Enhancing drug discovery with laboratory informatics and automation

Listen to this article on the DDW Podcast:

Laura Marozsan, Scientific Marketing Specialist, Thermo Fisher Scientific, outlines the benefits  of automation in drug discovery.

Automation plays a crucial role in modern drug discovery, enabling improvements in efficiency, standardisation, reproducibility and data integrity. An effective automated laboratory contains two main components, physical automation and a unified digital infrastructure. While physical instruments automate the analyses themselves, digital infrastructure is key for connecting the instruments and automating data driven processes. A unified digital infrastructure allows for data to be collected and stored in a single data lake which allows artificial intelligence systems to perform machine and deep learning.

Laying the groundwork for complex digital systems is a critical first step, and systems such as a Laboratory Information Management Systems (LIMS) provide the link from physical instruments to analytics tools to manage data effectively and holistically. This is particularly important for drug discovery laboratories, where producing high quality data to inform research decisions and ultimately identify potential therapeutics is a primary focus. Furthermore, as there are ever-increasing volumes of complex data that need to be managed, this digital infrastructure becomes invaluable.

A need for digital transformation

Digital transformation sees the integration of digital technology into every aspect of a business, revolutionising its operations and processes to improve value, efficiency and productivity. Automation has a significant part to play in digital transformation, as manual tasks are handed over to technology.

There are three main drivers of digital transformation: new scientific terrain, digital disruption and shifts in science economics. The new scientific terrain can be seen through the rise of new technologies which enable more advanced therapeutics such as personalised medicine, biologics, and mRNA vaccines and therapies. The traditional approaches once used for R&D no longer work when, for example, a scientist is trying to locate the specific mechanism of action for a drug to treat a complex and ultra-rare disease. Research teams need to use new technologies and methodologies to create treatments for new complex diseases. Additionally, innovative treatments have led to increased quality regulations, which in turn has resulted in more stringent safety checks for the new technologies.

Big Data is increasingly applied to advance research through machine learning. As science is evolving, so is the technology driving it. Developments, such as advanced analytics and data visualisation, Internet of Things (IoT), AI and even quantum computing, are creating opportunities for laboratories and leading to digital disruption. Laboratories have become faced with needing to adopt these technologies or risk falling behind the competition.

The third factor influencing transformation is the worldwide shift in scientific economics, with increasingly globalised scientific operations, cloud and platform economics, and the growing role of data as currency. This factor became all the more important during the global Covid-19 pandemic, when scientists worldwide were required to come together and work more efficiently than ever to create vaccines and therapies for Covid-19. According to a new McKinsey Global Survey1 of executives, companies have accelerated the digitization of their customer and supply-chain interactions and of their internal operations by three to four years. Additionally, the share of digital or digitally enabled products in their portfolios has accelerated byseven years.

Digital transformation brings real, tangible benefits, enabling laboratories to survive in today’s rapidly changing environment. By automating processes and performing intelligent analyses of data to identify trends and opportunities, laboratories can maximise productivity, while controlling costs.

Advantages of automation

To address the challenge of analysing more samples in less time, laboratory automation tools are becoming increasingly vital to scientific operations. With automation, scientists can achieve high levels of throughput and processing that is not possible with manual methods, while also reducing error rates. This leads to overall improvements in data quality, along with a high degree of reproducibility and standardisation. Consistency is also enhanced. For example, automated pipetting is more reproducible and precise than manual pipetting as it reduces the margin of error and eliminates the difference in user technique.

Laboratory automation specialists have engineered significant improvements to enhance the flexibility of laboratory automation systems, particularly through developments in modular systems. Modern platforms are easily configurable giving scientists the flexibility to adapt to many applications, and there is greater potential for bespoke customisation to accommodate laboratories’ specific requirements. An additional benefit of adopting laboratory automation systems is that they can free a scientist from performing repetitive and reproducible manual tasks, allowing them to focus on what they do best: creative and innovative research.

Informatics plays a pivotal role in automation

Data is the ultimate end-product in the laboratory, and therefore its integrity is key. Automated instruments can help generate data, but using informatics tools, such as LIMS, is essential to track and manage data in order to maintain its value.

Informatics tools ensure that efficient, compliant data management is upheld in accordance with FAIR principles, whereby data is findable, accessible, interoperable and reusable. This FAIR concept means data must be findable and accessible between systems and scientists, and be of sufficient quality to be re-used with confidence. Informatics tools store and track data to ensure its integrity and quality for downstream analysis, and enable data audits to be streamlined.

