Issue: Vol. 42

The current discussion surrounding the role of artificial intelligence (AI) in chemistry often centers on the provocative question of whether AI will supplant chemists in the laboratory. Such debates, while stimulating, tend to overshadow a more pressing and realistic consideration. At present, there is little evidence to suggest that AI will replace experimental chemists in research laboratories in the foreseeable future. However, a critical aspect frequently overlooked in these discussions is the competitive advantage that AI confers. Chemists who adeptly integrate AI into their research methodologies are likely to surpass their peers who do not adopt these advanced tools. This shift in research dynamics underscores the importance of embracing AI not as a replacement but as a powerful ally in the evolving landscape of chemical research. This article was written to demystify the capabilities and limitations of AI in modern chemical research, and to provide a balanced perspective on how AI tools can be effectively integrated without wasting the essential human element in scientific discovery.

Adverse event (AE) case intake, in its current form, is one of the most overlooked and broken workflows in biopharma, so it is ripe for disruption by next-generation AI technologies. After several years of bold promises, Generative AI and Large Language Models are now tangibly delivering human-like decision-making, leading to earlier and more accurate conclusions about Safety events, to enable real-time interventions. ArisGlobal’s Emmanuel Belabe assesses how far the technology has come in delivering intelligent, automated case intake; the tangible difference this is already making; and the wider opportunity for reinventing pharma R&D operations.