Up to $2.02 Billion in Deals: Major AI-Pharma Collaborations of the Year

October 10,XtalPiAilux Biologics, a biopharmaceutical discovery business line under XtalPi, and Johnson & JohnsonJanssen Biotech, Inc.Sign the authorization agreement,The core of the agreement is XtalPi's proprietary bio-AI platform.Ailux Biologics has authorized Jassen and its affiliated companies to use the XtalFold™ platform for the discovery and engineering design of biologics.

XtalFold™ utilizes sequence information to model interactions between biomolecules, which form the basis of biopharmaceuticals such as monoclonal antibodies.

October 7,AstraZeneca Announces Partnership with CSPC, jointly advancing the development of a novel preclinical small molecule lipoprotein(a) (Lp(a)) inhibitor YS2302018.

According to the agreement, CSPC will obtain AstraZenecaAn upfront payment of 100 million US dollars and the right to collectHighest$370 millionPotential Development Milestone Payments and MaximumPotential sales milestone payments of $1.55 billionTotaling $2.02 billion,As well as tiered sales royalties calculated based on the annual net sales of the product. AstraZeneca will obtain exclusive global rights to develop, manufacture, and commercialize the compound and the product.

According to the announcement by CSPC, YS2302018 was discovered by CSPC's AI-driven small molecule drug design platform. The platform uses AI technology to analyze the binding modes of target proteins with existing compound molecules, optimizes drug-like properties in a targeted manner, and ultimately selects a highly effective and development-friendly Lp(a) small molecule inhibitor.

This deal shows us that not only AI pharmaceutical companies can license out their technologies, but traditional pharmaceutical enterprises can also delve deeply into AI and gain recognition from overseas giants.

September 30,Regor Therapeutics and GenentechReach a final purchase agreement. Genentech will purchase Regor Therapeutics.Next-Generation CDK Inhibitors, for the treatment of breast cancer, with an upfront payment of $850 million in cash. Additionally, Regor Therapeutics is eligible to receive future development, regulatory, and commercialization milestone cash payments.The upfront payment of $850 million has set a new record for the largest upfront payment in China's AI pharmaceutical licensing deals.

In 2024, there were very few large-scale financings, butFormation Bio Successfully attracted $372 million in Series D funding. This round of financing was led by a16z.SanofiHeavyweight InvestorsFollow-on Investment.Sequoia Capital, Thrive Capital, and other investment institutions have participated in several rounds of financing for the company, while Sanofi is a new investor joining this round. Formation Bio (formerly TrialSpark) stated that it plans to use the funds to continue acquiring and licensing clinical-stage assets from biotechnology and pharmaceutical partners.                

Left: Ben Liu, Chief Executive Officer & Co-Founder of Formation Bio

Notably, just one month before the financing, on May 21,SanofiJustFormation Bio, OpenAI Announce First-of-Its-Kind CollaborationThe three companies pooled their data, software, and fine-tuned models to jointly develop customized solutions dedicated to the entire drug development lifecycle.A First in Peer Collaboration in Pharmaceutical and Life Science IndustriesAs Sanofi continues to move towards its goal of becoming "the first large-scale biopharmaceutical company driven by artificial intelligence," the company will leverage this partnership to provide access to proprietary data for the development of AI models.

Both cooperation and investment,Formation BioWhy Is Sanofi So Attracted? The Reason Lies in This CompanyThe technical platform can accelerate various aspects of clinical trials while improving quality, including study initiation, patient recruitment, and the continuous collection and validation of data.As is known to all, clinical trials are the most time-consuming, labor-intensive, and costly part of the drug development process, severely restricting the progress of drug development.

Traditional methods of patient recruitment and engagement often lead to incomplete patient data, slow operational responses, and ultimately delays in development plans. Additionally, conventional approaches to clinical data monitoring and analysis struggle to keep up with the growing volume and complexity of trial data, resulting in inefficiencies and blind spots. Formation Bio's platform can automatically ingest, harmonize, and clean clinical data, identify critical issues early on, provide deeper insights into each data source, prevent trial readout delays, unlock complex development plans and trial designs, and enable faster and better decision-making.

