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At ELRIG’s Drug Discovery 2025, Drug Target Review spoke with the teams turning big ideas into usable tools – automation, AI and biology – that help scientists work smarter.
Automation now plays a central role in discovery. From self-driving laboratories to real-time bioprocessing, this report explores how data-driven systems improve reproducibility, speed decisions and make scale achievable across research and development.
Cellarity has published a new paper in detailing an AI-powered framework that integrates single-cell transcriptomics to make drug discovery faster and more successful.
Nature’s pharmacy has yielded half of today’s medicines, yet most of its potential remains untapped. AI is now changing how quickly new therapies can be found.
Within3’s Jason Smith explores how artificial intelligence is breathing new life into next-generation launch situation rooms; delivering actionable insights for pharmaceutical companies.
Vish Srivastava considers the benefits of expanding the role of real-world data in drug discovery to provide improved therapies, faster and with greater success.
Organoids are changing the landscape of biomedical research, with automation and AI driving new levels of consistency, scalability and human relevance. Aaron Risinger of Molecular Devices discusses how these technologies are advancing precision medicine – and the challenges that remain.
Dublin-based biotech Meta-Flux has raised €1.8M ($2M) in seed funding to expand its AI-driven platform for preclinical drug development, helping researchers predict drug success and accelerate the pathway from lab to clinic.
AI has advanced molecule design, yet synthetic feasibility remains a bottleneck. Chemistry-first approaches offer a practical way forward.
Drug discovery now costs 100 times more per FDA-approved drug than in 1950, despite vast advances in biology and computing. The core problem is the collapse of predictive validity in preclinical models, which sits at the heart of pharma’s productivity paradox.
Measuring disease progression remains one of the biggest hurdles in CNS drug development. Eye movements, now trackable with just a laptop and webcam, are emerging as a sensitive and scalable biomarker that could transform how trials are designed and therapies reach patients.
Researchers have refined a cutting-edge DNA sequencing tool that reveals how mutations accumulate in healthy tissues as we age, offering insights into the earliest stages of cancer development.
Researchers have developed a new blood test method, CloneSeq-SV, that tracks treatment-resistant ovarian cancer cells over time. The approach could help predict recurrence and guide targeted therapies.
Dr Alan Nafiiev evaluates template-based, docking and template-free approaches to PPI prediction, highlighting how AI can enhance structural accuracy.
Multiomics, AI and liquid biopsies are giving researchers real-time insight into tumour biology and enabling more personalised cancer therapies. Find out how these technologies are advancing biomarker discovery, improving patient stratification, and guiding the design of new treatments.
