{"id":379343,"date":"2026-03-11T11:20:11","date_gmt":"2026-03-11T11:20:11","guid":{"rendered":"https:\/\/www.europesays.com\/ie\/379343\/"},"modified":"2026-03-11T11:20:11","modified_gmt":"2026-03-11T11:20:11","slug":"pharmas-ai-investment-signals-new-drug-discovery-paradigm","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ie\/379343\/","title":{"rendered":"Pharma\u2019s AI Investment Signals New Drug Discovery Paradigm"},"content":{"rendered":"

From improved molecular design to AI-driven automation, waves of AI tools promise to accelerate therapeutic development. Still, skeptics ask whether this momentum reflects real transformation or simply hype in drug discovery.<\/p>\n

Mike Nally, CEO of Generate:Biomedicines, emphasizes that the promise of AI lies in delivering better medicines to patients faster. What is typically a 10\u201315-year journey from discovery to clinical approval, he says, could potentially be compressed into an eight-year paradigm with AI technologies.<\/p>\n

Founded in 2018, the Flagship Pioneering company recently completed one of the industry\u2019s largest IPOs in years, raising $400 million in gross proceeds toward clinical trials and R&D efforts. Generate\u2019s AI platform includes an optimization stack guided by existing molecules, and a second layer that designs proteins from scratch.<\/p>\n

Generate\u2019s optimization approach gives machine learning models an existing therapeutic binder as a starting point. Researchers then computationally learn the functional landscape to improve the molecule for clinical drug properties. The company\u2019s current workflows can complete optimization rounds within a couple of weeks, while three rounds of design optimization, on average, are sufficient to reach the desired criteria.<\/p>\n

Nally tempers that new computational tools are not a panacea for every part of drug development.<\/p>\n

\u201cIf you pick the wrong target, dose, or patient population, no technology will overcome those things,\u201d he said. \u201cIf you have a transformational technology, you have to first prove the technology works in the clinic.\u201d<\/p>\n

\"GB-0895GB-0895, an anti-TSLP antibody for severe asthma, is the first \u201cAI-derived\u201d antibody to enter Phase III clinical trials [Generate:Biomedicines]In December, Generate announced that its most advanced program, GB-0895, an anti-thymic stromal lymphopoietin (TSLP) antibody for severe asthma, entered Phase III clinical trials. GB-0895 is the first \u201cAI-derived\u201d antibody to reach this clinical milestone, progressing from discovery to Phase III within five years. The two global studies, SOLAIRIA\u20111 and SOLAIRIA\u20112, will evaluate GB-0895 in approximately 1,600 adults and adolescents with severe asthma.<\/p>\n

More shots on goal<\/strong><\/p>\n

In preclinical discovery, researchers grapple with identifying the right molecule to advance to the clinic. AI promises to accelerate multiple stages of the pipeline\u2014from target discovery and molecular design to clinical validation.<\/p>\n

\u201cHave we seen a big impact yet? We are still not there, especially on the research side,\u201d said Sai Jasti, SVP, head of data science and AI at Bayer, when describing the role of AI platforms. He says Bayer has an internal goal to increase R&D productivity by 40% in 2030.<\/p>\n

To achieve this aim, Bayer has entered a three-year strategic collaboration with Cradle, an AI-based protein design company, to accelerate protein optimization across Bayer\u2019s therapeutic antibody pipeline. By reducing the number of optimization cycles and improving developability properties, including potency, safety, and manufacturability, Cradle\u2019s platform will expand Bayer\u2019s biologics portfolio.<\/p>\n

\"CradleCradle platform users can view detailed information about their generated sequences. The platform also provides an overview of user design strategy and configurations, and access to generation reports and round results to move protein engineering projects forward more efficiently. [Cradle]Anastasia Hager, PhD, head of drug discovery sciences, SVP, pharma R&D at Bayer, says the company has been on a journey to replenish its early pipeline given growth across multiple indications, including cardiovascular, immunology, oncology, and neurodegenerative disease.<\/p>\n

\u201cThe most exciting piece is enabling creativity to test different sequences while unlocking target and structural space,\u201d said Hager when describing the value-add of Cradle\u2019s platform. \u201cWe\u2019re committed to enhancing our pipeline with data science and AI as key tools for the biologics portfolio.\u201d<\/p>\n

When moving molecules through the clinic, Stef van Grieken, co-founder and CEO at Cradle, says translation is not a solved problem. Yet, the ability to more quickly identify candidates early in the development pipeline while increasing biological understanding of the target will \u201cprovide more shots on goal\u201d to support informed decisions during drug development.<\/p>\n

In that vein, Jasti emphasizes that the partnership is \u201cnot just a software deal,\u201d but a collaboration on the scientific and machine learning level, where scientists from both organizations will exchange ideas and expertise on research direction. Cradle\u2019s platform will also be embedded in Bayer\u2019s workflows to improve accessibility for scientists in the lab.<\/p>\n

Year of deployment<\/strong><\/p>\n

While traditional tech-pharma collaborations focus on a small number of drug targets, 2026 kicked off with a stream of AI platform deals across pharma, signaling a cultural shift of investing in AI infrastructure for broad discovery.<\/p>\n

