Insilico Medicine Cayman Topco · HKEX:3696
Insilico Medicine Cayman Topco — Investor Presentation (March 2026)
28 slides from Insilico Medicine Cayman Topco's investor presentation, March 2026
Slide 1: Company Presentation
Company Presentation March 2026
Slide 2: Disclaimer
Disclaimer THIS DOCUMENT OR THE INFORMATION CONTAINED HEREIN IS NOT INTENDED TO AND DOES NOT CONSTITUTE ANY OFFER OR INVITATION, SOLICITATION, COMMITMENT OR ADVERTISEMENT OF ANY OFFER FOR SUBSCRIPTION, PURHCASE OR SALE OF ANY SECURITIES, NOR SHALL ANY PART OF THIS DOCUMENT FORM THE BASIS OF OR BE RE
Slide 3: Table of Contents
Table of Contents 1 Overview 2 AI Platform 3 Asset Pipeline 4 Business Model 5 Financials 4
Slide 4: Overview
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Slide 5: A Leading and Global AI-driven Biotech Company Established in 2014
A Leading and Global AI-driven Biotech Company Established in 2014 To accelerate drug discovery and development by leveraging our rapidly evolving, proprietary Pharma.AI platform Revenue VALUES $85.8M +68% PATIENT FIRST Montreal +70% Boston $51.2M Yixing RELENTLESS INNOVATION New York Shanghai Taipe
Slide 6: AI Platform
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Slide 7: World's Leading Generative AI-powered Drug Discovery and Development Platform
World’s Leading Generative AI-powered Drug Discovery and Development Platform with End-to-end Capabilities Biology42 Chemistry42 Medicine42 PandaOmics Generative Chemistry inClinico Discover and Prioritize Novel Targets Generate Novel Molecules Design and Predict Clinical Trials Alchemistry Generati
Slide 8: Insilico Generative AI for Drug Discovery Process: Code to Cure
Insilico Generative AI for Drug Discovery Process: Code to Cure Disease Lead IND-enabling Submission Hypothesis Target-to-Hit Hit-to-Lead PCC Phase Ⅰ Phase Ⅱ Phase Ⅲ Optimization Studies to Launch and Target ID Generative Biologics Generative Chemistry Precious3GPT Nach01 Precious3GPT Retrosynthesis
Slide 9: Differentiated Generative AI Platform Empowered by AI + Scientists
Differentiated Generative AI Platform Empowered by AI + Scientists Full Integration of Pharma.AI and Our Biology Teams Allowing for Real-time Feedback to Enhance Platform’s Capability AI-powered Drug Discovery AI Scientists Traditional Drug Discovery ✓ Customized generation of millions of hit ✓ Disc
Slide 10: Unique Dual CEO Structure Combining Technological Innovation and R&D Execution
Unique Dual CEO Structure Combining Technological Innovation and R&D Execution High Performance Computing Biology AI Engines • Novel target ID + Drug Discovery • Novel molecules Team • Synthetic route plan Medicinal Chemistry Generative Biology AI • Clinical trial outcomes Pre-clinical Research Gene
Slide 11: Asset Pipeline
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Slide 12: ~30 Asset Pipeline Discovered from Our Generative AI Platform
~30 Asset Pipeline Discovered from Our Generative AI Platform with Leading Asset Most Advanced Globally among Peer Companies Development Therapeutic Pipeline Strategy Stage of Development Target Target- IND- Target Indication Identification to-hit Hit-to-lead Lead Optimization enabling Phase 1 Phase
Slide 13: 200+ Peer-reviewed Publications & 600+ Patents
200+ Peer-reviewed Publications & 600+ Patents Advisory Board of Biologists, Chemist and Drug Hunters Charles Cantor, PhD Michael Levitt, PhD Klaus Witte, PhD Stevan W Djuric, PhD Donald Small, MD, PhD Co-founder of Sequenom, Professor, Stanford University Co-founder of Sequenom, Adjunct Professor D
Slide 14: Traditional Drug R&D Takes >10 Years and >$2B
