FDA approves Eli Lilly's Inluriyo alongside Verzenio in breast cancer
The FDA cleared Eli Lilly to market a combination of its oral selective estrogen receptor degrader Inluriyo (imlunestrant) and its CDK4/6 inhibitor Verzenio (abemaciclib).
News
Alkermes reports symptom drops in early trial of orexin agonist for ADHD
Alkermes reported that its oral orexin agonist ALKS 7290 reduced symptom scores in a 50-patient Phase 1b trial in adults with attention deficit hyperactivity disorder.
Fierce Biotech, also reported by BioPharma DiveEndpoints News (subscription required)STATAnthropic confirms it operates an internal wet lab to test biology models
Anthropic has set up a physical biology laboratory to run wet-lab experiments that validate predictions made by its artificial intelligence models, life sciences head Eric Kauderer-Abrams told Reuters.
TechCrunch, also reported by ReutersCNBCNovo acquires three early-stage obesity drug candidates from Kallyope
Novo has acquired three early-stage obesity programs from New York biotech Kallyope, expanding its metabolic pipeline beyond the GLP-1 hormone class.
Two B7-H3 antibody-drug conjugates cut small-cell lung cancer death risk by 54% in Phase 3 trials
Hansoh Pharma's risvutatug rezetecan, partnered with GSK, and MediLink Therapeutics' tambotatug pelitecan, partnered with Roche, both cut the risk of death by 54% compared to standard topotecan chemotherapy in late-stage relapsed small-cell lung cancer trials.
Human brain arises from two distinct organs, developmental study shows
Researchers at Stanford, Caltech, and UCSF found that the human brain develops from two separate progenitor cell lineages rather than a single unified origin.
Proposed US investment rules would protect most drug licensing deals with China
Draft US regulations on outbound pharmaceutical investment in China would preserve Western companies' ability to license Chinese drug candidates, according to reporting by Reuters.
Reuters, also reported by Endpoints News (subscription required)Zealand Pharma's Zeydovio wins European regulatory panel backing
The European Medicines Agency's Committee for Medicinal Products for Human Use has recommended approval of Zealand Pharma's Zeydovio (glepaglutide), a long-acting GLP-2 analog for short bowel syndrome.
Xenon pauses Phase 3 depression trials over psychosis reports
Xenon Pharmaceuticals voluntarily stopped new patient enrollment in its Phase 3 trials of azetukalner, an oral Kv7 potassium channel opener, following reports of confusion, ataxia, and rare cases of psychosis.
Fierce Biotech, also reported by BioPharma DiveBristol Myers Squibb dumps Orum cancer drug after Phase 1 review
Bristol Myers Squibb has terminated development of ORM-6151, an antibody designed to deliver a protein degrader to CD33-expressing leukemia cells, which it bought from Orum Therapeutics for $100 million in 2023.
Fierce Biotech, also reported by Endpoints News (subscription required)
Publications
Machine learning model tunes organ-on-chip media to better mirror human liver disease
LIV2TRANS uses machine learning to map transcriptional data from microphysiological tissue models onto human clinical profiles to identify media supplements that maximize biological relevance.
AI turns single-cell clusters into sorting gates for physical cell isolation
ConvexGating uses machine learning to convert high-dimensional single-cell clusters into interpretable, low-contamination gating strategies that hardware cell sorters can execute directly.
Deep learning model predicts how drugs alter gene activity in single cells
Researchers have developed WAVE, a neural network designed to predict transcriptional changes caused by small molecules across both bulk tissue and individual cells.
Preprints
Updated database adds 5.8 million predicted viral protein structures
The Steinegger lab released version 3 of the Big Fantastic Virus Database, expanding its collection of ColabFold-predicted viral protein structures to 5,776,417 models across UniProt sequences.
Protein language model unearths 14,300-year-old RNA viruses from frozen wolf remains
Scientists used the protein language model Lucaprot and AlphaFold2 structure modeling to detect two previously unknown RNA viruses in RNA sequencing data from a 14,300-year-old permafrost-preserved Pleistocene wolf.
