Drug Target Review

AI in Drug Discovery: Progress, Limits and What Comes Next

2026-06-10T09:22:00+01:00By Drug Target Review

AI has attracted enormous investment across drug discovery, but major questions still remain around validation, reproducibility and real-world application. In our latest Beyond the Lab report, experts discuss where the technology is starting to influence discovery workflows – and where limitations continue to slow adoption.

Article
Why scaling human-derived models is pharma’s next big challenge
2026-06-09T08:20:00+01:00Contributor Steve Smith, By Drug Target Review
Many drugs still fail after promising preclinical results, raising difficult questions about how disease is modelled in the lab. Researchers are now turning to organoids and iPSC-derived systems to build more predictive models for drug discovery and reduce costly late-stage failures.
Article
Why targeted therapies are exposing the limits of animal models – and what comes next
2026-06-04T07:05:00+01:00Author Graham Craig
Traditional preclinical models are struggling to keep pace with a new generation of targeted therapies. As regulators embrace new approach methodologies (NAMs), vascularised tissue platforms are offering a more human-relevant approach to predicting drug efficacy and safety.
Article
From chemist to AI agent builder: inside the rise of agentic AI in drug discovery
2026-06-03T07:30:00+01:00By Dr Raminderpal Singh
Dr Raminderpal Singh speaks with Dr Srijit Seal about why specialised AI agents are outperforming general-purpose models in drug discovery and what a new consortium paper shows about their use in practice.

Opinion and interviews

Computational design drives new generation of synthetic promoters

2026-03-26T14:21:00+00:00By Drug Target Review

Designing gene control from scratch is becoming possible. SynGenSys is using computational design to create synthetic promoters for advanced therapies.

Webinar

Where NAMs stand in early drug discovery: an expert discussion

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