\u201cIf 2025 was the year of breakthrough research, we believe 2026 will become the year of deployment,\u201d said Jack Dent, co-founder at Chai Discovery, an AI-driven biologics company developing therapeutics against undruggable targets.<\/p>\n

Chai\u2019s core technology centers on Chai-2, a de novo antibody design model capable of generating full-length antibodies with therapeutic attributes. The model speeds up workflows by reducing reliance on labor-intensive and time-consuming experimental screens.<\/p>\n

Earlier this year, Chai announced a collaboration with Eli Lilly to deploy Chai\u2019s technology to design novel biologics for multiple targets. Chai will also develop an exclusive AI model for Lilly that is trained on the pharma giant\u2019s proprietary data and tailored to Lilly\u2019s discovery workflows.<\/p>\n

According to Aliza Apple, PhD, vice president of Lilly Catalyze360 AI\/ML and global head of Lilly TuneLab, Lilly\u2019s tech philosophy centers on being an early adopter of promising tools. She emphasizes that models must be trained on quality data and undergo rigorous testing to design better molecules.<\/p>\n

\u201cWe want to lean in early to the tools that look truly differentiated and put Lilly\u2019s weight behind them, not just rely on what we\u2019ve already built,\u201d said Apple. Rather than outsourcing therapeutic design, the collaboration with Chai gives Lilly scientists direct access to Chai\u2019s generative AI capabilities.<\/p>\n

From molecules to humans<\/strong><\/p>\n

Other biotechs have focused their efforts entirely on building platforms, rather than developing drugs internally. Boltz, an AI research and product company, launched in January with $28 million, with a mission to advance open science for drug discovery.<\/p>\n

The public benefit corporation (PBC) is co-founded by MIT researchers\u2014Gabriele Corso, PhD, Jeremy Wohlwend, PhD, and Saro Passaro, known as the developers of the widely adopted Boltz series of models. The Boltz team first made waves in November 2024, with the launch of the co-folding model, Boltz-1, a fully commercially available AI model to achieve AlphaFold 3-level accuracy in predicting the 3D structure of biomolecular complexes.<\/p>\n

Boltz has already solidified a multi-year collaboration with Pfizer to build \u00a0exclusive models that improve target selection for structure prediction, small-molecule affinity, and biologics design. Boltz scientists will also build custom models and workflows with Pfizer for a number of target programs to \u00a0enhance preclinical decision-making.<\/p>\n

Corso, who leads Boltz as CEO, said two realizations drove the decision to turn the Boltz models into an enterprise.<\/p>\n

\u201cFirst, continuing to push the frontier of biomolecular AI requires sustained investment in talent, compute, and data at a scale not attainable within academic environments,\u201d Corso explained. \u201cSecond, truly democratizing the technology, and maximizing its impact, means going beyond publishing models and building reliable, well-designed products that scientists could integrate directly into their daily work.\u201d<\/p>\n

While much of the industry is focused on molecular design, San Francisco-based Noetik is building biological foundation models trained on human data.<\/p>\n

Ron Alfa, MD, PhD, CEO of Noetik, emphasizes that a huge gap remains for large-scale translational data, preventing drugs from succeeding in the clinic. As an answer, the company generates multimodal data from human tissue samples with an intact in vivo context. These data fuel Noetik\u2019s foundation models, which predict clinical outcomes in cancer.<\/p>\n

Earlier this month, Noetik announced a five-year licensing partnership with GSK, which gives the pharma giant access to Noetik\u2019s non-small cell lung cancer and colorectal cancer models. The deal includes a $50-million upfront payment and will follow a subscription-based framework.<\/p>\n

\"blueNoetik generates multimodal data from primary human tissue samples with intact in vivo context. These data train biological foundation models that can predict cancer clinical outcomes. [Noetik]Alfa describes the GSK partnership as one of the first true foundation model licensing deals in biotech. \u201cFor years, the sector has looked for a way to commercialize AI as infrastructure rather than the standard R&D collaborations,\u201d he said. \u201cNow, we have a template.\u201d<\/p>\n

Whether AI-driven drug discovery is reality or hype, rising pharmaceutical investment points to the former. The ultimate payoff, however, will be decided in the clinic.<\/p>\n","protected":false},"excerpt":{"rendered":"From improved molecular design to AI-driven automation, waves of AI tools promise to accelerate therapeutic development. Still, skeptics…\n","protected":false},"author":2,"featured_media":379344,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[275],"tags":[289,2235,139410,174356,3541,18,56584,174357,135,475,474,19,33689,17,174353,174354,174358,174355],"class_list":{"0":"post-379343","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-healthcare","8":"tag-artificial-intelligence","9":"tag-automation","10":"tag-bayer-ag","11":"tag-cradle-bio","12":"tag-drug-discovery","13":"tag-eire","14":"tag-eli-lilly-and-company","15":"tag-generatebiomedicines","16":"tag-health","17":"tag-health-care","18":"tag-healthcare","19":"tag-ie","20":"tag-insights","21":"tag-ireland","22":"tag-issue-no-3","23":"tag-march-2026","24":"tag-noetik","25":"tag-phase-ii-clinical-trials-clinical-trial"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@ie\/116210278387363079","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/379343","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/comments?post=379343"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/379343\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/379344"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=379343"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=379343"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=379343"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}