Through integration with automated instruments, informatics tools enhance process management. Digital solutions facilitate instrument operation monitoring, enabling improvements to scheduling and resourcing, leading to productivity gains. For example, inventory management is optimised as restocking resources can be taken care of automatically. Informatics tools alert when stocks are low and can place or recommend repeat orders to maintain an optimum stock level within the laboratory.

LIMS software is the ideal digital solution for those working in drug discovery, having been designed with the needs of the laboratory in mind. LIMS supports laboratories to better connect instruments and databases, providing the infrastructure for machine and deep learning, and ensuring total management of samples and their associated information. With LIMS, data quality and productivity can be improved, and researchers and laboratory technicians can gain the reliability and flexibility they need in order to confidently perform complex work, such as next generation sequencing and pharmacokinetic and immunogenicity studies. Furthermore, an integrated LIMS solution allows scientists to collaborate and share their work with ease.

Overcoming the barriers to adopting laboratory automation

Despite the clear advantages of digital transformation and automation, there are still some perceived barriers to adopting fully automated science. These barriers typically fall under four broad categories, including:

  1. Physical interaction: concerns related to how reagents, consumables and samples are physically supplied to automated instruments.
  2. Digital interaction: apprehensions include how to schedule, initiate and track work remotely.
  3. Monitoring and error handling: there are fears about how this might be managed remotely and whether tools are truly able to recognise errors reliably.
  4. Service and support: concerns centred on aspects such as planning downtime.

Additionally, there are barriers stemming from the perceived rigidity of automation systems, with concerns they will not fit into existing laboratory infrastructure. Furthermore, costs and disruption associated with implementing automation processes are often cited as a barrier.

Fortunately, with modern integrated automation technology, these challenges can be easily overcome. Worries about physical interaction can be alleviated with plates reloaded overnight using autonomous vehicles, and conveyors used to supply equipment. Meanwhile, cloud-based technologies and informatics software solutions allow scientists to overcome the fears of digital interaction. Researchers can schedule, initiate and track work remotely to view the science in real-time. Camera monitoring, remote access and control, together with automated error recovery helps support robust monitoring and error handling. Moreover, the development of “maintenance-free”, predictive tools with IoT-enabled diagnostics and predictive maintenance removes issues surrounding service and support.

The advent of modular automated systems means that existing laboratory infrastructure can be accommodated, with the flexibility to create the right set-up for each individual laboratory’s needs. This flexibility allows systems to easily scale to accommodate future capacity requirements.

While there are undeniably significant costs, and some disruption, involved in committing to automation, it is undoubtedly a smart investment for future growth and achieving a competitive advantage. Laboratories that have already embraced automation are reaping the rewards, as highlighted by the St. Gallen Quality Metrics Research Report commissioned by the FDA2. In this research, key performance indicators were monitored, and high performing laboratories were noted to have significantly higher levels of automation. While the report focuses on QC laboratories, it also offers useful insights for drug discovery laboratories into the tangible benefits of informatics and automation.

Automation is now a strategic imperative

In order to deliver the benefits of automation and accelerate the delivery of new treatments to patients, instruments and software systems need to be better connected. Using advanced informatics solutions, such as LIMS, increases connectivity within the laboratory and ensures data is of the highest quality and securely accessible across the organisation.

Advanced informatics solutions can help drug discovery laboratories reach higher levels of throughput, reproducibility and standardisation. The gains in productivity and efficiency indicate the initial costs of informatics and automation are soon recouped. Ultimately, informatics and automation solutions play a vital role in driving automated science and should be a strategic imperative for all drug discovery laboratories.

Volume 22, Issue 3 – Summer 2021

About the author

Laura Marozsan is a Scientific Marketing Specialist at Thermo Fisher Scientific. Marozsan’s current professional focus is expanding the use of digital technologies to accelerate the drug discovery and development process. Prior to joining Thermo Fisher, Marozsan worked in bioanalytical development at Alexion Pharmaceuticals. She has a Bachelor of Science degree in Biology and a minor Neuroscience from the University at Albany.


  1. How COVID-19 has pushed companies over the technology tipping point — and transformed business forever. McKinsey & Company; 2020.
  2. Friedli, T. et al. FDA Quality Metrics Research Third Year Report. University of St. Gallen; 2019.

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