In-Depth Analysis Report on Sanofi's Increased Investment in AI Drug Discovery

Now I will provide you with a professional and comprehensive analysis report, offering an in-depth interpretation of this event based on collected data:

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[1][2]:

• Sanofi paid an
  upfront payment of $125 million
• Secured global exclusive rights to two bispecific antibodies developed by Earendil Labs
• Total deal value of
  $1.8 billion
• Targets: α4β7 integrin/TL1A (ulcerative colitis, Crohn’s disease), TL1A/IL-23 (colitis, skin inflammation)

[1][2]:

• Earendil Labs received an
  upfront payment of $160 million plus recent milestone payments
• The two parties will co-develop next-generation bispecific antibody therapies for multiple autoimmune and inflammatory diseases
• Total deal value reaches $2.56 billion
  (equivalent to approximately NT$82 billion)
• Earendil Labs is also entitled to
  low double-digit percentage
  royalty payments based on net product sales

This collaboration adopts the

[1]:

• Earendil Labs
  : Utilizes generative protein engineering and machine learning platforms to screen and optimize bispecific antibody drug candidates
• Sanofi
  : Responsible for subsequent clinical development, regulatory applications, and global commercialization

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Earendil Labs is an AI-driven biotech company[2]:

• Core Business
  : Develop next-generation innovative biologics for the treatment of autoimmune diseases, cancer, and other diseases with unmet medical needs
• Technology Platform
  : Integrates advanced machine learning, generative protein engineering, and high-throughput experimental technologies
• Affiliated Enterprise
  : Affiliated with Helixon Therapeutics (华深智药)

Earendil Labs has a proprietary integrated framework that enables[2]:

• Accurate optimization of the functionality, manufacturability, and developability of protein-based biologics
• Development of drugs with
  first-in-class
  and
  best-in-class
  potential

Dimension	Analysis
Technology Scarcity	Generative protein engineering is a cutting-edge technology with high barriers to entry
Pipeline Quality	HXN-1002 and HXN-1003 target unmet medical needs in the autoimmune field
Validation Value	Two collaborations within 8 months indicate recognition of preliminary results
Synergistic Effect	Synergy with Helixon Therapeutics enhances overall R&D capabilities

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According to the latest data[3][4]:

• Financing Scale
  : In 2024, there were 128 global financing events related to AI + drug R&D, with a total amount of
  $5.795 billion
  (equivalent to approximately RMB 41.64 billion), a year-on-year increase of
  61%
• Penetration Rate
  : 48% of enterprises have adopted AI for drug discovery
• Efficiency Improvement
  : Shortens preclinical R&D cycle from 5 years to 2 years, reduces costs by
  30%

• Number of Enterprises
  : China has the second-largest number of AI drug discovery companies in the world[3]
• Financing Growth
  : In 2024, financing for domestic AI drug discovery companies reached
  RMB 8.5 billion
  , a year-on-year increase of
  62%
  [3]
• Industry Scale
  : The scale of Shanghai’s biopharmaceutical industry grew from RMB 761.7 billion in 2021 to RMB 984.7 billion in 2024, with a compound annual growth rate of
  8.94%
  , and is expected to exceed the RMB 1 trillion mark in 2025[5]

According to industry research[3][4]:

Application Scenario	Technological Value	Implementation Progress
Drug Discovery	Big data analysis, molecular modeling, candidate molecule screening	Mature application, adopted by 48% of companies
Protein Structure Prediction	Tools like AlphaFold have revolutionized underlying technologies	Recognized by the Nobel Prize
Clinical Trial Design	AI-assisted patient screening, data analysis	Rapid development
Medical Imaging Diagnosis	Efficiency improvement, increased penetration rate	Relatively mature commercialization

According to ARK’s Big Ideas 2025 report[3]:

• AI will reduce drug development costs by 4x and increase R&D investment returns by
  5x
• AI will increase cancer screening efficiency by
  20x
  and expand the market size by
  10x
• The commercial value of AI-developed drugs will be
  20x higher
  than standard drugs and
  2.4x higher
  than best-in-class precision drugs

