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ENTITY drug development

drug development

PulseAugur coverage of drug development — every cluster mentioning drug development across labs, papers, and developer communities, ranked by signal.

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RECENT · PAGE 1/1 · 6 TOTAL
  1. TOOL · CL_208571 ·

    AI framework enhances drug discovery with reliable molecular property predictions

    Researchers have developed a new conformal prediction framework designed to improve the reliability of AI in drug discovery, particularly when dealing with label shift. This method generates statistically rigorous predi…

  2. TOOL · CL_199732 ·

    Agentic AI finds new applications in healthcare billing and drug development

    Cedar has implemented agentic AI to streamline patient billing and enhance the financial experience for patients. Separately, AI agents are being explored for their financial value in drug development, highlighting the …

  3. RESEARCH · CL_152411 ·

    AI dramatically accelerates drug development, cutting costs and timelines by up to 70%

    Artificial intelligence is significantly accelerating drug development, with a recent survey indicating that AI can reduce preclinical costs and timelines by up to 70%. This advancement is driving demand for sophisticat…

  4. TOOL · CL_123042 ·

    New MKGR framework enhances cold-start protein interaction prediction

    Researchers have developed MKGR, a novel multimodal representation learning framework designed to improve the prediction of protein-protein interactions (PPIs), particularly in cold-start scenarios where candidate prote…

  5. COMMENTARY · CL_102986 ·

    AI provenance: Verifiable records needed for trusted AI actions

    Mickai is advocating for audit-ready provenance for AI systems, emphasizing the need for verifiable records of AI actions and decisions. This approach aims to ensure that AI outputs, whether in drug development, legal c…

  6. RESEARCH · CL_55764 ·

    AI assistants find new drug targets for repurposed therapies

    Two AI-powered science assistants have successfully identified new therapeutic targets for existing drugs. These AI tools were able to propose novel applications for drugs that were previously ineffective or had failed …