{"id":59271,"date":"2024-02-02T06:00:11","date_gmt":"2024-02-02T11:00:11","guid":{"rendered":"https:\/\/www.ino.com\/blog\/?p=59271"},"modified":"2024-02-03T09:03:05","modified_gmt":"2024-02-03T14:03:05","slug":"buy-alert-mercks-ai-revolution-and-the-role-of-generative-ai-in-drug-research","status":"publish","type":"post","link":"https:\/\/wwwtest.ino.com\/blog\/2024\/02\/buy-alert-mercks-ai-revolution-and-the-role-of-generative-ai-in-drug-research\/","title":{"rendered":"Buy Alert: Merck's AI Revolution and the Role of Generative AI in Drug Research"},"content":{"rendered":"

Advancements in Artificial Intelligence (AI) have yielded remarkable progress in technological and operational efficiencies across various sectors. Yet, AI's noteworthy penetration into the healthcare field is raising propositions of transformation.<\/span><\/p>\n

Pharmaceutical companies have been capitalizing on AI long before the recent surge in interest \u2013 the utilization of intricate AI models to decipher disease mechanisms serving as a prime example. AI-facilitated applications like AlphaFold2, ESMFold, and MoLeR offer novel insights into protein structures that unravel numerous diseases.<\/span><\/p>\n

While the most advanced AI-centric medicine entities have Phase 2 clinical trial drugs, the unlocking of AI-healthcare collaboration power, especially in fashioning potential cures for lethal diseases, will witness compelling progression in the upcoming years.<\/span><\/p>\n

Researchers today regard AI as a pioneering tool offering an expedited analysis of vast data quantities, surpassing human capabilities. Presently, drug development demands a decade or more in research and development, compounded by the escalating production costs over the past decade \u2013 a conundrum existing despite technological advancement.<\/span><\/p>\n

With AI's intervention, the feasibility of expediting this process, slashing developmental timeframes and drug production costs by up to 30%, emerges. There is also a reduction in failure risk, given the current approximately<\/span> 90% attrition rate<\/span><\/a>, depending on the therapeutic domain.<\/span><\/p>\n

GenAI (a subset of deep learning) embarks on a fresh leap in AI evolution and imbues computers with transformative abilities. Its arrival challenges us to envision its implications within the healthcare sphere, particularly drug discovery.<\/span><\/p>\n

While most ongoing projects are in their infancy stages, the merger of GenAI and drug discovery might instigate not only novel treatments but also breakthroughs potentially outpacing nature. GenAI is revolutionizing several facets of the pharmaceutical realm, from speeding up drug discovery, enhancing procedural efficiency in clinical trials, accelerating regulatory approvals, and ultra-targeting marketing to facilitating in-house medical materials production. GenAI's potential to unlock billions in industry value is imminent.<\/span><\/p>\n

By expediting drug compound identification processes and their corresponding development, approval, and efficient marketing, this technology could generate an economic value<\/span> between $60 to $110 billion annually<\/span><\/a> for the pharma and medical-product industries.<\/span><\/p>\n

The looming GenAI-steered transformation in life sciences lends immeasurable advancements to human health and quality of life. An accelerated drug discovery process, for instance, aids in combating diseases swiftly, freeing up resources for underserved areas such as orphan diseases.<\/span><\/p>\n

GenAI\u2019s capability to derive patterns and insights from extensive patient data will ignite more personalized treatments, hence improving patient outcomes and streamlining patient care by minimizing discrepancies in therapeutic manufacture and delivery.<\/span><\/p>\n

Lastly, by automating mundane tasks like document creation and record-keeping, GenAI carries significant potential to augment productivity within the medical research field and enables researchers and medical liaisons to devote more time to patient-centered tasks. In turn, this holds promise for improved service to both clinicians and patients.<\/span><\/p>\n

