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#pharmaceuticals News & Analysis

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

7 articles
GeneralBearishCrypto Briefing · Jun 197/10
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US launches Section 301 probe of Germany over pharmaceutical pricing

The US has initiated a Section 301 investigation into Germany's pharmaceutical pricing policies, a trade action that could escalate transatlantic tensions and establish precedent for future disputes over drug pricing regulations globally.

US launches Section 301 probe of Germany over pharmaceutical pricing
GeneralBearishCrypto Briefing · Apr 207/10
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Trump imposes 100% tariffs on imported drugs, EU retaliation uncertain

The Trump administration has implemented 100% tariffs on imported pharmaceuticals, creating significant uncertainty around potential EU retaliation. This trade action threatens to disrupt global pharmaceutical supply chains and strain US-EU relations, with broader implications for international commerce and economic stability.

Trump imposes 100% tariffs on imported drugs, EU retaliation uncertain
GeneralNeutralMIT Technology Review · Jun 105/10
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The “steroid olympics” were a circus—and a window into our culture

An article examining a major doping scandal in Olympic sports involving dozens of athletes using various performance-enhancing drugs and hormones. The piece uses this incident as a lens to explore broader cultural attitudes toward competition, winning, and pharmaceutical enhancement.

AIBearisharXiv – CS AI · Mar 96/10
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On the Reliability of AI Methods in Drug Discovery: Evaluation of Boltz-2 for Structure and Binding Affinity Prediction

A comprehensive evaluation of Boltz-2, an AI-based drug discovery tool, reveals significant limitations in predicting protein-ligand binding structures and affinities. The study found only weak correlations with physics-based methods and concluded that while useful for initial screening, Boltz-2 lacks the precision required for reliable drug lead identification.

AIBullisharXiv – CS AI · Mar 36/107
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Pharmacology Knowledge Graphs: Do We Need Chemical Structure for Drug Repurposing?

Researchers developed a pharmacology knowledge graph for drug repurposing and found that removing chemical structure representations improved performance while dramatically reducing computational requirements. The study showed that drug behavior can be accurately predicted using only target protein information and network topology, with larger datasets proving more valuable than complex models.