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Highlights ● Insilico published a new study unveiling Target Identification Pro (TargetPro), a superior disease-specific model, and TargetBench 1.0, the first standardized benchmarking framework for target discovery. ● TargetPro achieved 71.6% retrieval of known clinical targets, a 2–3x improvement over large language models (LLMs) such as GPT-4o, Grok3, DeepSeek-R1, Claude-Opus-4, BioGPT, and public platforms like Open Targets. ● TargetPro’s predicted novel targets demonstrated 95.7% structure availability, 86.5% druggability, and 46% repurposing potential, outperforming competing systems on all measures. ● TargetBench’s explainable AI models revealed disease-specific feature importance patterns, emphasizing the value of disease-specific target identification models. ● New gold standard approaches improve accuracy, reliability, and transparency in AI-driven drug discovery.

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Due to the litigation Pfizer filed Friday and Monday against Metsera, Novo Nordisk and the biotech’s lead shareholder, CEO Albert Bourla was limited in what he could say. But he said Pfizer was the best fit for Metsera.

Pressure from the FTC and Pfizer is building around Novo Nordisk’s bid to snatch obesity biotech Metsera. The antitrust watchdog has spotted issues with the structure of Novo’s bid, while its New York-based rival has put more money on the table.