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#pharmaceutical News & Analysis

8 articles tagged with #pharmaceutical. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

8 articles
AIBullisharXiv – CS AI · Apr 67/10
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ClinicalReTrial: Clinical Trial Redesign with Self-Evolving Agents

Researchers have developed ClinicalReTrial, a multi-agent AI system that can redesign clinical trial protocols to improve success rates. The system demonstrated an 83.3% improvement rate in trial protocols with a mean 5.7% increase in success probability at minimal cost of $0.12 per trial.

AI × CryptoBullishCrypto Briefing · Mar 267/10
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Metanova Labs: Bittensor revolutionizes drug discovery with decentralized virtual screening, combinatorial reactions expand possibilities to 65 billion, and dual incentives drive innovation | TWIST

Metanova Labs is revolutionizing drug discovery by using Bittensor's decentralized AI network to screen billions of molecules efficiently. The platform utilizes combinatorial reactions to expand screening possibilities to 65 billion compounds and implements dual incentive mechanisms to drive innovation in pharmaceutical research.

Metanova Labs: Bittensor revolutionizes drug discovery with decentralized virtual screening, combinatorial reactions expand possibilities to 65 billion, and dual incentives drive innovation | TWIST
$TAO
AIBullisharXiv – CS AI · Mar 57/10
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Mozi: Governed Autonomy for Drug Discovery LLM Agents

Researchers have introduced Mozi, a dual-layer architecture designed to make AI agents more reliable for drug discovery by implementing governance controls and structured workflows. The system addresses critical issues of unconstrained tool use and poor long-term reliability that have limited LLM deployment in pharmaceutical research.

AIBullisharXiv – CS AI · Mar 57/10
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MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery

Researchers introduce MMAI Gym for Science, a training framework for molecular foundation models in drug discovery. Their Liquid Foundation Model (LFM) outperforms larger general-purpose models on drug discovery tasks while being more efficient and specialized for molecular applications.

AIBullisharXiv – CS AI · Mar 37/103
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mCLM: A Modular Chemical Language Model that Generates Functional and Makeable Molecules

Researchers developed mCLM, a 3-billion parameter modular Chemical Language Model that generates functional molecules compatible with automated synthesis by tokenizing at the building block level rather than individual atoms. The AI system outperformed larger models including GPT-5 in creating synthesizable drug candidates and can iteratively improve failed clinical trial compounds.

AIBullisharXiv – CS AI · Mar 37/103
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FROGENT: An End-to-End Full-process Drug Design Multi-Agent System

Researchers have developed FROGENT, an AI multi-agent system that uses large language models to automate the entire drug discovery pipeline from target identification to synthesis planning. The system outperformed existing AI approaches across eight benchmarks and demonstrated practical applications in real-world drug design scenarios.

AINeutralOpenAI News · Aug 74/106
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How Amgen uses GPT-5

The article discusses how pharmaceutical company Amgen utilizes GPT-5 technology in their operations. However, the article body provides insufficient detail to analyze the specific applications or implications of this AI integration.