AsA Firm Supporter of AI, April 17,SanofiAlso announced that it willReal-World Data in Oncology (RWD) and analytics leader Cota Healthcare collaboration, leveraging RWD and AI to accelerate cancer trials, with a particular focus on multiple myeloma. The aim of this collaboration is to gain a deeper understanding of clinical outcomes, obtain valuable insights, and ultimately benefit cancer patients.

Although MNCs generally hold a positive attitude toward the potential of AI in improving drug development efficiency and are boldly experimenting, expertise has its own specialization. MNCs usually do not invest resources in developing tools themselves, except for...Enter the AI Track through Equity Investment, and another approach isLeverage the existing platforms of professional AI technology companies。

October 5,AI Biotech Owkin Announces Collaboration with AstraZeneca, Developing AI for Breast CancergBRCA Pre-ScreeningSolution. This solution utilizes Owkin's extensive data network and cutting-edge AI can optimize the pre-screening of gBRCA gene mutations in breast cancer directly from digitized H&E pathology slides, improve gBRCA identification, and expand access to novel treatment options.

To ensure the tool performs powerfully across various laboratory environments, the development process will utilize high-quality data from more than 6,500 whole-slide images (WSI), sourced from approximately 2,000 patients who have undergone surgical resections and biopsies. Half of these patients have gBRCA mutations.

Typically, from the initial consultation to the issuance of test results, patients undergo testing for breast cancer susceptibility genes. (BRCA) testing can take months and involve multiple healthcare workers, significantly impacting patient outcomes. The gBRCA pre-screening solution has the potential to greatly enhance the efficiency of identifying BRCA gene mutations. In less than an hour, this solution can use existing materials such as H&E slides to identify high-risk patients carrying gBRCA mutations. This will greatly streamline the gBRCA testing process, enabling oncologists and genetic counselors to expedite gBRCA testing for high-risk patients and promptly incorporate these results into treatment plans.

September 26,AstraZenecaAnnouncementExpand Cooperation with Immunai, reaching a multi-year cooperation agreement aimed at applying artificial intelligence-driven approaches in AstraZeneca's cancer immunotherapy clinical trial design.Immune Cell Atlas。

The two parties had previously collaborated on a single-cell analysis research project based on the immune system.Targets of Inflammatory Bowel Disease。

AstraZeneca has also utilized Immunai's multi-omics technology for development.CTLA-4 and PD-L1 Bispecific AntibodyvolrustomigThe drug is currently in Phase III clinical trials, with indications for lung cancer, cervical cancer, and head and neck cancer.

Immunai was founded by researchers and computer engineers from MIT, Harvard, and Stanford University. Headquartered in New York, the company is dedicated to documenting the functions of each type of cell and their interactions with the human body and various diseases, creating a digital map of the immune system.

At the end of 2021, this start-up company, founded in 2018, secured a whopping $215 million in Series B funding. Earlier in the same year,Immunai Secures $60 Million in Series A Funding. The funds will empower Immunai to expand from immuno-oncology into broader research areas such as autoimmune diseases, cardiovascular conditions, and neurological disorders, leveraging its proprietary cell atlas and an AI model known as the Immune Dynamics Engine (IDE).

After the agreement was renewed, Immunai will receive $18 million in the first phase of the new project. Immunai stated that the core of this collaboration is to identify patients most likely to respond to different treatments based on the characterization of the patient's immune system and the drug’s mechanism of action, covering clinical decision-making, dosage selection, and biomarker identification. AstraZeneca can then decide whether to expand the scope of cooperation between the two teams.

Immunai CEO Noam Solomon"In the statement, the Ph.D. said, 'Our successful advancement in drug development within the fields of oncology and immunology has naturally led to this collaboration. Bringing drugs to market is extremely challenging, time-consuming, and costly. Through this partnership with AstraZeneca, we are excited to leverage our AI engine IDE to enhance the efficiency of drug development and bring potential new therapies to patients.'"

September 24,Genenerate: BiomedicineAnnouncementWith NovartisAchieve Multi-Target Collaboration with Generative AIDiscovery and Development of Protein TherapiesThe Generate Platform, Generate's proprietary generative AI platform, integrates machine learning with high-throughput experimental validation. This collaboration combines The Generate Platform with Novartis' expertise and capabilities in target biology, biologics development, and clinical development to create novel therapies and accelerate drug discovery and development.

