Topics
ArticleMachine learning identifies biological signals linked to emotional hunger
Researchers at Phenomix Sciences are using machine learning and genetic risk scoring to investigate emotional hunger, an obesity phenotype linked to emotional and reward-driven eating behaviours. Dr Timothy O’Connor discusses how the approach could improve patient stratification, obesity research and treatment selection.
ArticleWhy AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
ArticleTurning GWAS signals into drug targets with scalable CRISPR
Genome-wide association studies have linked thousands of genetic variants to disease, yet most remain disconnected from drug-relevant biology. Neville Sanjana, Professor at New York University and Core Faculty Member at the New York Genome Center, explains how scalable CRISPR screens systematically link noncoding variants to causal genes and therapeutic targets.
ArticleAACR 2026 part 1: AI design, precision biology and the next wave of oncology innovation
At AACR 2026, industry leaders discussed how oncology R&D is moving beyond isolated technological advances towards integrated discovery systems.
WebinarWhat it takes to automate high-content imaging at scale
This webinar examines the design trade-offs and technical constraints involved in building a high-throughput robotic imaging pipeline for complex biological workflows.
WebinarThe truth about AI in drug discovery: what the experts really think
AI is transforming drug discovery - but beyond the hype, what’s actually delivering results? In this expert-led webinar, industry leaders explore where AI is accelerating target identification, molecule design and hit discovery, while also confronting the real-world challenges of data quality, validation and adoption. Discover what’s working today, what still ...
WebinarCan One Peptide Change Pain Research? Meet the Tool Transforming Drug Discovery
Discover how a new peptide tool, WRPRFa, is helping researchers better understand pain pathways and accelerate the search for next-generation analgesics.
WebinarOvercoming Affinity and Expression Bottlenecks in TCR Discovery
This expert-led webinar discusses how to break through common bottlenecks in TCR discovery with practical strategies that help teams move faster and smarter.
- Article
Machine learning identifies biological signals linked to emotional hunger
Researchers at Phenomix Sciences are using machine learning and genetic risk scoring to investigate emotional hunger, an obesity phenotype linked to emotional and reward-driven eating behaviours. Dr Timothy O’Connor discusses how the approach could improve patient stratification, obesity research and treatment selection.
ArticleBeyond tangles: why soluble intracellular tau should guide drug discovery
Tau tangles are a hallmark of Alzheimer’s disease and related disorders, but evidence suggests the real damage may come from rare, soluble tau species inside neurons. Targeting these hidden drivers of circuit dysfunction could be key to restoring memory and cognition.
ArticleWhen antibiotics are not enough: the case for immune-engaging therapies
As antimicrobial resistance grows and patient populations become more complex, the limitations of antibiotics are becoming harder to ignore. Dr Helen Bright, CSO at Centauri Therapeutics, discusses a new approach that targets both the pathogen and the host.
ArticleWomen in STEM: resilience and leadership in rare disease research
Rare neurological diseases remain one of the most challenging areas in drug discovery, with many patients still lacking treatment options. Dr Nitza Thomasson discusses returning to Servier to lead its rare neurology therapeutic area and explains why resilience, curiosity and persistence are essential for those looking to build a meaningful career in STEM.
- Article
Machine learning identifies biological signals linked to emotional hunger
Researchers at Phenomix Sciences are using machine learning and genetic risk scoring to investigate emotional hunger, an obesity phenotype linked to emotional and reward-driven eating behaviours. Dr Timothy O’Connor discusses how the approach could improve patient stratification, obesity research and treatment selection.
- Article
Beyond tangles: why soluble intracellular tau should guide drug discovery
Tau tangles are a hallmark of Alzheimer’s disease and related disorders, but evidence suggests the real damage may come from rare, soluble tau species inside neurons. Targeting these hidden drivers of circuit dysfunction could be key to restoring memory and cognition.
- Article
Why AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
- Article
Turning GWAS signals into drug targets with scalable CRISPR
Genome-wide association studies have linked thousands of genetic variants to disease, yet most remain disconnected from drug-relevant biology. Neville Sanjana, Professor at New York University and Core Faculty Member at the New York Genome Center, explains how scalable CRISPR screens systematically link noncoding variants to causal genes and therapeutic targets.
- Article
Beyond tangles: why soluble intracellular tau should guide drug discovery
Tau tangles are a hallmark of Alzheimer’s disease and related disorders, but evidence suggests the real damage may come from rare, soluble tau species inside neurons. Targeting these hidden drivers of circuit dysfunction could be key to restoring memory and cognition.
- Article
Why AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
- Article
Turning GWAS signals into drug targets with scalable CRISPR
Genome-wide association studies have linked thousands of genetic variants to disease, yet most remain disconnected from drug-relevant biology. Neville Sanjana, Professor at New York University and Core Faculty Member at the New York Genome Center, explains how scalable CRISPR screens systematically link noncoding variants to causal genes and therapeutic targets.
- Article
When antibiotics are not enough: the case for immune-engaging therapies
As antimicrobial resistance grows and patient populations become more complex, the limitations of antibiotics are becoming harder to ignore. Dr Helen Bright, CSO at Centauri Therapeutics, discusses a new approach that targets both the pathogen and the host.
- Article
Machine learning identifies biological signals linked to emotional hunger
Researchers at Phenomix Sciences are using machine learning and genetic risk scoring to investigate emotional hunger, an obesity phenotype linked to emotional and reward-driven eating behaviours. Dr Timothy O’Connor discusses how the approach could improve patient stratification, obesity research and treatment selection.
- Article
Beyond tangles: why soluble intracellular tau should guide drug discovery
Tau tangles are a hallmark of Alzheimer’s disease and related disorders, but evidence suggests the real damage may come from rare, soluble tau species inside neurons. Targeting these hidden drivers of circuit dysfunction could be key to restoring memory and cognition.
- Article
Why AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
- Article
When antibiotics are not enough: the case for immune-engaging therapies
As antimicrobial resistance grows and patient populations become more complex, the limitations of antibiotics are becoming harder to ignore. Dr Helen Bright, CSO at Centauri Therapeutics, discusses a new approach that targets both the pathogen and the host.
- Article
Women in STEM: resilience and leadership in rare disease research
Rare neurological diseases remain one of the most challenging areas in drug discovery, with many patients still lacking treatment options. Dr Nitza Thomasson discusses returning to Servier to lead its rare neurology therapeutic area and explains why resilience, curiosity and persistence are essential for those looking to build a meaningful career in STEM.
NewsGinkgo Bioworks launches ADME-One platform for early-stage screening
Ginkgo Bioworks has launched ADME-One, an integrated platform combining high-throughput ADME testing with AI-powered human pharmacokinetic projections.
NewsAI identifies 23 antiviral candidates for Bundibugyo Ebola strain
US researchers have deployed artificial intelligence and molecular docking software to identify 23 antiviral compounds with potential activity against Bundibugyo Ebolavirus, as the rare strain continues to spread in the Democratic Republic of Congo with a fatality rate approaching 40 percent.
NewsISSCR consortium submits recommendations on NAMs to FDA
The ISSCR Consortium on Advanced Stem Cell-Based Models is calling for greater flexibilty from the FDA to accomodate rapidly changing technologies like stem cell-derived systems, organoids and computational approaches.