Lab of the Future

The SLAS Lab of the Future initiatives focus on the integration of new technologies into the laboratory, particularly those that increase automation of workflows as well as connectivity within and between labs. The SLAS Lab of the Future also emphasizes the integration of the human element in the Lab of the Future, interrogating not only what the role of the human operator in the Lab of the Future will be, but also how do we ensure that the Lab of the Future makes things easier for the human operator and does not simply increase pressure on productivity and contribute to burnout.

AI 101 Training Course – Online

This workshop offers a gentle introduction to the field of AI. The course will cover the three main branches of AI and machine learning: supervised, unsupervised, and reinforcement learning. Each topic will include a case study to illustrate how AI is used to solve data-intensive problems.

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Short Course – In Person

The Lab of the Future short course is designed to provide the framework, skills and knowledge to assist participating organizations in the design and implementation of automated laboratory workflows that are tightly integrated with modern AI machine learning strategies.

Under the guidance of a skilled instructor, participants will learn topics ranging from analyzing laboratory layouts to selecting optimal machine learning strategies to achieve their goals.

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2022 AI Data Pipelines for Life Science Symposium – Event Recordings

This two-day symposium will allow participants to explore how AI data pipelines are integrated into the life sciences. Attendees will learn about MLOPS, applications, techniques, and architectures of data and their uses in the life sciences.

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2021 AI-Powered Drug Discovery Symposium – Event Recordings

Learn more about the various AI tools available today as well as discuss future drug discovery collaborations involving the cutting-edge advances in AI, machine learning and computational science.

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Warm Up: SLAS AI in Process Automation – Webinar

Join the SLAS Scientific Director, and the AI in Process Automation Symposium Program Committee members as they talk with Dr. Ngiam Kee Yuan, the Group Chief Technology Officer of the National University Health System (NUHS) Singapore, about his group's efforts to use data to develop virtual models that allow earlier prediction of disease and use of natural-language data to drive medical conclusions.

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The Connected Laboratory – Webinar

The lab of the future will be connected. But do the advantages outweigh the risks of connectivity? Connectivity presents advantages like seeing instrument status anywhere, anytime and also comparing usage and performance data from multiple sites. Connecting labs promises to help improve operational efficiency reducing costs and increase return on investment. But the challenges are not to be underestimated. In this talk, we will see how Tecan is building the lab of the future and discuss our strategies to manage the challenges and risks involved.

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The Materials for Tomorrow, Today – Webinar

For materials discovery, one needs to go beyond simple computational screening approaches followed by traditional experimentation. I have worked on the design and implementation of what I call “materials acceleration platforms” (MAPs), which are enabled by the confluence of three disparate fields, namely artificial intelligence (AI), high-throughput quantum chemistry (HTQC), and robotics. I will describe our efforts under the Mission Innovation umbrella platform around this topic.

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SLAS Technology – Towards robotic laboratory automation Plug & play: Survey and concept proposal on teaching-free robot integration with the lapp digital twin

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SLAS Technology – AI-driven laboratory workflows enable operation in the age of social distancing

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SLAS Technology – Towards an automated approach for smart sterility test examination

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