The current AI + life sciences industry presents a

[3]:

    ┌─────────────────────────────────────┐
    │   Top Pharma Companies: End-to-End AI Platform Optimization        │
    │   (MNCs like Sanofi, Pfizer, etc.)             │
    ├─────────────────────────────────────┤
    │   Mid-Sized Enterprises: Focus on Specific Segments            │
    │   (e.g., AI-assisted clinical trial design)            │
    ├─────────────────────────────────────┤
    │   Small and Medium Enterprises: Cloud Services Lower Technical Barriers      │
    │   (e.g., XtalPi, Insilico Medicine, etc.)            │
    └─────────────────────────────────────┘

• Business Model
  : “AI + CRO” model, provides R&D services instead of developing drugs independently
• Performance
  : H1 2025 revenue reached
  RMB 517 million
  , a year-on-year increase of
  403.8%
  ; achieved first-half profitability for the first time, with adjusted net profit of
  RMB 142 million
  [6]
• Major Collaboration
  : Entered into a
  $5.99 billion
  major collaboration with DoveTree in August 2025[4]

• Milestone
  : Listed on December 30, 2025, raising
  HK$2.277 billion
  , becoming the largest biopharmaceutical IPO on the Hong Kong Stock Exchange in 2025[5]
• Core Product
  : ISM001-055 —— the world’s first innovative drug fully developed by AI from target discovery to molecular design
• R&D Efficiency
  : Only 12-18 months from project initiation to preclinical candidate nomination, with only 60-200 molecules synthesized and tested[5]
• Valuation
  : Exceeds
  $1.3 billion
  [6]

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Factor	Analysis
Policy Support	“AI + Biomedicine” special initiatives drive technology implementation
Capital Favor	The AI drug discovery sector has a price-to-earnings ratio of 149.1x, far exceeding the industry benchmark[6]
Technological Maturity	Adopted by 48% of companies, with significant efficiency improvements
Industry Synergy	Collaborations between MNCs (multinational pharmaceutical companies) and AI companies are deepening
China’s Advantages	Abundant clinical data resources and policy support

According to industry forecasts[3][4]:

• The AI drug discovery market is in a period of explosive growth
• By 2030, AI is expected to completely transform multi-omics tools, drug R&D, and molecular diagnostics
• Healthcare will become the most far-reaching application field for AI

Risk Type	Details
Commercialization Validation	There are still few cases of AI-discovered drugs entering late-stage clinical trials (only about 10 candidates have entered Phase II globally)[6]
Regulatory Challenges	The FDA and NMPA have strict requirements for new drug approval, and AI-developed drugs face additional scrutiny
Data Dependency	AI models rely on high-quality data; small and medium-sized enterprises often face low model accuracy due to insufficient data volume
Profit Uncertainty	Most AI drug discovery companies are still unprofitable, and their commercialization models await validation
Intensified Competition	As technology becomes more widespread, industry consolidation may occur

• Revolutionary tools like AlphaFold are facing
  shortages of drug-related data
  [6]
• AI technology can significantly improve the efficiency of early-stage drug R&D, but whether it can increase
  clinical trial success rates
  still requires more data support

Current valuation characteristics of the AI drug discovery sector[6]:

• AI Drug Discovery Sector
  : Average price-to-earnings ratio of
  149.1x
• AI-Assisted Diagnosis Sector
  : Average price-to-earnings ratio of
  127.7x
• Both
  far exceed the overall level of the biopharmaceutical industry

This high valuation trend is mutually confirmed by active investment activities in the primary market, forming a positive feedback loop, but there is also a risk of valuation bubbles.

