Public articles linked to the same research event.
Science (New York, N.Y.) This work introduces the Virtual Biotech, an organization of AI agents modeled on a drug-development company with agentic divisions spanning target discovery, safety assessment, modality selection, and clinical development, and demonstrates its utility at three drug-development decision points: over 37,000 agents annotated outcomes from 55,984 trials and found that drugs targeting cell-type-specific genes were 48% more likely to reach market with 32% fewer adverse events; it integrated multimodal evidence to propose a therapeutic strategy in lung cancer; and it analyzed a terminated ulcerative colitis trial and inferred potential mechanisms of failure.
This work introduces the Virtual Biotech, an organization of AI agents modeled on a drug-development company with agentic divisions spanning target discovery, safety assessment, modality selection, and clinical development, and demonstrates its utility at three drug-development decision points: over 37,000 agents annotated outcomes from 55,984 trials and found that drugs targeting cell-type-specific genes were 48% more likely to reach market with 32% fewer adverse events; it integrated multimodal evidence to propose a therapeutic strategy in lung cancer; and it analyzed a terminated ulcerative colitis trial and inferred potential mechanisms of failure.
This work introduces the Virtual Biotech, an organization of AI agents modeled on a drug-development company with agentic divisions spanning target discovery, safety assessment, modality selection, and clinical development, and demonstrates its utility at three drug-development decision points: over 37,000 agents annotated outcomes from 55,984 trials and found that drugs targeting cell-type-specific genes were 48% more likely to reach market with 32% fewer adverse events; it integrated multimodal evidence to propose a therapeutic strategy in lung cancer; and it analyzed a terminated ulcerative colitis trial and inferred potential mechanisms of failure.
This work introduces the Virtual Biotech, an organization of AI agents modeled on a drug-development company with agentic divisions spanning target discovery, safety assessment, modality selection, and clinical development, and demonstrates its utility at three drug-development decision points: over 37,000 agents annotated outcomes from 55,984 trials and found that drugs targeting cell-type-specific genes were 48% more likely to reach market with 32% fewer adverse events; it integrated multimodal evidence to propose a therapeutic strategy in lung cancer; and it analyzed a terminated ulcerative colitis trial and inferred potential mechanisms of failure.