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Artificial intelligence (AI) is driving innovation in drug discovery. Recently, the rapid expansion of human genomic and transcriptomic data has created an environment where AI algorithms can analyze these datasets. As data volume and computing power grow in tandem, traditional experiment‑centric approaches are reaching their limits.

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Lexogen is a company that provides high‑quality RNA sequencing solutions, and Ochre Bio operates an AI‑based bioinformatics platform. Each company brings complementary strengths—data generation and data analysis, respectively. This complementarity can generate significant synergy for discovering new biomarkers from human data.

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Utilizing AI can compress target identification and lead‑compound screening timelines from years to months. This markedly improves cost‑effectiveness before entering clinical trials, enabling faster patient access. Ultimately, productivity across the entire therapeutic development pipeline is expected to increase.

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However, the use of human data raises privacy concerns and the risk of data bias. If AI models are not adequately validated, erroneous predictions can waste research funds. Therefore, transparent data governance and ongoing model validation are essential.