Source: PharmaDJ

Author:RuiRui LiEditor: Vitamin

The 2024 Nobel Prize was awarded to several scientists who have achieved significant breakthroughs in the field of artificial intelligence, including areas such as protein structure prediction and computational protein design. These research achievements have greatly advanced the progress of drug development. Through big data analysis, machine learning, and deep learning, AI is able to mine and analyze vast amounts of biomedical data.FurthermorePlay a key role in every aspect of drug development.

At the same time,An increasing number of AI + pharmaceutical newcomers are coming into the spotlight. These companies, with their unique technical advantages, have quickly "emerged" in the field of drug research and development, becoming an important force driving industry transformation.In addition, many pharmaceutical giants are also deepening their cooperation with AI companies to reduce costs, increase efficiency, and promote effective decision-making.

In the target discovery phase,AI can quickly and accurately identify potential disease-related targets from vast amounts of biological information, significantly reducing the time required for target discovery.In terms of drug molecular design,AI can design drug molecules with higher activity and selectivity based on the structure and properties of the target, improving the success rate of drug development.In the clinical trial phase,AI can also optimize trial design through data analysis, improve trial efficiency, and reduce trial costs. At these different stages of R&D, there are AI + pharmaceutical companies with various strengths.

Atomwise is a technology-based pharmaceutical company located in San Francisco, USA, dedicated to using AI to revolutionize the discovery of small molecule drugs. Its AtomNet^®The platform uses deep learning for structure-based drug design, and its virtual HTS method can search an ever-expanding chemical library composed of over 15 trillion synthesizable compounds, accurately identifying hits that are distinct from any known binders, enabling rapid discovery from a vast, unexplored chemical space.

In 2022, Atomwise signed a strategic multi-target research collaboration with Sanofi, utilizing its AtomNet^®Platform Targets Five Key Areas in Drug Development, Sanofi Pays $20M Upfront with Potential Milestones Tied to Research, Development, and Sales Possibly Exceeding $1B. This Collaboration Highlights Atomwise's Technical Strength and AI’s Significant Potential in Drug Discovery.

Exscientia, a UK-based AI-driven precision medicine company, merged with Recursion last year. At the end of 2021, Genentech, under Roche, reached a collaboration with Recursion, with a total potential value of $12 billion. Genentech paid Recursion an upfront payment of $150 million to initiate the development of 40 projects. In early 2022, Exscientia established a collaboration with Sanofi, covering up to 15 novel small-molecule drug candidates in the fields of oncology and immunology, with a total potential value of approximately $5.2 billion.

Insilico Medicine is a clinical-stage biotechnology company driven by generative artificial intelligence, utilizing AI systems to connect biology, chemistry, and clinical trial data analysis. Since 2021, with the support of its proprietary AI platform Pharma.AI, Insilico Medicine has built a robust portfolio of over 30 self-developed pipelines and nominated 20 preclinical candidates, with 10 compounds receiving clinical trial authorization.

XtalPi is a technology innovation company driven by AI and quantum computing. Its AI-related businesses mainly focus on drug discovery and materials science, making it a leading AI pharmaceutical company in China. Its drug discovery business focuses on both small-molecule and large-molecule drugs, with core platforms including the ID4Inno™ drug discovery system and XupremAb.^®Antibody Discovery Platform.

The world's first FDA-approved oral solid COVID-19 drug, PAXLOVID, was developed by Pfizer, with key collaboration from XtalPi, significantly shortening the R&D time and confirming the optimal crystal form of the drug candidate in just six weeks. Additionally, XtalPi signed an AI small molecule drug discovery collaboration with Eli Lilly, under which XtalPi will use its proprietary small molecule drug discovery platform ID4Inno™ to develop first-in-class drugs, with upfront payments and milestone-based earnings potentially reaching $250 million.

Deep Potential Technology, relying on its deep cultivation in interdisciplinary fields, has built the "Deep Potential·Yuzhi" AI for Science large model system, bringing research methods from many disciplines from the "experimental trial-and-error/computer" era into the "pre-trained model era". Deep Potential Technology's RiDYMO^®The drug discovery platform integrates various AI and physical model algorithms, focusing on the development of drugs for "difficult-to-drug" targets and "Best-in-Class" molecules, which has contributed to the successful discovery of the orally available, highly selective small molecule inhibitor DPT0218.

In summary, these drugs that have successfully been marketed or entered the trial stage, whether in the early target discovery, molecular design, or in the subsequent clinical trials, AI technology has played a crucial role. By analyzing and mining vast amounts of biomedical data, AI can more accurately predict the efficacy and safety of drugs, optimize the drug development pathway, and improve R&D efficiency.

In the past three years, the financing situation in the AI pharmaceuticals and even the entire biomedicine field has been like a roller coaster. Due to its combination of computational and biopharmaceutical attributes, AI pharmaceuticals were highly sought after by cross-industry capital during the pandemic. In 2023, the financing enthusiasm for the AI pharmaceuticals sector continued to rise. According to data from market research institutions, the total global financing in the AI pharmaceuticals field exceeded 3 billion US dollars in just the first half of the year, demonstrating strong capital confidence in this sector.

In 2024, most leading AI pharmaceutical companies have raised over 100 million US dollars in funding. Among them, the company co-founded by Nobel laureate Professor David BakerXaira Therapeutics Tops the List with $1 Billion.Ranking second isBioAge Labs, Focusing on "AI + Aging", Completes Series D Financing and IPO, with Cumulative Funding Exceeding $400 Million.Focused on the development of AI drug platformsFormation Bio ranked third with a $372 million Series D financing round.

In 2023,Recursion's Single Round of Financing Reaches $270 MillionNVIDIA, Microsoft and other tech giants are accelerating cross-border expansion. Recursion is using the funds to expand its AI-driven drug discovery platform and advance multiple clinical projects. In the same year, Recursion also acquired two AI drug discovery companies (Cyclica and Valence Discovery), further enhancing capabilities in digital chemistry, machine learning, and generative AI. Recursion's AI platform discovers new indications for existing drugs by analyzing vast amounts of biomedical data, and its technology has gained favor from several pharmaceutical giants.

Turning our attention to China, in April 2024,XtalPi Announces Completion of $150 Million Series E FinancingLed by Sequoia Capital China, the company will expand its AI + quantum computing technology platform and accelerate its layout in the global market. XtalPi's technology platform can accurately predict the physicochemical properties of drug molecules through quantum physics simulations and AI algorithms, thereby speeding up the drug discovery process.

The official website of Insilico Medicine shows,Insilico Medicine has raised over 500 million US dollars.The investors include: Prosperity7, B Capital Group, BHR Partners, Qiming Venture Partners, Deerfield, Pavilion Capital, BOLD Capital, Lilly Asia Ventures, Lake Bleu Capital, Sequoia Capital China, and Sage Partners, among others. Recently, on January 6 this year, Insilico Medicine announced that it had received a joint E-round financing from Shanghai and Hong Kong, with a total scale exceeding 100 million US dollars.

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