堆栈中。。

Microsoft and TetraScience deliver the four essential components of that scientific AI stack: massive computational power, advanced models, sophisticated scientific data ontologies, and deep scientific use case expertise. TetraScience is the only industry cloud purpose-built to replatform and engineer the world’s scientific data into powerful data models and domain-specific use cases.

Microsoft和TetraScience提供了科学AI堆栈的四个基本组成部分：巨大的计算能力、先进的模型、复杂的科学数据本体以及深入的科学用例专业知识。TetraScience是唯一一个专门用于将世界科学数据重新格式化和工程化为强大数据模型和特定领域用例的行业云。

The Microsoft Azure platform provides enterprise-grade infrastructure and serves as the computational backbone for even the most demanding scientific workloads, from real-time analytics to large-scale AI use cases..

Microsoft Azure平台提供了企业级基础设施，甚至可以作为最苛刻的科学工作负载（从实时分析到大规模AI用例）的计算骨干。。

The combined capabilities deliver immediate practical benefits to scientific organizations, seamlessly harmonizing data from hundreds of scientific instruments and vendor formats while maintaining the experimental context needed for multimodal analytics and AI model training. The best part? Scientists can focus more time and resources on science rather than dealing with data..

综合能力为科学组织带来了即时的实际利益，无缝协调了数百种科学仪器和供应商格式的数据，同时保持了多模式分析和人工智能模型培训所需的实验环境。最好的部分？科学家可以将更多的时间和资源集中在科学上，而不是处理数据。。

'The world's scientific data is trapped in millions of silos and locked in proprietary and incompatible languages,' says Patrick Grady, TetraScience Chairman and CEO. 'By joining forces with Microsoft, we're breaking down these silos and unlocking the full potential of scientific data to proliferate AI-driven use cases that will define the next century of scientific discovery.'.

通过与微软联手，我们正在打破这些孤岛，释放科学数据的全部潜力，以扩散人工智能驱动的用例，这些用例将定义下一个世纪的科学发现。”。

'It’s not enough to have data, you have to have AI-ready data,' says Elena Bonfiglioli, General Manager, Pharma, and Life Sciences, Microsoft. “Combining TetraScience’s expertise in scientific data and use cases with Microsoft’s leading AI and cloud capabilities, our joint customers will benefit from cutting-edge solutions that will empower researchers with insights for faster discovery and development cycles.”.

微软制药和生命科学总经理埃琳娜·邦菲奥利（ElenaBonfiglioli）说，拥有数据是不够的，你必须拥有AI就绪的数据。“将TetraScience在科学数据和用例方面的专业知识与微软领先的人工智能和云功能相结合，我们的联合客户将受益于尖端解决方案，这些解决方案将为研究人员提供更快发现和开发周期的见解。”。

The collaboration aims to improve processes across the biopharma value chain. In drug safety assessment, for example, scientific AI models trained on well-engineered data sets predicted IC50 values with fewer data points required, accelerating early-stage discovery by shortening screening times. At another pharma organization, scientific AI models classified cellular features and drug responses in high-throughput images far faster than humans can, accelerating the phenotype screening step critical in oncology and neurology.

该合作旨在改进整个生物制药价值链的流程。例如，在药物安全性评估中，在精心设计的数据集上训练的科学AI模型预测IC50值，所需数据点较少，通过缩短筛选时间加速了早期发现。在另一家制药组织，科学人工智能模型在高通量图像中对细胞特征和药物反应进行分类的速度远快于人类，从而加速了肿瘤学和神经病学中至关重要的表型筛选步骤。

At a third firm, AI co-pilots automatically flagged anomalies in system audit trails, which can streamline review processes in manufacturing, quality control, and GxP environments..

在第三家公司，人工智能联合试点自动标记系统审计跟踪中的异常情况，这可以简化制造、质量控制和GxP环境中的审查流程。。

The companies will engage with leading pharmaceutical organizations to demonstrate the real-world impact of liberated data with AI for scientific discovery. The combination of TetraScience solutions with Microsoft data platform capabilities has the potential to accelerate scientific workflows and make data collaboration accessible to research organizations of all sizes..

这些公司将与领先的制药组织合作，用人工智能展示解放数据对科学发现的现实影响。TetraScience解决方案与Microsoft数据平台功能的结合有可能加速科学工作流程，并使各种规模的研究组织都可以访问数据协作。。

About TetraScience

关于TetraScience

TetraScience is the Scientific Data and AI Cloud with a mission to improve and extend human life radically. It is accelerating the Scientific AI revolution by designing and industrializing AI-native scientific datasets, which it brings to life in a growing suite of next-generation scientific data and lab data automation products and AI-enabled scientific use cases.

TetraScience是科学数据和人工智能云，其使命是从根本上改善和延长人类生命。它通过设计人工智能原生科学数据集并将其产业化，加速了科学人工智能革命，并在不断增长的下一代科学数据和实验室数据自动化产品以及人工智能支持的科学用例中赋予了生命。

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