Pharmaceutical powerhouse<\/span> Merck & Co., Inc. (MRK)<\/span><\/a> has set sights on exploring GenAI platforms. The company's interest comes on the heels of the Merck Research Labs collaboration announcement with<\/span> Variational AI<\/span><\/a>, supported by the CQDM Quantum Leap program.<\/span><\/p>\n

At the core of this innovation is Variational AI, a trailblazer in optimizing drug discovery and development through the efficient employment of GenAI. This potent technology called Enki offers a novel approach to drug discovery. Drawing parallels with AI software like DALL-E and Midjourney, which can translate text prompts into visual images, Enki generates small molecular structures in response to target product profiles (TPPs). The user picks the desirable attributes, selecting the targets they aim to affect alongside those they seek to avoid; then, Enki produces molecules tailored to meet the TPP specifications.<\/span><\/p>\n

Constructed as a fundamental model for small molecule drug discovery, Enki serves to hasten and mitigate risks attached to the early stages of discovery. The startup believes that a series of prompts about the TPP is all that stands between users and innovative, selective, and lead-like structures ready for synthesis. Utilizing experimental data, Variational trained Enki to generate molecules based on TPPs, thereby handing researchers the tool to canvas a broader scope of chemical space.<\/span><\/p>\n

Thanks to the Enki Platform, chemists can bypass the complex process of developing their own GenAI models. They can input their TPP and receive an array of innovative, diverse, selective, and synthesizable lead-like structures within days, facilitating a swift transition into lead optimization. With this dynamic start, it is evident that MRK, the leading purveyor of pharmaceuticals, aims to make a significant splash in the new year.<\/span><\/p>\n

Several other factors present an optimistic outlook for MRK in 2024.<\/span><\/p>\n

MRK's flagship oncology drug, Keytruda \u2013 the highest-grossing prescription medication worldwide \u2013 is slated to gain approval for additional uses. In 2023 alone, Keytruda grossed a remarkable $25.01 billion, equating to 45.2% of MRK's fourth-quarter sales. Forecasters project Keytruda to yield over<\/span> $30 billion in sales by 2026<\/span><\/a>.<\/span><\/p>\n

MRK has already seen the tangible effects of its 2023 transactions, substantially boosting the company's future revenue projections. The pharma giant now anticipates garnering $20 billion from fresh oncology products in development by the mid-2030s, almost doubling its earlier pipeline forecast of just over $10 billion.<\/span><\/p>\n

However, as Keytruda approaches its patent expiration in 2028, MRK is already searching for strategic acquisitions within $15 billion, preparing to weather the ensuing patent erosion. This effort is to ensure continuous growth through novel lucrative ventures, replacing the revenue stream provided by Keytruda upon losing its exclusiveness.<\/span><\/p>\n

MRK's proactive approach comes on the heels of its recent $680 million acquisition of Harpoon Therapeutics, following the larger purchases of Prometheus Bio ($10.8 billion) and Acceleron Pharma ($11.5 billion).<\/span><\/p>\n

MRK, buoyed by solid fourth-quarter performances backed by strong Keytruda sales, has secured several deals over the past year. Notably, this includes a notable $5.5 billion agreement with Japan's Daiichi Sankyo, granting co-development rights for three antibody-drug conjugate cancer treatments. This partnership has contributed to MRK's non-GAAP R&D expenses, increasing them to $9.63 billion in the fourth quarter of 2023 and $30.53 billion for fiscal 2023.<\/span><\/p>\n

Aside from its dominant presence in the oncology sphere, MRK is also targeting the<\/span> weight loss medication market<\/span><\/a>. The company is developing Efinopegdutide, a GLP-1 class drug for weight management that has demonstrated promising trial results.<\/span><\/p>\n

After securing only 1% year-over-year sales growth in fiscal year 2023, analysts project a 5.3% year-over-year increase in the fiscal year ending December 2024. This predicted growth is expected to propel the company\u2019s EPS to $8.49, a 462.1% year-on-year increase.<\/span><\/p>\n

MRK estimates its global sales between $62.70 billion and $64, while non-GAAP EPS is expected to be between $8.44 and $8.59.<\/span><\/p>\n

