In recent years, researchers have benefited from rapid advancements in analytical instrumentation, particularly in respect to liquid chromatography (LC). As a result, the use of LC in labs across the globe has increased, with 47% of labs globally now using LC-MS systems.
Pharmaceutical labs in particular have expanded their use of LC and it has quickly become a must-have for every stage of the drug discovery process, from drug development to quality control. By the close of 2023, 58% of labs in the pharma/biopharma industry were using LC-MS systems. The pharmaceutical industry has also taken advantage of recent developments in automation. However, there is scope for automation to be more widely adopted, and pharmaceutical labs should investigate how they can make use of new developments in automation to ease and improve their workflows.
Why Automate the Lab?
Resource management is central to pharmaceutical labs, who must ensure resources are handled in the most time- and cost-effective manner. Automation can bring real benefits to lab resource management, especially in terms of time savings and productivity, as it can take ownership of repetitive tasks and give time back to scientists to focus on life-changing research.
For example, specialist scientists are often required to perform or oversee sample preparation and loading, in addition to interpreting and reporting results. Sample prep and loading consumes valuable time that could be better spent analysing and extracting valuable information from results. The manual input required for sample loading also means that many workflows cannot be left to run overnight, as human input will be required to unload the sample and reload the next batch once a sample run has been complete, which further limits the efficiency of the lab.
Another challenge relates to the identification and elimination of errors. Lab errors can arise from a variety of sources, including environmental, procedural, and instrumental, but humans are most often the lead cause. In fact, it has been widely speculated that anywhere between 23% to 80%+ of total errors in manufacturing are the result of human error, a statistic which can also be applied to the laboratory setting. In a repetitive, high-throughput daily routine, it is inevitable that scientists will make mistakes – for example, mislabelling vials, introducing contamination into samples, or incorrectly preparing or loading samples.
Such errors must be identified swiftly as they can prove to be dangerous and costly. In extreme cases, failure to identify errors can result in FDA warning letters/483 observations, which are used to communicate concerns following an FDA inspection. Although 483 observations do not incur a fine, they enter the public domain5 and can consequently have a detrimental effect on company reputation.
