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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

從炒作到現實,人工智能重塑了從藥物發現到營銷的製藥行業——值得關注的股票
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.

製藥公司站在人工智能的最前沿已有一段時間了。甚至在最近的興趣激增之前,研究人員就一直在使用先進的人工智能模型來了解疾病機制。

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

週三,Alphabet Inc(納斯達克股票代碼:GOOG)(納斯達克股票代碼:GOOGL)谷歌DeepMind的研究人員開發了新的人工智能(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 可以預測生物分子的結構和相互作用。這包括蛋白質、DNA、RNA 和可以用作藥物的小分子。

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.

根據麥肯錫全球研究所的最新報告,人工智能技術每年可以爲製藥行業創造600億至1,100億美元的經濟價值,因爲它可以幫助加快化合物的鑑定、開發和批准的過程。

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.

該報告補充說,生成式人工智能對藥品的影響預計將是深遠的,因爲基礎模型建立在語言、圖像、組學、患者信息和其他類型的數據之上,這些數據彙集在一起,可以解釋和解決疾病過程和有效的治療方法。

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.

提高藥物發現、審批和上市速度可以幫助公司解決資產生命週期壓縮問題,即公司獲得新藥價值的時間越來越短。

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

麥肯錫的研究表明,該時間已從過去20年的11.7年減少到9.8年。

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

儘管發現速度很快,但發現和開發新藥的平均成本卻增加了。

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.

使用增強基礎模型的生成式人工智能可以幫助加速製藥研究,藥物發現時間縮短了近一半。人工智能技術的研究和發現可能具有150億至280億美元的潛在經濟價值。

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.

該報告指出,將一種新藥推向市場平均需要十年和大約14億美元,其中80%與臨床開發有關。

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

生成式人工智能通過提高整個臨床開發過程的效率來解決痛點,解鎖130億至250億美元的經濟價值。

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

報告稱,生成式人工智能工具可以加深護理提供者、藥劑師、保險公司和患者之間的關係,從而實時微調活動策略。

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

製藥專業人員和患者將擁有大量數據,可以做出更快、更明智的決策,從而提供180億至300億美元的潛在機會。

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

2023年,世界衛生組織發佈了一份綜合出版物,重點介紹了在醫療保健中利用人工智能潛力的關鍵監管注意事項。

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(場外交易代碼:BAYRY)和谷歌雲宣佈合作開發人工智能解決方案,爲放射科醫生提供支持。

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.

塑造市場的主要參與者包括英偉達公司(納斯達克股票代碼:NVDA)、英特爾公司(納斯達克股票代碼:INTC)、國際商業機器公司(紐約證券交易所代碼:IBM)、谷歌、通用電氣公司(紐約證券交易所代碼:GE)、微軟公司(納斯達克股票代碼:MSFT)、美敦力集團(紐約證券交易所代碼:MDT)、美光科技公司(納斯達克股票代碼:MU)、亞馬遜網絡服務和西門子Healthineers等行業巨頭。

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