Science, Ahead of Print.

I know what you think about papers in Cell. They are long. Mechanistic. “Complete.” They report deep biological insights. I know this because I hear it a lot from researchers. There is truth to it. Cell has published thousands of papers that fit these descriptors, and we will continue to. They have incredible value. But we don’t publish papers in Cell because they are long and mechanistic. We publish them because they are exciting. Cool. Awe-inspiring. We publish them because we think they provide something that our readers will want to learn about and will benefit from.

Salaudeen et al. review common reliability failures in predictive and generative AI for healthcare, including erroneous model outputs, clinically unjustified performance differences, and deployment-time degradation. They examine why existing technical solutions fall short and argue for lifecycle-aware evaluation, continuous monitoring, and institutional governance.

Artificial intelligence (AI) is changing the way biomedical research is conducted by making it possible to integrate diverse types of biological data and tackle questions that were previously difficult to address. At the same time, its growing use also raises important questions about data quality, reliability, interpretability, and how computational predictions should be combined with biological knowledge and experimental validation. In this Voices piece, researchers from diverse disciplines share their perspectives on how AI is advancing their respective fields and highlight both the transformative opportunities and the key challenges that will shape the future of the life sciences.

scBaseCount is presently the largest public single-cell RNA-seq repository, containing over 502 million cells across 27 organisms and 75 tissues. An AI agent autonomously discovers, annotates, and uniformly reprocesses all 10× Genomics datasets in the SRA, creating a harmonized, continually updated resource for studying the diversity of cell biology and training AI models.

Tahoe-100M is an atlas of 100 million single-cell transcriptomes, capturing how 50 cancer cell lines respond to ∼1,100 drug-dose treatments. By pairing single-cell and molecular phenotypes at scale, the resource links drug mechanisms to cellular responses and provides an openly available substrate for training predictive models of cell behavior.

LongevityBench, Longevity-LLMs, and Longevity Claw evaluate the readiness of the state-of-the-art AI systems for spearheading aging research.

Nature Medicine, Published online: 17 September 2026; doi:10.1038/s41591-026-04646-6

Results of this study show in experimental models and data from patient cohorts that the antiseizure medication levetiracetam is associated with longer survival and reduced tumor growth in diffuse midline glioma, but not hemispheric high-grade glioma, by selectively dampening GABAergic synaptic signaling, independently of its canonical SV2A-mediated primary antiseizure mechanism.

Nature Medicine, Published online: 16 September 2026; doi:10.1038/s41591-026-04665-3

Increased expression of EBV reactivation genes in B cells and MS risk genes targeted by the EBV protein EBNA-2 precedes MS attacks, linking EBV reactivation and genetic risk to the development of MS relapses.

Nature Medicine, Published online: 16 September 2026; doi:10.1038/s41591-026-04625-x

In a prospective study involving 1,785 individuals from four countries, the PANXEON exosome-based biomarker, combined with carbohydrate antigen 19-9 levels, achieves high sensitivity for the detection of early-stage pancreatic cancer.

Nature Medicine, Published online: 16 September 2026; doi:10.1038/s41591-026-04636-8

In this single-arm phase 1 trial, an AAV gene therapy carrying the Padua variant of factor IX was well tolerated in 11 adolescents with hemophilia B and led to reductions in annualized bleeding rate.

Nature Medicine, Published online: 16 September 2026; doi:10.1038/s41591-026-04662-6

Sex-specific biological aging clocks across multiple organs and molecular systems show that female and male aging patterns can differ in organ-specific, disease-relevant ways.

Cell Death Discovery, Published online: 16 September 2026; doi:10.1038/s41420-026-03349-8

ESAM reduces sensitivity to anti-HER2 therapy in HER2-positive breast cancer by activating the mTOR pathway

Nature Medicine, Published online: 15 September 2026; doi:10.1038/s41591-026-04609-x

An autonomous clinical AI agent enhances decision-making through on-premise deployment and reliability metrics, achieving high diagnostic accuracy and selective autonomy.

Nature Medicine, Published online: 15 September 2026; doi:10.1038/s41591-026-04644-8

In the phase 2 RIO trial, there was delayed viral rebound and resistance to broadly neutralizing antibodies 3BNC117-LS and 10-1074-LS in adult males living with HIV undergoing analytical treatment interruption, and initial reservoir sensitivity to autologous antibodies was associated with a longer time to rebound.

Agarwal et al. introduce MitoSpace, a self-supervised model trained on 4D lattice light-sheet microscopy data. The model resolves drug-induced mitochondrial phenotypes without labels, predicts membrane potential from morphology and dynamics, generalizes to unseen perturbations and lung organoids, and shows that representation quality improves progressively from 2D to 4D.

Modeling perturbation effects across large single-cell populations requires flexibility to capture heterogeneity. By training over sets of cells in a shared embedding space, State outperforms baselines at generalizing effects to new contexts. Cell-Eval, the framework used for this comparison, provides a comprehensive benchmark for future models.

The Virtual Cell Challenge returns in 2026 with a more demanding test of biological generalization: zero-shot prediction across multiple independent cellular contexts. Participants will build models to predict gene knockdown responses in a new Arc-generated dataset comprising unseen cell lines. The goal is to determine whether the best models can meaningfully close the gap between preclinical experimental predictions and human biology.

Recombining domains across an entire protein family, rather than relying on natural sequences shaped by evolution, generates synthetic “DESynR” transcription factors with enhanced function. DESynR AP-1 TFs reprogram CAR T cells into non-natural, therapeutically optimized states and outperform natural AP-1 factors in antitumor immunity.

(Cell 188, 6953–6970.e1–e8; November 26, 2025)