Automate to innovate: accelerating the move towards the laboratory of the future
Phenotypeca, a baker’s yeast biofoundry, is implementing automated laboratory technologies to build Lab 4.0. Based on Industry 4.0, which is sometimes called the Fourth Industrial Revolution, Lab 4.0 aims to exponentially increase laboratory throughput. This higher throughput will drive down unnecessary costs, speed up delivery and, most importantly, allow the scientists to do more science. With increased interconnectivity and smart automation, the final laboratory will be designed to be future-proof, reproducible and scalable.
More science, less waste
A significant proportion of research and development is required for laborious and time-intensive tasks, such as the handling of liquids between samples and copying data from platform to platform. Phenotypeca is aiming to reduce the amount of time spent performing repetitive and menial activities to focus on scientific talent on innovation and development. The intention is to deploy industry-standard liquid handling robots in combination with proprietary software to take the sting out of routine assays. Automating the pipetting process also increases pipetting accuracy and consistency. The company’s systems can be set up to automate and monitor the stages of sample handling and processing, which further aids with tracking and standardising experiments.
Internet of Things for the laboratory
The Internet of Things (IoT) describes the connectivity of multiple physical objects or systems. Most people have seen this change in their homes with the introduction of technology such as smart speaker-controlled lights, Wi-Fi enabled fridges and security systems connected to their smartphone. IoT benefits include convenience, connectivity and simpler monitoring. IoT can also be applied to the laboratory as well, with machines and instruments allowing continual monitoring, data collection and inventory management. With everything connected, workflows are streamlined, and actions recorded, which reduces the effort whilst increasing the data integrity. Examples of the IoT-connected laboratory include automated inventory management systems with barcoded consumables, experimental sample tracking and touchless balance output.
Phenotypeca use a secure online system of electronic lab books and protocols. This leads to a reduction in paper usage, a standardised format of knowledge transfer and instantly backed up, secure storage. Storing all data electronically allows better organisation of information output, saving time by allowing standard operating procedures and protocols to be easily accessible from anywhere in the laboratory. Reducing paper use also aligns with the firm’s environmental goals, minimising the contribution of waste to the environment and reducing the need for space and equipment to store the data.
Artificial intelligence and machine learning
Artificial intelligence (AI) is the use of algorithms and software to mimic human cognition. AI is not a replacement for scientists but allows the computers to focus on repetitive tasks and the scientists to focus on the science. Machine learning is a branch of AI that uses algorithms to recognise patterns in data and apply this learning to influence decisions on how to handle it. With the right programming, AI can handle experimental modelling, data analysis and evaluation tasks, while Phenotypeca’s human scientists take on the tasks of higher understanding and project goal refinement.
Design of experiments
Often in science, it is understood that multiple factors influence an experimental output, for example, looking at the impact of both temperature and pH on cell growth. Design of experiments (DOE) is a technique that can analyse both the individual and combinatorial effects of factors that influence an experimental outcome without testing every combination. DOE allows Phenotypeca to efficiently look at the whole experimental space. For example, this technique can find the exact optimal condition for protein production in the company’s baker’s yeast biofoundry by varying the input of multiple factors and using powerful statistics to untangle the interactions.
Super-fast feasibility studies
With an automated laboratory, Phenotypeca can increase the throughput of customer feasibility studies to find out whether a customer’s recombinant protein product can be produced in its optimised panel of key yeast strains. These rapid screens, which can be completed within a matter of weeks, save its customers both time and money when searching for the appropriate product platform, allowing projects to ‘fail fast’. If the project feasibility study is successful, its customers can move to the next stage of the project where the firm can rapidly screen over one billion genetically diverse yeast strains, and then quickly to market with a robust low-cost product.
A genetically diverse library of 1 billion yeast strains
Phenotypeca’s platform offers an advanced approach to baker’s yeast breeding technology that can generate genetically diverse libraries of one billion unique genotypes, maximising the chance of finding most effective production strains for its customers. Its libraries are the product of breeding together four parent strains of baker’s yeast from diverse ecological and geographical niches over multiple generations to create a surpassed library of strains. Laboratory automation alongside population screening techniques, such as flow cytometry, enables the company to screen and identify the right strains quickly and accurately.
More scientist years per calendar year
Ultimately, the automation of the laboratory aims to remove non-value-added activities from a scientist’s day, allowing many more scientist years of output per calendar year. With more scientist years available, innovation can progress at an accelerated rate.
Keith Williams, director of Phenotypeca says: “Applying the Lab 4.0 approach will significantly increase our output, enabling our customers to have industrial strains that reduce the cost of goods of medicines and hopefully reduce the regulatory approval timelines. Our goal for our company, and the aim of this project, is that by using Lab 4.0 principles, we can achieve 10 science years output per calendar year from every one of our highly skilled scientists. This is the latest initiative in our mission to make life life-saving medicines more accessible and affordable to all that need them.”