Archive
532 articles, sorted by publication time.
When the pivotal trial for a marketed rare disease drug is no longer regarded by regulators as reliable, the question is not only whether a single product stays or goes, but how clinical evidence, patient safety, and trust in medicines are recalculated.
A modest-sized acquisition reflects immune reconstitution technology moving from proof of concept toward capital selection; but transaction details are limited, and its clinical value still needs to be answered by subsequent development.
A study using the PANX1 channel as a model shows that DNA-encoded libraries can screen membrane protein targets in an environment closer to their natural membrane setting, helping fill a long-standing gap in early drug discovery.
Generative models are rewriting how drug candidates are searched for, but the biotech industry’s next major opportunity may lie not in more dazzling predictions, but in bringing those predictions into a reproducible, reviewable, and payable clinical evidence chain.
From predicting protein shapes to reverse-designing new molecules, artificial intelligence is changing the starting line for life sciences; but to truly move toward drug, vaccine, and materials applications, it still must clear wet-lab validation and regulatory trust.
Platinum-resistant ovarian cancer has long lacked comfortable options; NTB-928 has completed first-patient dosing in Phase 1, marking the formal move of a new therapy into clinical validation, though what can be interpreted for now remains only a starting point.
A Harvard team has turned tumor gene expression into interpretable predictions of immune response, offering a new tool for patient stratification; but the more a model can operate across cancer types and drugs, the more clinical trials must also re-answer questions of validation, bias, and regulatory responsibility.
The U.S. FDA has expanded approval of Vertex’s CASGEVY for patients aged two and older with sickle cell disease and transfusion-dependent beta thalassemia; this brings a one-time gene therapy closer to pediatric wards for young children, while pushing questions about long-term safety, pediatric evidence, and treatment timing further to the fore.
From target identification to molecular design, AI is making the front end of drug R&D faster; but data quality, wet-lab validation, and clinical review still determine whether an algorithmic hypothesis can become a treatment option for patients.
The point of Claude Science is not to claim that AI can replace drug R&D, but to connect models, databases, programming environments, and traceable records into the same scientific workbench; this also shifts tech companies’ responsibility in biomedical R&D from polished demos toward harder-to-avoid questions of validation.
The focus of this clinical data is not only more accurate glucose readings, but whether continuous glucose monitoring can identify false hypoglycemia caused by pressure during sleep, bringing alarms closer to the physiological changes that truly need attention.
A seemingly technical drug-control lawsuit is pulling cannabis policy back to more fundamental questions: who should guide the next step in the regulatory system: scientific assessment, public health, or entrenched industry interests?