Archive
557 articles, sorted by publication time.
Daraxonrasib’s late-stage trial is drawing major drugmakers closer, while making one biotech company’s choices more complicated: whom to sell to, or whether to bring an oral KRAS drug into clinical practice on its own.
Ethics approval allows HaemaLogiX to begin a higher-dose combination therapy trial; this step is not a conclusion on efficacy, but places early response signals into a testing framework closer to clinical decision-making.
Ethics approval allows HaemaLogiX’s Phase 2b trial to move toward enrollment readiness; the real question is whether an antibody targeting the kappa myeloma antigen can establish a verifiable clinical position within existing drug combinations.
A stock-price background report brings the focus back to Incyte’s core challenge: while mature drugs still support revenue, can new hematology, immunology, and oncology pipelines build the next chapter amid competition?
As global biotech companies look for faster and more stable trial pathways, Asia-Pacific and China are being pushed to the center of the R&D map; but with limited details in a single piece of news, this expansion is better viewed as an industry signal rather than a guarantee of outcomes.
AI models for antibody design are proliferating, but what is truly scarce is a comparison standard that can bring predictions back to the experimental setting. A wet-lab-validated dataset spanning multiple antibody formats and targets is trying to make the question of “which model is more reliable” no longer depend solely on internal data.
This collaboration, with up to $510 million in milestone payments, is not just another deal in AI drug discovery; it pushes the question back into the laboratory itself: can machine learning, supported by sufficiently robust protein data, shorten the distance from therapeutic candidates to credible evidence?
A new preprint uses ClinicalTrials.gov records as an observation window to track how artificial intelligence is entering clinical research; it reminds readers that what truly needs to be examined is not only algorithm performance, but also how trials clearly explain what humans and machines each did.
Researchers are using artificial intelligence to design proteins in an effort to create self-assembling virus-like shells; the real significance is not in imitating viruses, but in rewriting viruses’ ability to package and deliver molecules into a controllable bioengineering tool.
The early trial of ABS-201 moves AI drug design from molecular promise into tests of safety and efficacy signals; the real question is not how novel the model is, but whether human data can support the next stage of development.
A large evidence review links nicotine e-cigarettes more directly to the risk of lung cancer and oral cancer; it does not amount to claiming that e-cigarettes and conventional cigarettes are equally dangerous, but it weakens the popular idea of a “harmless alternative.”
A shared challenge in Alzheimer’s disease and Parkinson’s disease is not only that harmful proteins clump together, but how cells steer those aggregates toward disaster or function. New research suggests that tubulin may act as a key traffic director, though it remains some distance from becoming a drug.