DDW Editor Reece Armstrong examines some of the science that has emerged in the last year that is driving the conversations at SLAS 2026.

SLAS always provides a great opportunity to assess what topics are in the minds of scientists within the drug discovery and development sector and this year is no different. The exhibition’s focus on technology provides attendees with ample chances to learn about how systems could impact their own work and engage in exciting discussions about what the future of drug discovery looks like. 

With a range of educations sessions covering technologies such as AI, automation, nanotechnologies and more, what research have we seen lately that we can expect to drive these talks?  

AI & Machine Learning  

Perhaps the most ubiquitous topic in life sciences at the moment, the rise of AI and machine learning is raising serious questions about how drug discovery can be advanced through the use of these technologies.  

At the end of 2025, Insilico Medicine went public on the Hong Kong Stock Exchange, raising a total of $292 million in its IPO and highlighting a strong backing for AI in drug discovery. With investors ranging from large pharma, tech conglomerates and more atypical funding, Insilico’s IPO demonstrates that a close eye is being kept on the opportunities that AI offer life sciences.  

Last year too saw multiple collaborations between organisations aiming to utilise AI to improve drug discovery and our understanding of human biology. A collaboration between ARC Innovation at Sheba Medical Center, Icahn School of Medicine at Mount Sinai and NVIDIA is exploring how AI can enable researchers to understand the unexplored regions of the genome.  

Quantum company IonQ also announced a partnership with the Centre for Commercialization of Regenerative Medicine (CCRM) focused on accelerating next-generation therapeutics through the use of quantum and quantum-AI technologies.  

Projects from the collaboration are set to be launched in 2026 across Canada and Sweden and will focus on areas such as bioprocess optimisation, disease-modelling workflows, and quantum-enhanced simulation to support the design and manufacturing of advanced therapies.  

In terms of target identification, last year saw Charles River Laboratories and Valo Health identify a candidate for the treatment of lupus and potentially other autoimmune conditions. The discovery was made using an AI powered drug development solution that has been trained on predictive models which the companies hope will enable their candidate to be ready for IND-enabling studies.  

The rise of companies utilising AI to bring molecules into the clinic has meant that regulatory agency have had to adjust their review processes to keep up with an advancing industry. The FDA for instance has recently qualified its first AI tool to help drug developers evaluate fatty liver disease in clinical trials. The agency has also made steps to reduce animal testing using human-relevant models such as AI-based computation models of toxicity and cell lines, organoids, organ-on-a-chip systems and other New Approach Methodologies (NAMs). More so, to keep up with demands from the life sciences sectors, the FDA last year introduced an aggressive timeline to scale the use of AI within its own centres. The agency is now looking towards the use of generative AI to assist with the review process for new drugs.  

Cellular technologies 

Cellular technologies is a major focus at this year’s SLAS, with talks examining how these systems are being implemented throughout the drug discovery and development timelines, all the way from efficacy testing to considerations for regulatory filings.  

This year already we’ve seen researchers from the Francis Crick Institute and AlveoliX develop the first human lung-on-chip model that could hold promise for testing treatments against lung-based infections and diseases.   

The goal of the researchers was to recreate the battle between human cells and bacteria, specifically by recreating the lung’s air sacs to see how they respond to infection.  

More so, this chip can use stem cells produced from a single donor, making it ideal for personalised medicine approaches and to understand how infections are spreading across individuals with specific mutations, or even which antibiotics should be used to treat an infection. 

Towards the end of the last year, a centre dedicated to developing standardised organoid-based NAMs was opened in the US.  

The, US Standardized Organoid Modeling (SOM) Center will leverage the latest technologies to enable real-time optimisation of organoid protocols. The centre is looking to address reproducibility challenges seen throughout drug development, through the use of technologies such as artificial intelligence, robotics, and a variety of human cell sources to establish standardised organoid models. These models will hopefully be used widely by researchers and accepted by regulators, accelerating scientific discoveries and decisions. 

In the field of neuroscience, progress was made by researchers from MIT who developed a 3D human brain tissue platform that was the first to integrate all major brain cell types into a single culture.  

The culture, named miBrains, utilises pluripotent stem cells grown from individual donors which can replicate key features of human brain tissue. It’s a development which mirrors calls by the industry for models that better replicate human biology and could help drug developers better understand brain biology and treat diseases. The model has already been used to understand how a common genetic marker for Alzheimer’s disease can alter cells’ interactions to produce pathology.  

Biomarkers 

Biomarkers and screening applications are essential tools for drug developers who want to better understand disease progression and match therapies or molecules to drug targets. SLAS is covering the topic with sessions exploring how these technologies can improve patient care, the challenges of current screening applications, and what AI and big data mean for these technologies.  

Last year, a study published in CNS Drugs showed that hippocampal volume (HV) could be used as a reliable and measurable biomarker to assess clinical benefits in early Alzheimer’s disease. Study results show that a shrinkage of the hippocampus can be linked to memory decline and disease progression. More so, data show that the hippocampus of early Alzheimer’s patients responds to disease-modifying therapies.  

The researchers stated how multiple clinical studies, including lecanemab, donanemab, and valiltramiprosate/ALZ-801, show that interventions in cognitive decline are also associated with reduced hippocampal atrophy. These findings, and the subsequent development of non-invasive imaging-based surrogate markers, are something the authors from Duke University say could help accelerate Alzheimer’s drug development.   

Conclusion

These are simply a handful of the work that has gone on in the industry in the build-up to this year’s SLAS. The conference though will touch upon a wider remit of developments within the drug discovery industry, including how wearables are driving the age of personalised medicine, how omics are being utilised in various stages of drug development, and of course a look at some of the most exciting new modalities that are driving the therapies of tomorrow. Expect talks on targeted protein degradation, cytokines, multi-specific antibodies and more, all of which should give attendees an exciting overview of the current and future workings of the industry.  

From DDW Volume 27 – Issue 1, Winter 2025/2026 – Read the digital issue here