Anti-Infective Development Boosted by AI and Automation

Anti-infectives are a class of drugs used to treat or prevent infections caused by various pathogens, including bacteria, viruses, fungi and parasites. With the increasing challenges posed by emerging infectious diseases and antimicrobial resistance, accelerating the development of new anti-infectives has never been more urgent.

Robotics, artificial intelligence (AI) and machine learning (ML) are playing a pivotal role in reshaping the landscape of infectious disease research, particularly in the discovery and development of novel anti-infectives. These technologies are not only accelerating development timelines but also influencing future pandemic preparedness strategies.

By automating manual processes and uncovering previously inaccessible patterns in large datasets, these technologies enable researchers to accelerate various stages of the drug discovery pipeline, from early-stage screening to preclinical validation. The impact of AI/ML on drug discovery is already evident;  the first drug claimed to have been discovered and designed by generative AI, INS018_055, is currently undergoing Phase 2 clinical trials.

Liverpool School of Tropical Medicine (LSTM) will leverage these innovations to address challenges in anti-infective development through the creation of new AI-powered robotic labs, delivered by LSTM and the Infection Innovation Consortium (iiCON), which brings together industry, academia and the NHS to progress the development of antimicrobial treatments. The project has received a £10 million investment from the Liverpool City Region Combined Authority to support the build.

“These Category 3 high-containment facilities will be among the first of their kind in the UK to combine advanced robotics, automated liquid handling systems and AI/ML-driven analytics within a secure research environment capable of working with dangerous pathogens,” Dr. Mike Egan, senior business development manager at iiCON, told Technology Networks.

These tools will be designed with industry and academic collaborators to ensure they address real-world challenges in anti-infective development. “This includes the use of high-throughput automated platforms to process thousands of compounds rapidly, with AI algorithms then deployed to analyze biological responses, identify promising leads and predict efficacy and resistance profiles,” said Egan.

The labs will play a key role in supporting industry innovation, with commercial partners able to access and utilize this specialist facility to drive forward their infection R&D.  Research in the new labs will focus on LTSM’s organoid platform and bio-actives library. These platforms are designed to enable more physiologically relevant disease modelling and compound testing. While the development of 3D cell models can be time-consuming and laborious, robotic automation promises to significantly accelerate this process. “By automating these pathways, we not only speed up the production, but more importantly improve the reproducibility and consistency of the 3D organoids,” explained Egan.

This work automating organoid technologies aligns with recent announcements from the US Food and Drug Administration and European Medicines Agency who both shared plans to phase out animal testing in favor of human-based lab models. Alongside reducing reliance on animal testing, more human-relevant models can also help decrease late-stage clinical failures in drug and vaccine development.

“This approach supports the creation of more predictive models for human disease and contributes to the development of next-generation regulatory data packages, ultimately speeding up approval processes and improving patient outcomes worldwide,” said Egan.

Unlocking the full potential of AI in anti-infective development

One of the most significant challenges drug developers face is the huge amounts of complex data generated. When looking at anti-infectives in a pandemic situation, this data must be processed, interpreted and acted upon rapidly. “AI/ML offers a powerful mechanism for filtering these large datasets, identifying trends and generating actionable insights that would be difficult or impossible to detect using traditional analysis methods alone,” stated Egan.

However, implementing AI is not always straightforward and presents numerous technical and operational challenges. As Egan explained, “These include the need to ensure data integrity and interoperability, the integration of heterogeneous biological and clinical data sources and compliance with stringent regulatory and biosafety requirements – particularly within high-containment environments.”

Key to the success of implementing AI in LSTM’s Category 3 laboratories is investment in high-security infrastructure and leveraging the expertise and capabilities of its partners across academia, industry and the NHS.

“Through active collaboration with organizations operating Category 2 robotic laboratories and commercial AI platforms, we are building a robust knowledge base and set of best practices that will underpin the successful deployment of AI in our new facility,” said Egan.

With the lab refurbishment work set to be completed this year, and validation of the facility to follow shortly after, LSTM hopes to see the facility open in early 2027.

Egan is optimistic that these facilities will significantly speed up the development of new anti-infectives: “In summary, the integration of robotics and AI marks a paradigm shift in how infectious disease threats are addressed—ushering in an era of rapid, data-driven innovation that holds the potential to transform global health outcomes. These labs will be crucial in fostering industry collaboration, offering commercial partners access to cutting-edge resources that will drive forward infection-related R&D,” he concluded.