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Sanofi’s strategic intentions can be seen from this collaboration[1][2]:

1. Seize Leadership in Immunology
   • Autoimmune diseases impose a heavy burden on patients and healthcare systems
   • Many patients require lifelong treatment, and their response to existing therapies often falls short of expectations

2. Technological Positioning
   • Acquire generative protein engineering capabilities through collaboration with Earendil Labs
   • Reserve core technologies for future autoimmune drug pipelines

3. Diversify R&D Risks
   • Adopts the “upfront payment + milestone payments” model
   • Transfers early-stage R&D risks to AI companies while retaining late-stage commercialization rights

Sanofi is not an isolated case; multinational pharmaceutical companies are accelerating their布局 in AI drug discovery:

Enterprise	Collaboration/Layout
Sanofi	Invested in Earendil Labs twice within 8 months, with total upfront payments exceeding $280 million
AstraZeneca	Entered into a $5.33 billion AI drug collaboration with CSPC Pharmaceutical Group[4]
Pfizer, Eli Lilly	Established collaborations with companies like Jingtai Technology, Exscientia
Novartis	Entered into a long-term collaboration with Schrödinger

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1. Sanofi’s increased investment in Earendil Labs
   reflects multinational pharmaceutical companies’ high recognition of AI drug discovery technology and validates the value of Earendil’s technology platform

2. The implementation prospects of AI applications in biomedicine are broad
   :
   • Technology has moved from concept to reality
   • Significant efficiency improvements (60% reduction in R&D cycle, 30% reduction in costs)
   • Highly favored by the capital market, with continuous growth in financing scale

3. The industry is in a transition phase from “technology story” to “performance delivery”
   :
   • Some AI-designed drugs have already entered clinical trials
   • But late-stage clinical validation and commercialization still require time
   • A key validation period is expected in the next 1-2 years

Focus Area	Specific Targets
AI + CRO Leaders	XtalPi (profitable, mature business model)
AI + Biotech	Insilico Medicine (leading pipeline progress)
Technology Platform Companies	DeepKin (AI for Science underlying algorithms)
Industry Integration	WuXi AppTec, Fosun Pharma (industrial capital layout)

• Short-Term (1-2 Years)
  : As more clinical data is released, the market will verify whether AI drug discovery can truly become the “second growth curve” for biopharmaceutical innovation
• Mid-Term (3-5 Years)
  : It is expected that more AI-discovered drug candidates will enter late-stage clinical trials or even receive approval for marketing
• Long-Term (5-10 Years)
  : AI will completely transform the drug R&D paradigm and become the most far-reaching AI application scenario in the healthcare field

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[1] GeneOnline News - Sanofi Invests Heavily in AI Drug R&D, Signs Multi-Billion-Dollar Autoimmune Drug Development Agreement with Earendil Labs (https://geneonline.news/sanofi-earendil-labs-autoimmune-drug-partnership/)

[2] Sina Finance - $2.56 Billion! Sanofi Reaches Another Collaboration with Helixon Therapeutics (https://finance.sina.com.cn/roll/2026-01-06/doc-inhfiver1408709.shtml)

[3] Medical Biotech Industry Report (2025.02.05-2025.02.07) - US Stock “AI + Healthcare” Sector Surges (https://pdf.dfcfw.com/pdf/H3_AP202502101642933919_1.pdf)

[4] OFweek - Top 10 Overseas Expansion Cases of Chinese Innovative Drugs in 2025 (https://mp.ofweek.com/biotech/a556714630607)

[5] Shanghai Observer - AI Drug Discovery Company Insilico Medicine Lists, Shanghai Accelerates Towards Trillion-Yuan Biopharmaceutical Industry High Ground (https://www.jfdaily.com/news/detail?id=1044251)

[6] 21st Century Business Herald - Insilico Medicine Surges 45% on Debut! Why the “First AI Drug Discovery Stock” Ignited the Hong Kong Stock Market (https://www.21jingji.com/article/20251230/herald/e67cd05b81fc1c0907ea268d2ad8846e.html)

[7] Chinaventure - AI Drug Discovery Company with $9 Billion Valuation Files for Hong Kong IPO Third Time (https://m.chinaventure.com.cn/news/111-20251114-388872.html)

[8] CSDN - 2025 Life Sciences and Biopharmaceutical Panorama Report: Industry Map, Investment Directions and Strategic Insights (https://blog.csdn.net/qq_19600291/article/details/149903907)

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: This report is for reference only and does not constitute investment advice. Investment involves risks; please invest cautiously.