In 2023, AI has become a trusted assistant among drug discovery and repurposing researchers since it has enabled scientists to discover novel molecules and identify secondary or tertiary use cases for existing drugs faster and more cost-effectively than ever before.
This includes within the laboratory and for wider research purposes. With the latter, the scientific publishing firm Elsevier released a ChatGPT-like artificial-intelligence interface for some users of its Scopus database.
Here, ChatGPT is a powerful tool that allows scientists to focus on analysing and interpreting literature reviews. Another area of application is within the laboratory, helping to accelerate scientific research.
According to Hanjo Kim, SVP of global strategy and head of medicinal chemistry at Standigm, the AI drug discovery company:
“Lab automation, a long-standing industry practice, has evolved from merely automatic ‘executions’ to include automatic ‘controls’ and ‘adaptations’ in the era of AI-powered research. This necessitates impeccable data quality, further emphasizing lab automation’s role in maintaining data integrity.”
The merging cohort of scientists who are more in tune with artificial intelligence are best placed to take advantage of the emerging scientific technologies.
As Kim has explained to Digital Journal: “As science progresses from molecular to organism levels, integrating AI models across various stages of drug discovery requires high data compatibility and substantial contextual data—both strong drivers for lab automation.”
In terms of how this is altering the make-up of the laboratory, Kim details: “Scientists are actively seeking innovative systems to intelligently complete missing values in multidimensional data matrices.”
This also coincides with the goals of many pharmaceutical firms, finds Kim: “In addition, the advancement of personalized medicine and better diagnostics has produced numerous compounds in smaller quantities. Ensuring data reproducibility from the early stages of research, even in medicinal chemistry labs, is integral to this process.”
Generative AI may well take the lead role. Here Kim observes: “Many researchers have also relied on tools like ChatGPT for writing research papers. The scientific community is keen to explore its potential in their daily routines and its capacity to create new methods for executing previously unimaginable lab tasks.”
GPT-4 is a state-of-the-art language processing AI model developed by OpenAI. It is capable of generating human-like text and have a wide range of applications, including language translation, language modelling, and generating text for applications such as chatbots. The platform is increasingly being used by researchers.
This leads Kim to conclude his assessment by noting: “The advent of AI technology is revolutionizing scientific methods in every aspect—it’s not a matter of if but when.”