September 5,Lilly &RNA Specialty CompanyGenetic LeapReached a cooperation agreement to develop AI drugs.

The technological cornerstone of Genetic Leap is an AI model that supports the discovery of RNA-targeted drugs. The platform under Genetic Leap is characterized by discovering new targets and finding ways to tackle targets that have been validated but lack druggability. In 2022, Astellas collaborated with Genetic Leap, utilizing the platform to search for RNA-targeted small molecule drugs for an undisclosed oncology target.

Now, Eli Lilly has also become a partner of Genetic Leap. Eli Lilly will use its RNA-targeting AI platform to generate candidate gene drugs for selected targets. Eli Lilly will choose targets in high-priority areas, and Genetic Leap will focus on these targets.Searching for Oligonucleotide Drugs。

RNA is a naturally polarized molecule with a shallow binding pocket, once considered unsuitable for small molecules. However, in the past decade, some new biotech companies have emerged, starting to attempt targeting RNA. Arrakis Therapeutics is one, and Genetic Leap is another.

June 25,Eli LillyAnnouncementCompared with OpenAICollaborate, Utilizing OpenAI's Generative AI, to InventNew Antibacterial Drugs, to combat drug-resistant pathogens. Antimicrobial resistance (AMR) is one of the most serious public health and development threats in the field of global health.

January 7,Novartis &IsomorphicSign the agreement, the latter will be responsibleIdentificationFor three undisclosed targetsSmall MoleculesThe foundation of the Isomorphic platform isGoogle DeepMind’s AlphaFold AITechnology. Isomorphic indicates that the new iteration of AlphaFold is expanding from protein prediction to small molecule and nucleic acid prediction.

Isomorphic has four Nobel laureates as scientific advisors: CRISPR scientist Dr. Jennifer Doudna, Sir David MacMillan, Sir Paul Nurse, and Dr. Venki Ramakrishnan.

On the same day,IsomorphicAlsoWith Eli LillySimilar agreements have been signed, and coincidentally, they are also for several undisclosed targets.Discover Small Molecule Therapies。

As a large pharmaceutical enterprise that actively embraces AI,NovartisAs early as 2019With MicrosoftCollaborate to establish Novartis AI Innovation Lab, becoming one of the few MNC pharmaceutical companies with its own AI lab. The lab has two core objectives:

1. Combine Novartis' massive datasets with Microsoft's advanced AI solutions to build new AI models and applications, enhancing the ability to meet the next wave of medical challenges;

2. It will harness the power of AI to address the most challenging computational problems in the life sciences, starting with the intelligent and personalized delivery of generative chemistry, image segmentation, and analytical therapies.

Iya Khalil, Global Head of Novartis AI Innovation Center

Today, Novartis researchers can use AI to meticulously comb through the treasure trove of laboratory data accumulated from tens of thousands of past drug development experiments, which are buried in PDF files, Excel spreadsheets, and previous written descriptions of molecular chemical properties. Ultimately, the goal of Novartis scientists is to use computational models to assist.Predict which molecular structures are promising, or reveal which experiments in the tests would be most helpful, ensuring quality while shortening the testing process that currently takes years.

Buffett said: "Life is like rolling a snowball. Find the wet snow and a long hillside to make your wealth grow bigger and bigger." However, to roll a big snowball, in addition to a long slope and thick snow, you also need to "not neglect small things and keep working hard for a long time."Any form of attempt is worth encouraging, and any form of cooperation creates value.Every step forward will lead to the bright future depicted in "The Book of Rites: The Great Learning" as "Long slopes with deep snow, lush grass in deep ravines, dense and thriving forest on the mountains, and clear waters."

BiG Recent Conference

On October 26, the 3rd BioCalculation Conference Retained Column - The Second Roast Conference is Coming Soon!Will focus on hot topics such as investment and financing, industry sentiment, youth, and AI to develop plans, through scene transitions,Mentor Leading Newcomers,Explore the Integration of AI and Biomed Together!

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October 31,BiG, in collaboration with Citeline, will host a small-scale private autoimmune disease symposium at the end of October.Focus:TCE vs. CAR-T, Autoimmune Development Strategies，Live streaming online simultaneously,Stay tuned!

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