Shares of Bruker Corporation (NASDAQ:BRKR) and 10x Genomics (NASDAQ:TXG) dropped on Monday following public attention to GigaTIME, an artificial intelligence model created by Microsoft in collaboration with Providence Health and the University of Washington that predicts multiplex immunofluorescence test outputs from hematoxylin and eosin (H&E) pathology slides.
Market reaction and analyst perspective
Wolfe Research attributed the sell-off to investor concern that clinical demand for spatial proteomics - the category that includes multiplex immunofluorescence assays - could shrink if AI were to supplant some clinical applications. The research firm, however, cautioned that the price moves appeared disproportionate to the underlying evidence.
Specifically, Wolfe Research noted two points that temper the perceived threat to companies that supply spatialomics tools. First, Bruker and 10x Genomics' spatialomics products are not yet widely integrated into clinical workflows. Second, the paper underlying GigaTIME was published in Cell several months prior, meaning the key findings were already in the public domain.
What GigaTIME does - and the scope of the study
The GigaTIME approach applies multimodal AI to translate H&E pathology results into spatial proteomics readouts. According to the published study, the model was trained on 40 million cells using paired H&E slides and multiplex immunofluorescence results across 21 proteins, and then evaluated on 14,256 patients. The set of markers included PDL-1, a protein cited for its relevance to immunotherapy.
Wolfe Research emphasized limitations within the study, noting that assessing only 21 proteins may not be sufficient to demonstrate that the AI approach could replace traditional multiplex methods, which often survey many more markers. The firm described the development as early stage.
Clinical context reported in the study
The Cell paper framed multiplex immunofluorescence as a tool used to characterize the tumor immune microenvironment, a factor that influences cancer progression and response to immunotherapy. The study also described multiplex immunofluorescence as expensive and slow, which is part of the motivation for exploring AI-based translation from routine H&E slides.
Taken together, the market reaction reflects concern about potential downstream effects of AI on niche clinical testing markets, while analysts underline that the technology and evidence remain in early stages and that current clinical adoption of spatialomics platforms is limited.