Nikhita Singh presents a case study that explores how one company has overcome the challenge of accessibility in lab automation.
With costs going down, integrators reducing the burden on teams and new software tools that capture data or connect instrumentation, fully automated systems are no longer only installed at high-throughput screening labs and Big Pharma screening groups. Instead, new tech-forward biotech companies are implementing these systems as they seek to address a labour shortage of skilled technicians, accelerate their discoveries and enable their scientists to focus on their next idea. As a result, biotech companies are faced with how they should adopt automation instead of whether they should or not.
3 Stages of the Automation Journey
For most companies, the automation journey is broken down into three stages. First, it starts with manual operations. Then, it moves towards a semi-automated system that typically includes a liquid handler and an analytical instrument such as a plate reader. Finally, it moves to a fully automated system with robots, liquid handlers and an array of instruments.
Due to costs or technical challenges, labs typically go through this process stage-by-stage. However, companies such as Beam Therapeutics, a biotechnology company pioneering the use of base editing, evaluated its return on investment (ROI) differently – it understood that the greatest drivers of operating costs – personnel and space – are actually best used with automation. So, Beam sought to go from manual to fully automated immediately so it could realise all of the benefits of automation routinely in its day-to-day operations.
What are the Benefits of Automation?
Beam’s mission is to leverage its cutting-edge science to provide life-long cures to patients suffering from serious diseases. The company knew that the most effective and efficient path to advancing this mission was through automation. While automation’s ROI is well known – the ability to miniaturise experiments and increase walk-away time and instrument utilisation – Beam also understood how automation could empower its scientists.
First, Beam wanted to establish a culture of automation amongst its scientists as it would alter the way they design experiments. With automation, the scale of their experimentation changes – they can test more variables, increase reps to power statistics, and ultimately accomplish more with smaller volumes in less time. Second, Beam wanted FAIR data capture without putting the burden on its scientists. With a fully automated system, scientists have a complete data capture of every single step in the process. Third, the company is rapidly growing its teams and wants its new employees to focus on scientific discovery and innovation, not spinning plates and moving liquids.
Identifying the Challenges in Automation
Although the benefits of automation are vast, many labs are intimidated by the costs and technical complexity. Fully automated systems have a multitude of instruments but each has its own software, which needs to be tied together to run smoothly. There’s also the challenge of building a data infrastructure so all the data is easily retrievable. Finally, automating assays isn’t a trivial task as translating a manual protocol into an automated equivalent can be challenging.
However, the lab automation market is changing – more vendors and integrators are working together to seamlessly integrate instruments, system prices are going down and the implementation process is getting easier. As well, many of the technical challenges can be easily addressed through software such as Artificial’s aLab Suite, HighRes Bio’s Cellario and Benchling. Instead, Bob Gantzer, director of Lab Automation at Beam Therapeutics, views the real challenge as accessibility. The complexity of these systems drives people away so most research is still being manually performed. To fully realise the benefits of automation, Gantzer believes the solution is through a non-intimidating user interface that is fully connected and as intuitive as using a smartphone.
Beam’s first fully automated system, affectionately named Ursula, is a next-generation sequencing (NGS) platform comprised of equipment from 11 different vendors including robots, liquid handlers, dispensers, heater/shakers and much more. To run jobs, Ursula is connected to a cloud-based LIMS (Benchling), a local scheduler (Cellario) and the cloud (AWS). Working with an integrator (HighRes Bio), Beam’s automation team overcame the early challenges of adopting and the company quickly saw the ROI of automation and started to empower ita scientists.
However, the firm realised that running Ursula was still intimidating as it required a high level of familiarity with the system. To run a request, a scientist needed to navigate multiple software interfaces and have a deep understanding of the local scheduler’s methods. Before the request can run, Ursula’s devices need to be set up appropriately, which can be very daunting given the number of instruments. This meant the scientists needed to have intimate knowledge on complex storage devices, liquid handlers with changing deck layouts, a multitude of plate types, and several other instruments they didn’t typically use. All of this combined together made it difficult for teams outside of the automation group at Beam to simply walk up and use Ursula.
Making automation accessible to all
To make Ursula accessible to all of its scientists, Beam’s automation team decided to implement Artificial’s aLab Suite. With full connectivity into Benchling, Cellario and AWS, aLab Suite provides one place to control, run and track Ursula so scientists only need to use one interface. They also don’t need to be familiar with each Cellario method as aLab Suite automatically selects the appropriate protocol. Scientists have customised guidance for the set-up of Ursula using aLab Assistants, eliminating the need to know every single detail of each instrument, plate and consumable. With aLab Suite, Beam’s scientists can easily operate Ursula to accomplish more with fewer resources in less time.
The automation landscape is changing. With decreasing costs, automation teams like those at Beam, and partnerships with integrators, the more traditional barriers to automation are easily addressed. Now, the question is no longer whether labs should adopt automation, but how to ensure the benefits of automation reach all parts of an organisation.
Nikhita Singh is c-founder and chief product officer at Artificial