Laboratory Automation
Intelligent, automated laboratory instruments are helping labs run more efficiently and deliver more advanced testing services while setting the stage for AI-driven workflows and procedures.
Are You a Developer?
Accelerate your path to production with developer tools and resources at the Intel® Developer Zone, your official source for developing on Intel® hardware and software.
What Is Lab Automation?
Lab automation uses sophisticated laboratory information from management systems (LIMSs) and automated laboratory instruments to deliver precise, accurate test results at scale. These smart laboratory instruments use onboard processors to drive robotics, support Internet of Things (IoT) technologies, and perform sophisticated analysis.
Intel and Intel partners work closely with laboratory instrument manufacturers to help optimize applications, introduce innovative new technologies, and meet changing customer needs.
Build for Today, Design for Tomorrow
The instruments you ship this quarter will be in service for years to come. For instruments to stay relevant, they must be able to adapt to rapid innovation especially in the areas of analytics and AI.
Laboratory instruments, powered by Intel®-based hardware, development tools and software, can access the computing performance they need to process intense workloads, adapt to next-level automation, and securely manage unprecedented amounts of data.
Automated Laboratory Instruments—Current Trends Driving Change
Clinical labs are facing shrinking margins and increasing demands for more sophisticated testing. Research labs are under constant pressure to create more breakthroughs, faster. Both markets are looking to instrument manufacturers to deliver smarter devices that can perform advanced tests, automate more processes, and serve as platforms for future innovations.
Cost Pressures
Laboratories are seeking ways to improve operations while requiring that instruments do more and cost less. Shifting to single-CPU configurations can reduce materials costs, increase performance, and deliver better user experiences.
Remote Diagnostics
In lab settings, reducing downtime is critical. Integrated computer vision (CV) systems can support remote instrument diagnostics, which can help identify and resolve issues earlier and faster. Intel® hardware, developer toolkits, and reference applications provide the flexibility needed to build CV solutions for a range of instrument requirements.
Security and Manageability
Data security is a primary concern in the healthcare industry. Intel® computing platforms have hardware-enabled security technologies like accelerated data encryption and trusted execution technology, which help instrument manufacturers meet their cybersecurity needs.
Analytics and AI Growth
Modern lab instruments must be able to support increasingly complex analytics and—in the future—artificial intelligence. The latest Intel® technologies combine AI acceleration with flexible, multipurpose computing performance. With an Intel foundation, lab instruments can support extended analytics and AI capabilities.
Customer Success Stories
TGen Unravels Genetic Mystery of Disease
Researchers are using high performance computing to develop genomic treatments for rare diseases.
KFBIO Accelerates Cancer Screening Throughput
KFBIO deep learning AI solutions detect and classify abnormalities in Pap smears. Using Intel® optimizations and toolkits, KFBIO increased throughput 8.4x1 on Intel® Xeon® CPUs.
Broad Institute Sees Return from Optimization
Intel and Google worked with the Broad Institute to reduce cloud computing costs and improve performance for their open source biomedical platform, Terra.
The Future of Lab Automation
Intel is helping manufacturers integrate new technologies that deliver value today and set the foundation for the future.
Empowering Digital Pathology with Intel
Intel makes it easy to scale digital pathology solutions with optimized software and AI model management platforms.
Powering the Future of Automation in Clinical Labs
Intel is helping blood banking and clinical chemistry instrument makers deliver new services and achieve higher throughput with computer vision, AI, and robotics.
Emerging Technology Trends for Research Laboratories
Intel® technologies, hardware, and developer tools are helping R&D labs put AI to work on big data analytics and autonomous experimentation.
Biopharmaceutical Manufacturing Goes Digital
Intel® hardware and software solutions are at the forefront of digital transformation in biopharmaceutical manufacturing, serving as the foundation for a move toward modern, software-defined, data-driven operations broadly known as Industry 4.0.
Intel® Technologies for Lab Automation
A single, modern Intel® processor has the performance lab instruments need to shift from hardware-defined logic to software-based infrastructure. With an Intel® CPU, today’s instruments can support years of expanding capabilities and increasing demands.
Enhanced-for-IoT processors combine real-time computing, out-of-band remote management, and hardware-based security measures with industrial-grade reliability for even greater performance and flexibility.
With Intel® hardware, you can manufacture multiple lab instruments—with a range of capabilities—using a standardized, single-CPU architecture, which reduces your bill of material, simplifies certification, and unifies device management.
Intel Atom® Processors
Intel Atom® Processors deliver power-conscious performance for on-instrument automation like sample handling, sorting, centrifuging, and analytical functions.
Intel® Core™ Processors
Intel® Core™ Processors have higher computing performance and Intel® Iris Xe graphics for advanced on-instrument analysis and workstations with 4K displays.
