Moderna Procures Machine Learning Partnership to Boost Generative AI Use In Drug DiscoveryApr25

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Moderna Procures Machine Learning Partnership to Boost Generative AI Use In Drug Discovery

Summary: Moderna has announced a partnership between itself and OpenAI, allowing the biopharma firm to utilize the latter’s enterprise ChatGPT product to embed custom generative pre-trained transformers (GPTs) throughout all of its business functions, from the research to legal departments. Moderna hopes the OpenAI partnership will increase the number of products it rolls out over the next five years.

New data suggests the use of machine learning in drug discovery is expected to eventually cut costs associated with all phases of pharmaceutical development by up to two-thirds. Streamlining the drug rollout process with AI could prove to be a critical development for a number of biopharma firms facing steep patent cliffs throughout the second half of the decade. 

Related ETF & Stocks: VanEck Pharmaceutical ETF (PPH), Moderna, Inc. (MRNA)

Just a week after Moderna CEO Stéphane Bancel claimed that artificial intelligence (AI) would allow scientists to “understand most diseases” in the next three to five years, Moderna announced a partnership with ChatGPT developer OpenAI. The biotech company disclosed that its collaboration with OpenAI in early 2023 and noted that 750 generative pre-trained transformers (GPTs) developed in ChatGPT Enterprise are now “embedded across Moderna’s business functions – from legal, to research, to manufacturing, to commercial”.

The use of AI to speed the rollout of new drugs is especially critical for Moderna. MRP highlighted Moderna specifically last year as one of the companies that would need to move beyond the “COVID era” that supercharged profits at a number of major biopharma firms, but was increasingly fleeting by 2023. Moderna’s only product currently at the commercial stage is its COVID-19 vaccine and revenues from the shot fell by more than -45% YoY in Q4 2023. Further integration of AI, however, could help the company outpace its current plan to roll out 15 new products within the next five years.

Utilizing machine learning for drug discovery is not a new concept, but recent progress in scaling large language models (LLMs) by OpenAI and its peers has finally put AI in a position to be used more efficiently by virtually all employees across every part of the biopharma business. At Moderna, some 3,000 employees are now utilizing ChatGPT Enterprise and The Wall Street Journal reports that Bancel has laid out a goal for employees to use it at least 20 times a day.

Efficiencies provided by AI have been shown to speed up the initial screening process for potential treatments ten-fold, and reduce the cost by a thousand-fold, according to researchers at the University of Cambridge working on medicines for Parkinson’s disease. An unnamed data science head at a large pharmaceutical company told EY that traditional drug discovery takes about five years and costs roughly $400 million. Further, bringing that drug to market can cost nearly $2 billion. Generative AI could potentially bring costs down by $40 million – $400 million, a cut of up to 20%. Per an EY survey of senior research and development decision makers at biopharmaceutical and biotech companies, cost reductions from generative AI across all phases of drug development are expected to range from 15% – 22% across the next three-to-five-year period. In five to seven years, savings are expected to increase to a range of 22% – 33%. Once peak adoption of generative AI is reached, this expected range was forecast to be as high as 44% – 67%.

Earlier this week, AI drug discovery startup Xaira Therapeutics emerged from stealth mode with a massive $1 billion in committed funding, exhibiting the newfound level of excitement around machine learning in the biopharma space. An investment from Arch Venture Partners, one of the co-leaders of Xaira’s funding, was the largest in the venture firm’s nearly four-decade history. Xaira will use AI models to develop new ways to connect biological targets and engineered molecules to human diseases. Such models are similar to diffusion models that power image generators like OpenAI’s DALL-E and Midjourney but, rather than creating art, these aim to design molecular structures.

THEME ALERT – LONG Pharmaceuticals

MRP added LONG Pharmaceuticals to our list of themes on June 16, 2022 amid huge cash balances among pharma firms and rapidly declining biotech valuations opening up opportunity for the former to bolster pipelines with a trove of new drugs at a major discount. Though we’ve specifically highlighted the looming prominence of pharma industry “patent cliffs” throughout the next several years, noting that they are likely to increase M&A activity throughout the biopharma industry, recent dealmaking by Novo Nordisk shows that big pharma can also leverage their cash balances to boost the supply chains of in-demand drugs. A recent PwC report notes that the biopharma industry is looking for assets that can start to provide value from 2024 as patent cliffs have put about $180 billion in revenue for the largest companies at risk in the 2023 through 2028 time frame.

In addition to acquisitions, pharma companies could speed the development and deployment of new drugs through the use of AI technologies. Last October, The Wall Street Journal reported Johnson & Johnson had hired 6,000 data scientists and digital specialists in recent years to pursue drug discovery through machine learning. That has already helped the company design an experimental cancer drug that is scheduled to start human testing this year. Separately, BioNTech acquired AI startup InstaDeep last year in a deal valued at nearly $550 million, adding 290 specialists to its staff, with teams focused on bioengineering, data science, machine learning and software development.

According to an RBC count, the cumulative value of biopharma deals in 2023 topped $128 billion, more than doubling up on $61 billion in deals in 2022. EY’s 2024 Firepower report, which assesses the capacity of pharma companies to execute M&A deals based on the strength of their balance sheets, found that the top 25 companies have $1.37 trillion on hand to make deals. These assets can be deployed by pharma firms to bolster their drug and therapeutics pipelines as the weak performance of publicly traded biotech shares, compounded by massive layoffs and other economic disruptions to business at privately held operations, has made valuations increasingly attractive to possible big pharma buyers. Through the first eight months of 2023, a Fierce Biotech analysis shows the number of biotech companies that cut staff matched the total for full-year 2022, with 119 firms reporting workforce reductions. Per a recent survey commissioned by CRO Icon, 48% of biotechs are now using partnerships with big pharma firms as a financing method. Further, VC funds are expected to total just $24 billion for the year—the lowest tally in four years, according to PitchBook data.

Attractive prices, combined with particularly strong cash positions of large pharma companies will allow the pharmaceutical industry to ramp up the expansion of their pipelines at a favorable value. Since the initiation of this theme, the VanEck Pharmaceutical ETF (PPH) has returned 19%, thus far underperforming the S&P 500’s increase of 36% over that same period.

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