Archive
538 articles, sorted by publication time.
A new study shifts the focus from directly killing cancer cells to immune cells that have been “co-opted” within the tumor microenvironment; if the metabolic state of macrophages can be reshaped, immunotherapy may be able to work in more patients.
Insilico’s new collaboration with Takeda puts generative AI into a drug development workflow closer to pharmaceutical decision-making; but the undisclosed targets, disease areas, and validation design mean the scientific value of the deal still has to be answered by experimental and clinical data.
The deal is not a large-scale acquisition, but its signal is clear: the regenerative medicine race is not only about manufacturing organs, but also about reshaping how the immune system recognizes “self” and “non-self” after transplantation.
Kidney disease drug development is shifting from reliance on a single blockbuster product toward earlier-stage, more distributed portfolios of candidate molecules; AstraZeneca’s new agreement with CSPC highlights how multinational drugmakers are looking in China for the next entry point into R&D.
The collaboration connects cancer genome interpretation and candidate drug development within the same R&D chain, aiming to shorten the distance from patient data to clinical trial design; but with limited public information available, whether it can truly accelerate new therapies will still depend on data quality, target validation, and clinical results.
Anthropic is pushing Claude into scientific research workflows, extending competition in AI drug discovery from model capability to data, workflows, and trusted validation; the market’s immediate reaction reveals investors’ reassessment of the moats of existing AI drug discovery companies.
The approval means T cell therapy is not only serving as an anticancer weapon, but is also being applied to one of the most difficult immune-balance challenges in hematopoietic stem cell transplantation. The real test will be whether its efficacy can be consistently reproduced in complex clinical settings.
The July advisory meeting is not just a technical question of whether pharmacies can compound several popular peptides, but a redrawing of the boundaries of evidence among therapeutic narratives, patient demand, and regulatory responsibility.
Drug-resistant bacteria are narrowing treatment options for hospital-acquired infections; Telum’s new funding brings a protein-based antibacterial therapy for Acinetobacter baumannii pneumonia to a key threshold, moving from a design platform into human testing.
Against the reality of high drug development costs and high failure rates, alliances between AI platforms and biotech companies are moving from concept demonstrations to project-based collaborations; but the real dividing line for such deals remains whether candidate molecules can pass experimental and clinical validation.
In 2026, autism-related treatment strategies are again receiving market review and assessment, but in neurodevelopmental diseases, the real key is not the length of the candidate drug list, but whether trials can precisely define the populations that benefit and measurable clinical improvement.
The deal, worth up to $600 million, shows that major pharmaceutical companies are willing to put AI at the core of early-stage R&D; but molecules identified by algorithms still face the long test of biology, clinical trials, and regulatory review.