Intel® Xeon® Scalable Processors
With Intel® Xeon Processors, you can run multiple virtualized workloads on edge servers in the lab, including high-content screening (HCS), culture counting, and other image analysis.
Intel® FPGAs
Intel® FPGAs and SoC FPGAs can be programmed in the field to accelerate key workloads and adapt to changing requirements.
Intel vPro® Platform
Access systems even when they’re powered off for remote diagnostics, maintenance, and troubleshooting.
Intel® Deep Learning Boost
Run complex AI workloads side-by-side existing workloads for computer vision, speech recognition, and other deep learning AI.
Intel® Developer Tools for Lab Automation
Intel provides instrument manufacturers with tools that can extend the capabilities of their systems and simplify their development process.
Intel® Distribution of OpenVINO™ Toolkit
The OpenVINO™ toolkit creates optimized deep learning AI models that can run on any mix of Intel® hardware at maximum performance. Hundreds of pretrained models and reference applications can help you get to market faster.
Video Analytics Serving
Deploy optimized media analytics pipelines as container-based services. Video Analytics Serving supports pipelines defined in GStreamer or FFmpeg. It includes APIs to discover, start, stop, customize, and monitor pipeline execution.
Azure Video Analyzer
Build and deploy AI video analytics pipelines as a service using the Azure cloud. A Video Analytics Serving extension supports GStreamer and FFmpeg pipelines.
Intel® Media SDK
The Intel® Media SDK provides developers with a rich set of libraries, tools, and samples to enable hardware-accelerated video encoding, decoding, and processing in applications for Windows and Linux.
Frequently Asked Questions
Lab automation uses sophisticated laboratory information management systems (LIMSs), robotic material handlers, and increasingly smart laboratory instruments to track test samples, evaluate results, and perform labor-intensive clinical tasks.
Lab automation is used in clinical and biopharmaceutical research labs as well as manufacturing facilities. Materials research labs use automation to discover new compounds and molecules.
Basic lab automation depends on automated laboratory instruments with onboard computing and high-speed networking. Instruments are assembled to create workflows that are managed by automated control systems and information management systems. High-performance workstations and on-premise or cloud-based servers support lab-wide automation and operational technology.
Artificial intelligence is making lab automation smarter and more autonomous. AI requires cameras, microphones, and other sensors to capture data plus additional software and computing power.
Related Reading
Learn about other advances in health and life sciences.
1. KFBIO Cervical Cancer Screening OpenVINO™ Model Throughput Performance on Intel® Xeon® Gold 6148 Processor:
NEW:
Test 1: Tested by Intel as of 6/15/2019. Two-socket Intel® Xeon® Gold 6148 processor, 20 cores, HT on, turbo on, total memory 192 GB (12 slots/16 GB/2,666 MHz); BIOS: SE5C620.86B.0X.01.0007.062120172125 (ucode: 0x200004d), CentOS Linux release 7.5.1804 (Core); Deep Learning Framework: Keras 2.2.4 and Intel-optimized TensorFlow: 1.13.1; topology: RetinaNet: https://github.com/fizyr/keras-retinanet; compiler: gcc 4.8.5, MKL DNN; version: v0.17, BS=8, both synthetic data and customer data, one instance/two socket, datatype: FP32.
Test 2: Tested by Intel as of 6/15/2019. Two-socket Intel Xeon Gold 6148 processor, 20 cores, HT on, turbo on, total memory 192 GB (12 slots/16 GB/2,666 MHz); BIOS: SE5C620.86B.0X.01.0007.062120172125 (ucode: 0x200004d), CentOS Linux release 7.5.1804 (Core); Intel® software: OpenVINO™ R2019.1.1094; topology: RetinaNet: https://github.com/fizyr/keras-retinanet; compiler: gcc 4.8.5, MKL DNN; version: v0.17, BS=1, eight asynchronous requests, both synthetic data and customer data, one instance/two socket; datatype: FP32.
BASELINE:
Tested by Intel as of 6/15/2019. Two-socket Intel Xeon Gold 6148 processor, 20 cores, HT on, turbo on, total memory 192 GB (12 slots/16 GB/2,666 MHz); BIOS: SE5C620.86B.0X.01.0007.062120172125 (ucode: 0x200004d), CentOS Linux release 7.5.1804 (Core); Deep Learning Framework: Keras 2.2.4 and Vanilla TensorFlow: 1.5; topology: RetinaNet: https://github.com/fizyr/keras-retinanet; compiler: gcc 4.8.5, MKL DNN version: v0.17, BS=8, both synthetic data and customer data, one instance/two socket; datatype: FP32.