Thermo Fisher Scientific and SelectScience kicked off the Orchestrated Lab webinar series to provide holistic perspectives on the ever-changing laboratory environment. During the first webinar of the series, Ian Yates, Director of Enterprise Science and Innovation Partnerships at Thermo Fisher Scientific, shared a compelling perspective on automated science and the lab of the future. The webinar covered how digital solutions and lab automation are paving the way for innovation in the connected laboratory. Yates explained how technology-driven strategies can promote success and how automated science is a key driving factor.
Drivers for automated science
We are seeing scientific disruption in three main areas including the scientific terrain, digital disruption with new technologies, and the economics of the laboratory looking for ways to increase efficiency. Underlying this, data is becoming one of the laboratory’s most valuable assets. Those embracing digital transformation and adopting technologies are better at driving productivity and controlling cost.
Steps to driving digital transformation
Yates presented two lenses to consider when driving digital transformation: lab centric and data centric. The lab centric considerations include human experience, workflow, layout, and robotics. The data centric considerations include end-to-end data management, digital connectivity, advanced analytics, and AI. When asked how laboratories should begin an automated science or digital transformation journey, Yates suggested “It’s about understanding where one is starting the journey and mapping the current state of the digital or automation structure within the organization. Before rushing into transformation, know where you start and where you want to get to. Get a good understanding on the current situation and plan the roadmap to the future.”
Taking these lenses into account, there are three main steps to driving digital transformation:
Step 1 – Connect everything to make data available
Digital transformation is broad and complex, so the execution can be daunting with siloed data and disconnected teams. Take a step back and analyze the existing infrastructure to determine if the people or processes are currently disconnected. By connecting people, equipment, consumables, systems, and data, you make data available when and where it is needed.
Ensuring you have quality data that can be reused with confidence is key. Quality data is considered FAIR data (findable, accessible, interoperable, and reusable). This includes experimental data and operational data for an instrument. By connecting these two types of data, we can drive data integrity, enable compliance, and improve productivity.
Step 2 – End-to-end automation workflows
Productivity challenges can be addressed by automation – maximize throughput, enhance reproducibility, reduce manual handling errors, ensure flexibility to scale, adapt to changing workflows or technology available, decrease FTE hands-on time so scientists can add value.
Yates shared the Thermo Fisher Scientific™ Amplitude Solution as an example of the first and second steps, combining connectivity with workflow automation. Pairing Thermo Scientific™ SampleManager LIMS™ software and automation hardware created a truly integrated workflow with full end-to-end tracking to provide a high-throughput testing platform.
When Yates was asked about takeaways from delivering the Amplitude Solution, he said “The biggest takeaway for me was the power of collaboration in the face of a unique and common goal. And how do we keep that speed of scale. The other key takeaway was it demonstrates that automation and hardware by itself only gets so far, but digital infrastructure and result interpretation really gives result and productivity and reproducibility needed.”
Step 3 – Advanced analytics
The last step of digital transformation is making use of the data and enabling advanced analytics. Once the data is connected and workflows are optimized, it is possible to look at the collected data through advanced analytics, allowing you to make informed decisions on the data and downstream activities.
Over the last decade, there has been a resurgence of machine learning in the form of deep learning, complemented by the explosion of data, availability of computing power and advancements in training algorithms and architectures. Ultimately, this leads to what Yates calls “goal-based or target-based science,” where systems tasked with delivering specific results iterate to learning as they go. This closed loop approach emerges as robotics and automated systems generate data which is interpreted by machine learning and used by artificial intelligence to select the optimal experiment to do next.
The idea of driving digital transformation through connectivity spans instruments and equipment, consumables, people, scientific workflows, and data.
A roadmap to the labs of the future
When working towards digital transformation, it is not enough to transform only one lab. Data must be accessible through the entire process, not only one lab or one function but the entire organization. To reap the benefits, the entire end-to-end process needs to be transformed to accelerate new treatments to patients.
Yates explained there are three layers of laboratories. First, the foundational layer where connected labs have adopted FAIR data and have applied using LIMS, ELN and software data management realizing productivity gains. The second layer is automated labs with application centric workflows, using robotics applying disruptive technology like autonomous carts seeing improved quality and reproducibility. The third layer is intelligent labs using everything and embracing all digital transformation has to offer. These include integrated workflow orchestrations, applying data science, AI and ML, and connected to other parts of the organization. Immersive technologies will be common in these labs with predictive support, service, and supply chains. These labs will gain the most seeing scientific acceleration through data intelligence.
Remember, it’s about the journey and not the destination. There is no one lab of the future as scientific and technological progress and continue. Adaption will always be necessary, and Thermo Fisher Scientific is here to serve you along your journey. To learn more about automated science, visit www.thermofisher.com/digitalsolutions. You can also watch a replay of the Automated science to create the Lab of the Future webinar is now available on-demand.