Machine learning designs solid mRNA vaccines stable at body temperature
Researchers built an active-learning system called AGENT, combining Bayesian optimization with lab testing to formulate solid-state mRNA lipid nanoparticles in six iterative rounds.
AI tracks immune T cells to predict vaccine antibody responses
Researchers built a language model named DeepAir-Cov19 to spot SARS-CoV-2-targeting T-cell receptors, achieving an area under the curve of 0.94.
Projecting single-cell expression data onto a sphere yields interpretable developmental coordinates
Computational biologists developed SPHERE-PCA, a method that maps the first three principal components of single-cell RNA sequencing data onto a three-dimensional unit sphere to create an interpretable coordinate framework.
Adversarial machine learning predicts peptide functions without confirmed negative data
Researchers built Pep-PU-GAN, a machine learning model that pairs graph neural networks with positive-unlabeled adversarial learning to classify bioactive peptides when verified non-functional examples are scarce.
Spatial maps of 112 million melanoma cells pinpoint immune hubs that predict immunotherapy response
A spatial multi-omics study tracking over 112 million cells across three melanoma neoadjuvant immunotherapy regimens revealed that mature tertiary lymphoid structures with germinal centers, sustained by specialized fibroblast scaffolds, distinguish responders from non-responders.
Generative model translates protein sequence into microscopy images
Researchers built CELL-FM, a bidirectional generative AI framework that predicts fluorescence microscopy images directly from protein sequences and cellular context, and can also work in reverse.
Sparse machine learning maps cord blood omics in infant lung disease
Researchers applied a sparse machine learning workflow using Stabl and LASSO regression to analyze 45,000 cord blood features in a cohort of 217 infants at risk for bronchopulmonary dysplasia, a chronic lung condition affecting premature babies.
Language model decodes complex fat molecules in mass spectrometry data
Researchers built OpenLipid, a workflow that uses large language models to identify target lipids from data-independent acquisition mass spectrometry.
Machine learning trained on tumor gene loss spots potent cancer neoantigens
Researchers built the Neoantigen Elimination Model (NEMo), a two-compartment machine learning tool that predicts which mutant tumor targets trigger immune attack by tracking which cancer subclones disappear during immunotherapy.
AI turns text descriptions of genes into an interpretable coordinate system for single-cell data
A computational method named MESIC uses a biomedical language model to translate written gene annotations into low-dimensional semantic coordinates that give biological meaning directly to single-cell data.
Generative model designs synthesizable drug candidates validated across five protein targets
Researchers introduced the Large Drug Discovery Model, a 3D generative framework that designs drug candidates to satisfy fine-grained structural goals while ensuring they can be readily made in a laboratory.
Generative search guides protein design to build binders for carbohydrates and polar surfaces
Researchers introduced latent generative search, a framework that guides the Proteina-Complexa model at inference time to generate protein sequences and 3D shapes simultaneously, eliminating the need for a separate inverse-folding step.
Adding physical rules brings three-dimensional drug-binding models up to standard ligand baselines
A computational study evaluated whether adding structural and physical rules can help three-dimensional machine learning models match conventional two-dimensional ligand-only models in predicting small-molecule binding affinity.
Fine-tuned neural networks predict molecular toxicity in data-scarce chemical classes
Researchers fine-tuned a general baseline molecular property model on small, specialized datasets to predict chemical toxicity in classes with limited historical testing.
Clustering tool for single-cell genome architecture separates true gaps from missing data
A computational method called ssJSD groups single-cell chromatin contact maps by distinguishing biologically meaningful uncontacted DNA regions from technical dropouts caused by shallow sequencing.
Autonomous laboratory robot tests physical inputs on living cells and embryos
Researchers built MOMbot, an automated hardware and software platform that delivers chemical, electrical, mechanical, and thermal cues to biological specimens while an active-learning algorithm decides the next test.