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From Hype To Reality, AI Reshapes Pharmaceutical Industry Across Drug Discovery To Marketing - Stocks To Watch

From Hype To Reality, AI Reshapes Pharmaceutical Industry Across Drug Discovery To Marketing - Stocks To Watch

从炒作到现实,人工智能重塑了从药物发现到营销的制药行业——值得关注的股票
Benzinga ·  05/10 14:49

Pharmaceutical companies have been at the forefront of artificial intelligence for quite some time. Researchers have been using advanced AI models to understand disease mechanisms even before the recent surge in interest.

制药公司站在人工智能的最前沿已有一段时间了。甚至在最近的兴趣激增之前,研究人员就一直在使用先进的人工智能模型来了解疾病机制。

Wednesday, researchers at Alphabet Inc's (NASDAQ:GOOG) (NASDAQ:GOOGL) Google DeepMind developed AlphaFold 3, a new artificial intelligence (AI) model.

周三,Alphabet Inc(纳斯达克股票代码:GOOG)(纳斯达克股票代码:GOOGL)谷歌DeepMind的研究人员开发了新的人工智能(AI)模型AlphaFold 3。

AlphaFold 3 can predict the structure and interactions of biological molecules. This includes proteins, DNA, RNA, and small molecules that could function as drugs.

AlphaFold 3 可以预测生物分子的结构和相互作用。这包括蛋白质、DNA、RNA 和可以用作药物的小分子。

According to the latest McKinsey Global Institute report, AI technology could generate $60 billion—$110 billion annually in economic value for the pharmaceutical industry, as it can help speed up the process of identifying compounds, their development, and approval.

根据麦肯锡全球研究所的最新报告,人工智能技术每年可以为制药行业创造600亿至1,100亿美元的经济价值,因为它可以帮助加快化合物的鉴定、开发和批准的过程。

The report adds that generative AI's impact on pharmaceuticals is expected to be profound as the foundational models are built on languages, images, omics, patient information, and other types of data that come together to explain and solve the disease process and effective treatment ways.

该报告补充说,生成式人工智能对药品的影响预计将是深远的,因为基础模型建立在语言、图像、组学、患者信息和其他类型的数据之上,这些数据汇集在一起,可以解释和解决疾病过程和有效的治疗方法。

Increased drug discovery, approval, and marketing speed can help companies resolve the asset life cycle compression issue, which is the diminishing amount of time companies have to capture the value of the new drug.

提高药物发现、审批和上市速度可以帮助公司解决资产生命周期压缩问题,即公司获得新药价值的时间越来越短。

McKinsey's research shows that the time has decreased to 9.8 years from 11.7 years over the past 20 years.

麦肯锡的研究表明,该时间已从过去20年的11.7年减少到9.8年。

Despite the speedy discovery, the average cost of discovering and developing new drugs has increased.

尽管发现速度很快,但发现和开发新药的平均成本却增加了。

Generative AI using augmented foundational models can help accelerate pharma research, with drug discovery timelines cut by almost half. AI tech can have a potential economic value of $15 billion-$28 billion on research and discovery.

使用增强基础模型的生成式人工智能可以帮助加速制药研究,药物发现时间缩短了近一半。人工智能技术的研究和发现可能具有150亿至280亿美元的潜在经济价值。

The report notes that, on average, ten years and around $1.4 billion are needed to bring one new drug to the market, of which 80% is associated with clinical development.

该报告指出,将一种新药推向市场平均需要十年和大约14亿美元,其中80%与临床开发有关。

Generative AI addresses pain points by increasing efficiency across the clinical development process, unlocking the economic value of $13 billion to $25 billion.

生成式人工智能通过提高整个临床开发过程的效率来解决痛点,解锁130亿至250亿美元的经济价值。

Generative AI tools can deepen relationships between care providers, pharmacists, insurers, and patients to fine-tune campaign strategies in real time, per the report.

报告称,生成式人工智能工具可以加深护理提供者、药剂师、保险公司和患者之间的关系,从而实时微调活动策略。

Pharma professionals and patients will have substantial data to make faster, smarter decisions, providing a potential opportunity of $18 billion to $30 billion.

制药专业人员和患者将拥有大量数据,可以做出更快、更明智的决策,从而提供180亿至300亿美元的潜在机会。

In 2023, the World Health Organization unveiled a comprehensive publication highlighting critical regulatory considerations for harnessing the potential of AI in healthcare.

2023年,世界卫生组织发布了一份综合出版物,重点介绍了在医疗保健中利用人工智能潜力的关键监管注意事项。

In April, Bayer AG (OTC:BAYRY) and Google Cloud announced a collaboration to develop AI solutions to support radiologists.

4月,拜耳公司(场外交易代码:BAYRY)和谷歌云宣布合作开发人工智能解决方案,为放射科医生提供支持。

Key players shaping the market include industry giants such as Nvidia Corp (NASDAQ:NVDA), Intel Corporation (NASDAQ:INTC), International Business Machines Corporation (NYSE:IBM), Google, General Electric Co (NYSE:GE), Microsoft Corporation (NASDAQ:MSFT), Medtronic Plc (NYSE:MDT), Micron Technology Inc (NASDAQ:MU), Amazon Web Services, and Siemens Healthineers.

塑造市场的主要参与者包括英伟达公司(纳斯达克股票代码:NVDA)、英特尔公司(纳斯达克股票代码:INTC)、国际商业机器公司(纽约证券交易所代码:IBM)、谷歌、通用电气公司(纽约证券交易所代码:GE)、微软公司(纳斯达克股票代码:MSFT)、美敦力集团(纽约证券交易所代码:MDT)、美光科技公司(纳斯达克股票代码:MU)、亚马逊网络服务和西门子Healthineers等行业巨头。

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