Core Insights - The pharmaceutical industry is increasingly leveraging artificial intelligence (AI) to enhance drug development efficiency and reduce costs, with companies like In Silico demonstrating significant advancements in this area [1][2][8] - A notable trend is the shift from traditional acquisition strategies to targeted deals that focus on acquiring specific assets, particularly in response to impending patent expirations [4][10][14] AI in Drug Development - In Silico has showcased the potential of AI in drug development, reporting an average of 13 months from project initiation to candidate selection for its drug rentosertib, which has shown positive signals in increasing lung function in a Phase IIa study [1] - AI-driven tools are sought by pharmaceutical companies to enhance internal R&D productivity and streamline the drug development process [2][3] Patent Expirations and Industry Response - The upcoming patent cliff between 2024 and 2030 is projected to reduce the global share of drugs protected under patents from 6% to 4%, resulting in an estimated loss of $236 billion in US revenues [6][7] - The industry is witnessing a surge in deal-making as companies seek to replenish their drug pipelines in light of patent expirations, with AI partnerships becoming increasingly common [7][9] Changing Acquisition Strategies - Pharmaceutical companies are moving away from large-scale mergers and acquisitions (M&A) towards smaller, asset-specific acquisitions to mitigate revenue losses from patent expirations [10][14] - Companies like Eli Lilly and AstraZeneca are actively pursuing AI capabilities through strategic partnerships, indicating a shift in mindset towards more targeted investments [4][11] Market Dynamics and Future Trends - The hierarchy of top-selling drugs is shifting, with a growing focus on metabolic disorders and peptide-based drugs, while oncology remains a significant area of interest [16][17][18] - Companies are also exploring secondary patents and trademarks as strategies to extend the lifecycle of branded drugs and maintain revenue streams despite patent expirations [20][22] Conclusion - AI is positioned as a transformative force in the pharmaceutical industry, with the potential to reshape drug development timelines and strategies for managing patent cliffs, although its impact may vary [23]

位于波士顿的生物技术公司Insilico Medicine似乎是首家将新一代人工智能（称为Transformer模 型）应用于药物研发领域的公司。早在2019年，该公司的研究人员就思考能否利用这些模型，根据 生物和化学数据研发新药。他们的首要目标是特发性肺纤维化，一种肺部疾病。 他们首先利用与该疾病相关的数据集训练人工智能，并找到了一种很有前景的靶蛋白。随后，第二 个人工智能推荐了一些能够与该蛋白结合并改变其行为，但毒性和稳定性又不太高的分子。之后， 由化学家接手，合成并测试了筛选出的分子。他们将最终成果命名为rentosertib，该药物近期已成 An AI revolution in drugmaking is under way 它将彻底改变药品的生产方式，以及整个行业本身。 阿特里克·施瓦布并非普通的药物研究员，他的工作场所也并非普通的制药实验室。这里既没有实验 台，也没有冒泡的液体，更没有白大褂。施瓦布博士总是身着一身黑衣。但这对于他位于国王十字 区的工作场所来说，倒也十分贴切。国王十字区曾是铁路货场和工业区，如今经过改造，已成为伦 敦最令人艳羡的时尚街区之一。 施瓦布博士就职于葛兰素史克（GSK） ...