Amid a flood of daily headlines, which topics truly dominated reader attention—and which debates shaped the industry’s direction? To answer these questions, Hit News conducted a comprehensive analysis of its article data from 2025.

Starting today, Hit News presents a year-end special series examining the defining trends of the year—from the most-read stories and most-mentioned keywords to the issues that generated exceptional reader engagement. Told through data, “2025 Pharma-Biotech Issues: All in Hit News” begins now.

① The Click Economy Converges on “Obesity” and “AI”

Interest in obesity treatments overwhelmingly drove readership in 2025. Coverage surrounding the market entry, pricing strategies, and competitive positioning of leading GLP-1–based therapies accounted for three of the five most-read articles of the year.

Reader attention surged as expectations grew around the launch timing and pricing of next-generation obesity drugs, particularly amid speculation over lower prices and dose-based pricing models. This, in turn, triggered swift competitive responses, including aggressive wholesale price reductions by incumbent products. The unfolding commercial rivalry between the two leading therapies—played out across pricing, supply, and market access—kept readers closely engaged.

Beyond traffic rankings, the scale of coverage underscored the issue’s prominence. The keywords “obesity” and “GLP-1” appeared a combined 332 times across Hit News content in 2025, ranking third among all keywords. Reported nearly once per day on average, obesity treatments firmly established themselves as one of the year’s central industry themes.  

Artificial intelligence emerged as the most dominant keyword of the year, appearing 524 times across Hit News coverage—the highest frequency of any topic in 2025. AI further solidified its role as a mega-trend reshaping the structural direction of the pharmaceutical and biotech industries.

AI-driven innovation extended beyond drug discovery, influencing regulatory thinking and investment behavior. As the U.S. FDA formally advanced AI-based Next Generation Approaches (NAMs)—widely interpreted as a step toward reducing reliance on animal testing—industry responses reflected both optimism and caution, highlighting unresolved technical and validation challenges.

Meanwhile, global pharmaceutical companies accelerated large-scale AI partnerships, intensifying competition in drug discovery speed and efficiency. A notable milestone came when an AI-designed TNIK inhibitor demonstrated meaningful efficacy in pulmonary fibrosis, marking the first case in which artificial intelligence led the entire development process through clinical proof of concept. The achievement fueled renewed debate over how close the industry may be to a fundamentally AI-driven drug development paradigm.