The front page of AI-driven biology
Thursday, October 15, 2026Thu, Oct 15
Updated 6:32 PM PT
Following positive Phase 3 adjuvant melanoma results reported in August, the partners are preparing regulatory submissions for intismeran autogene given alongside Keytruda, an anti-PD-1 antibody.
The European Medicines Agency's human medicines committee recommended marketing authorization for daraxonrasib, Revolution Medicines' oral RAS inhibitor for pancreatic cancer sold in the United States as Rasonque.
Researchers from the University of Toronto, the Sloan Kettering Institute, King's College London, and the Francis Crick Institute applied a computational tool named MicroExonator to over 100 terabytes of RNA sequencing data, uncovering more than 1,500 tiny protein-coding segments known as microexons.
Researchers at MIT's Picower Institute found that the Alzheimer's risk variant APOE4 impairs myelination by suppressing Wnt signaling in oligodendrocytes, the brain cells responsible for insulating nerve fibers.
Illumina announced the launch of BioInsight, a unified software suite that combines its multiomics analytics, artificial intelligence tools, and biological datasets.
Healthcare investment firm OrbiMed has collected $3 billion across two vehicles, comprising over $1.9 billion for its 10th flagship private investment fund focused on North America and Europe alongside more than $1 billion for its sixth Asia-dedicated partnership.
France-based Osivax reported that its influenza A candidate OVX836 achieved a vaccine efficacy of 24% in a Phase 2b trial of 2,850 healthy European adults, missing the 50% bar required by the primary endpoint.
AstraZeneca is paying insitro $40 million upfront, with up to $1.46 billion in potential milestones that bring the deal's headline value to $1.5 billion, to identify drug targets for metabolic liver disease and heart failure.
University of Washington researchers have introduced RFdiffusion3, a generative model that uses free-atom diffusion to build custom protein and RNA structures around precise geometric constraints.
Researchers built RARE-PHENIX, an automated framework that reads unstructured clinical text, standardizes symptoms into formal Human Phenotype Ontology terms, and ranks them by diagnostic importance.
HitSV combines repeat-aware breakpoint detection with haplotype-resolved local DNA assembly to identify structural genomic variants across multiple sequencing platforms.
Researchers built NoiTox, a computational framework that pairs standard tree-based classifiers using physicochemical properties with deep protein language models and graph networks to predict peptide toxicity.
Because laboratory tests rarely document proteins that fail to interact, computational biologists evaluate interaction models against randomly paired non-interacting proteins, an approach that systematically warps performance metrics.
A multi-agent framework called ExpertTwins anchors language-model agents to inspectable evidence policies and cited publications rather than simple persona prompts.
Machine learning classifiers trained on early embryonic stages revealed that tumors widely reactivate gene expression programs from preimplantation development, with opposing effects on survival depending on the stage mimicked.
Conditional generative models frequently hallucinate non-additive interactions when predicting how interventions behave in combination, according to an evaluation across drug dose-response, cellular perturbation, and molecular shape datasets.
Researchers have built a family of discrete diffusion models that construct phylogenetic trees from sequence data using top-down, middle-out, or bottom-up steps.
A combined statistical and neural-network method accurately infers anomalous diffusion parameters from noisy single-particle tracks.