Along with many other industries these days, biotech companies are rapidly changing the way they do business by leveraging the use of Artificial Intelligence (AI) and Machine Learning (ML).  These cutting-edge technologies are leading the way to help shorten drug development timelines, improve compliance, and make laboratories more efficient. By integrating them into Electronic Laboratory Notebooks (ELN) and Laboratory Information Management Systems (LIMS), pharmaceutical companies can innovate and reshape how they capture, analyze, and utilize their data. Below, we explore the advantages of leveraging AI and ML in lab informatics. 

The Power of AI and ML in ELN &LIMS 

Traditional ELN and LIMS have been essential tools for managing lab experiments and data by ensuring traceability and compliance. With AI’s ability to mimic human decision-making and ML’s capacity to allow systems to learn from data, ELN/LES and LIMS platforms are evolving from a data storage solution into intelligent systems that are also able to accurately perform predictive modeling, automated analysis, and anomaly detection. Systems that use Natural Language Processing (NLP) tools can further enhance their capabilities by processing text from lab notebooks and making the data more accessible and actionable.   

Imagine an AI-powered ELN/LES/LIMS with the ability to instantly detect data errors or inconsistencies that can improve data integrity and reduce the risk of costly mistakes. Or, systems using ML algorithms that can predict experimental outcomes from large amounts of historical data, thereby accelerating research processes and increasing the chances of success.  

LIMS providers like LabWare, LabVantage, and ThermoFisher have integrated powerful data analysis tools within their ELN/LES/LIMS that make these scenarios a reality for their customers. With improved efficiency, the companies gain a strategic advantage by accelerating the time to market and enhancing compliance with regulatory agencies like the U.S. Food and Drug Administration (FDA).   

Looking Forward 

The impact of these technologies is already seen across the pharmaceutical industry.  As these technologies continue to evolve, we are seeing automated NLP functionality improve the documentation of records in R&D laboratories by automatically interpreting and processing a researcher’s notes into structured data that can be easily accessed and searched by other researchers.   

AI and ML algorithms are being used to not only predict when lab instrument maintenance is needed but also to design studies and forecast the success rate of drug trials. Laboratories using this new technology can additionally detect result outliers in real-time and avoid product loss and costly investigations.  The more this technology is used, the faster the capabilities advance, and the greater the possibilities for laboratories to enhance their efficiency, throughput, and data integrity.   

How Clarkston Can Help 

At Clarkston Consulting, we understand the benefits and challenges associated with integrating AI/ML with your laboratory systems and our experts are specialized in implementing ELN/LES and LIMS solutions that are tailored to your organization’s unique needs. Our team can help you harness the power of AI and ML to streamline your lab processes and improve overall compliance. Contact us today to learn how we can support your digital transformation.   

Contributions by Eric Borries