Furthermore, MRK boasts an impeccable dividend history, with the annual dividend currently at $3.08 per share, yielding 2.55%. In an impressive display of consistency, MRK has increased its dividend for 13 consecutive years and holds a four-year average yield of 2.97%. Also, over the past three and five years, its dividend grew at a CAGR of 7.8% and 9.3%, respectively.<\/span><\/p>\n

MRK\u2019s shares have gained over 15% year-to-date to close the last trading session at $126.38. Moreover, it trades above the 50-, 100-, and 200-day moving averages of $110.53, $107.39, and $109.24, respectively. If this upward trajectory persists, the company is poised for a notable performance in 2024.<\/span><\/p>\n

Bottom Line<\/b><\/p>\n

With the employment of GenAI, the pharma industry has made a considerable stride forward, leading to significant operational enhancements and quicker benefit realization, especially in drug discovery. The<\/span> GenAI in drug discovery<\/span><\/a> market is projected to surpass around $1.13 billion by 2032, growing at a CAGR of 27.1%.<\/span><\/p>\n

MRK has swiftly evaluated and addressed the potential impact of GenAI, demonstrating commendable adaptability in deploying the most appropriate tool for each specific use case. This technology holds great promise for MRK's research, trials, manufacturing, and commercialization endeavors.<\/span><\/p>\n

Partnerships formed between MRK, AI technology firms, and research institutions could catalyze innovation in GenAI for drug discovery and bolster the company's product pipeline in the future. MRK, with an abundant oncology pipeline, is utilizing advanced technology for drug research. Furthermore, MRK shares are compelling due to robust shareholder returns, growth prospects, solid profitability, and an optimistic outlook.<\/span><\/p>\n

However, the stock is priced at a premium compared to its competitors. In addition, despite displaying consistency in its dividend payment, its yield of 2.55% sits not only below the U.S. consumer inflation rate but also under that of its healthcare counterparts, potentially rendering MRK a less appealing proposition for conservative investors.<\/span><\/p>\n

Further complicating matters, government regulations and the Inflation Reduction Act might unfavorably affect MRK's operations. Modifications such as negotiations with Medicare, implementation of medication discounts covered under Medicare Part B and D, and enforced penalties for escalating drug prices pose potential financial risks.<\/span> MRK's Januvia<\/span><\/a> ended up on this list, jeopardizing the financial stability of MRK's diabetes franchise.<\/span><\/p>\n

Sales for the Januvia\/Janumet (diabetes) franchise declined 13% year-on-year to $787 million in the fiscal fourth quarter of 2023. The drug's sales suffered due to dwindling demand in the U.S. and generic competition in certain international markets. Such regulatory restraints could decelerate MRK\u2019s future revenue growth, pressuring management to reassess its R&D approach.<\/span><\/p>\n

Therefore, investors are advised to weigh both the positive and negative factors prudently before investing in this stock.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Advancements in Artificial Intelligence (AI) have yielded remarkable progress in technological and operational efficiencies across various sectors. Yet, AI's noteworthy penetration into the healthcare field is raising propositions of transformation. Pharmaceutical companies have been capitalizing on AI long before the recent surge in interest \u2013 the utilization of intricate AI models to decipher disease mechanisms […]<\/p>\n","protected":false},"author":41,"featured_media":59014,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[33547,33550,33549,33545,32518,32517,33544,33548,33546],"class_list":["post-59271","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-general","tag-30-billion-in-sales-by-2026","tag-90-attrition-rate","tag-between-60-to-110-billion-annually","tag-genai-in-drug-discovery","tag-inc-mrk","tag-merck-co","tag-mrks-januvia","tag-variational-ai","tag-weight-loss-medication-market"],"yoast_head":"\nBuy Alert: Merck's AI Revolution and the Role of Generative AI in Drug Research - INO.com Trader's Blog<\/title>\n<meta name=\"description\" content=\"The process of drug discovery is one of the most significant and challenging realms of medical science. 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