– Written by Will Greenway, Programming Manager at Plus-Project
Automation, once a buzzword of futuristic dreams, has increasingly become an integral part of our daily lives. From manufacturing to healthcare, automation has significantly reshaped how we operate, increasing efficiency, accuracy, productivity, reliability, and (often) safety. In this blog post, we briefly delve into the history of automation, its transformative possibility, and its crucial role in the pharmaceutical industry, particularly in the analysis and reporting of clinical trial data.
A Brief History of Automation
Automation refers to the use of technology and machines to perform tasks without or with limited human intervention, referred to as automation and semi-automation respectively. It involves creating and implementing systems that can operate and control processes automatically.
Automation may sound new but it has been around in various forms for centuries. Some of the earliest examples date back to the 1st century BC, with water wheels grinding grain into flour. Such semi-automation of tasks alleviated the heavy lifting of manual labour by using the power of falling water instead of muscle. In fact, throughout history there is evidence that people have strived to improve efficiency in day-to-day tasks, or simply to avoid having to do boring things!
However, arguably, the seeds of automation were more definitively sown in the 18th century with the advent of the Industrial Revolution, which introduced mechanised processes to streamline production. The assembly line, pioneered by Henry Ford in the early 1900s, revolutionised manufacturing by allowing for mass production of goods. This laid the groundwork for further automation innovations, including numerical control systems, programmable logic controllers (PLCs) and industrial robots.
With the rise of computers in the mid-20th century, automation transcended the physical realm and entered the era of information processing. Businesses began automating administrative tasks, data entry, and financial calculations, leading to increased accuracy and speed in decision-making processes.
Further fuelled by advancements in technology, computing, robotics, and even world-changing events such as the COVID-19 pandemic, the levels and types of tasks that can now be automated have dramatically increased.
Automation in the Pharmaceutical Sector
Clinical trials, the cornerstone of pharmaceutical research, generate vast volumes of data pertaining to patient demographics, treatment efficacy and safety profiles. Collecting, analysing and interpreting this data is historically a labour-intensive process that requires meticulous attention to detail and adherence to regulatory guidelines. Consequently, the pharmaceutical industry has embraced automation to enhance efficiency, reduce errors, and accelerate drug discovery and development – anything from simple tasks such as pre-population of dates on eCRFs to more complex work streams.
One area where great strides have been made, and which may be more evident, is the impact automation has made on the analysis and reporting of clinical trial data.
Automation in Clinical Trial Data Analysis
Automation can and has streamlined various aspects of clinical trial data analysis, from data collection and processing to statistical analysis and report generation. Increasingly, advanced software platforms and algorithms are automating repetitive tasks, reducing the risk of human error and expediting the analysis process.
Recently, machine learning algorithms and artificial intelligence (AI) techniques have been playing a pivotal role in identifying patterns, trends and correlations within clinical trial data, uncovering insights that might otherwise remain hidden. Although it may be evident that the automation of mundane tasks helps increase efficiency, improve productivity and reduce human error, it can also help, or even necessitate, the drive for standardisation and consistency. The embodiment of this comes in the form of cross-company collaboration efforts, including CDISC and PHUSE, which focus on standardisation, which in turn allows for automation, which then often demands more standardisation, each time pushing the boundaries of what is possible to automate.
With this cycle of standardisation and automation continuing, our roles are evolving. In the past, most of our time was spent programming and on administrative tasks, but slowly over time, as standardisation and metadata frameworks have improved, there has been more focus on the metadata, which can become the inputs to processes, and the interpretation of the output, leaving most of the time-consuming code to be automated and a reduction in administrative tasks.
Automation Indirectly Impacting on our Sector
There are also improvements going on outside our specific sector in the wider computing community that are having an impact. With advancements in technology, there is a wealth of tools available to aid our industry. One example is Microsoft’s Power Automate platform, which allows automated process flows to perform everyday tasks, such as updating MS365 files based on triggers or manual prompts. This type of automation can reduce the ‘extra’ tasks we need to do daily, allowing us to focus on where we bring the most value. Such tasks can often be run in the background, effectively doubling the use of our time.
It would also be amiss if I didn’t do a shout-out to the infamous ChatGPT and other AI tools that are slowly revolutionising the way we approach tasks. You can now simply ask an AI tool to write or help you understand code. It may not be perfect, but it can often get you a large percentage of the way there with very little effort, allowing you to review and finalise. This could be considered a form of semi-automation.
The Future of Automation in Pharmaceuticals
As technology continues to evolve, the role of automation in the pharmaceutical industry will only expand. Innovations such as blockchain technology, Internet of Things (IoT) devices, predictive analytics, and AI promise to further enhance the efficiency, transparency and reliability of clinical trial processes.
Moreover, the emergence of decentralised clinical trials (DCTs) and virtual trial platforms present new opportunities for automation to revolutionise the conduct and management of clinical research.
How Can I Get Involved in Automation?
As automation is touching so many parts of our jobs the options are (almost) endless. Although often written in programming or scripting languages including Java, VBA and Python, there are tools with a graphical user interface (GUI) that allow anyone to set up a series of actions without learning a single programming language.
In programming environments, there are often ways to set up some level of automation for programming, for example keyboard macros in SAS, automating data pipelines, validation, compiling of outputs, even out-of-office notifications based on calendar entries. When you think about it, there are lots of tasks that ‘you need to do’ that don’t need you to do them!
To get started, you only really need what most of us already have: a logical mindset and a drive to reduce boring, monotonous tasks from our to-do lists.
Conclusion
Automation isn’t new and yet over the last decade it has emerged as a transformative force in the pharmaceutical industry, offering unprecedented opportunities to streamline clinical trial processes, improve data quality and enhance patient care.
By embracing automation and leveraging cutting-edge technologies, pharmaceutical companies can usher in a new era of innovation and discovery, bringing life-saving therapies to market faster and more efficiently than ever before.