Traditional Drug R&D Takes >10 Years and >$2B* From the discovery to the launch of a new drug Disease Hypothesis and Target Discovery** Lead Submission Sales and Real world Target-to-hit Hit-to-lead Preclinical Phase I Phase II Phase III optimization to launch marketing evidence Usually takes from m
Slide 15: AI-based Drug R&D is Cheaper, Faster, and has Higher Success Rate
AI-based Drug R&D is Cheaper, Faster, and has Higher Success Rate than Traditional R&D Cheaper Faster Higher Success Rate AI Application in Drug R&D Cost in Preclinical Months from Target Discovery to Molecule Synthesized Candidate Selected Preclinical Candidate Nomination to Identify Preclinical Ca
Slide 16: Pharma.AI Catalyzed Drug Discovery Breakthroughs from 2021-2025
Pharma.AI Catalyzed Drug Discovery Breakthroughs from 2021-2025 28Total Developmental Candidates (DC) 2021: 2022: 2023: 2024: 2025: 2 DC 9 DC 6 DC 5 DC 5 DC 12 Molecules Received IND Clearance Completed Phase IIa in IPF Completed Two Phase I in IBD Shortest Time To DC: Average Time To DC: Longest Ti
Slide 17: Case Study: ISM001_055 (TNIK Inhibitor) is the Most Clinically Advanced AIDD Candidate
Case Study: ISM001_055 (TNIK Inhibitor) is the Most Clinically Advanced AIDD Candidate Globally Submission to launch Phase III Disease Phase 0 & Lead Candidate Hypothesis and Target-to-hit Hit-to-lead IND-enabling Phase I Phase II Optimization Validation Target ID studies 2019 2020 2021 2022 2023 20
Slide 18: High Unmet Medical Needs in IPF with Limited Treatment Options
High Unmet Medical Needs in IPF with Limited Treatment Options Market Opportunity Competitive Landscape Fibrosis is a pathological feature of many chronic inflammatory diseases Approved Drugs that refers to the scarring and hardening of tissues and organs Original Drug FDA Approved Original Drug Gen
Slide 19: ISM001-055: Target Identified and Molecule Created by our Generative AI Platform
ISM001-055: Target Identified and Molecule Created by our Generative AI Platform INS018_055 (ISM001-055): Small-molecule drug candidate designed by our generative AI platform to treat fibrosis-related indications by inhibiting the TRAF2- and NCK-interacting kinase (TNIK) Indications ISM001_055 Inhal
Slide 20: ISM001-055 Out-performs Other Investigational Agents in Cross Trial Data Comparison
ISM001-055 Out-performs Other Investigational Agents in Cross Trial Data Comparison Mean FVC αvβ6 /αvβ1 Hedgehog Nerandomilast Pirfenidone Nintedanib change TNIK from baseline (discontinued) inhibitor (approved) (approved) (approved) (ml)(1) 98.4ml 100 60.0ml 29.5ml 0 (46.8ml) (62.3ml) (100) (95.0ml
Slide 21: Life Star 2: AI-Driven Automated Laboratory Accelerates Drug Discovery
Life Star 2: AI-Driven Automated Laboratory Accelerates Drug Discovery and Development Target discovery and target Drug development and Algorithm verification verification translational medicine AI modules Automation module ✓ Sample self-registration ✓ Compound management platform ✓ Cell culture pla
Slide 22: Towards Chemical and Biological Superintelligence: MMAI Gym for Science
Towards Chemical and Biological Superintelligence: Insilico Medicine’s MMAI Gym for Science After MMAI Gym training, LLMs can achieve up to 10-fold performance gains on key drug discovery benchmarks, compared to their baseline performance where they fail on approximately 75–95% of tasks. LLMs traine
Slide 23: Business Model
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Slide 24: Multi-Pronged Revenue Generating Business Model for Long-term Growth
Multi-Pronged Revenue Generating Business Model for Long-term Growth Drug Discovery and Pipeline Development Software Solutions Other Discovery Related to Non-pharma Sectors • Generated >20 clinical or IND-enabling stage assets • Utilize Pharma.AI to discover novel molecules for specific topics rela
Slide 25: Multiple Collaboration and Out-Licensing Agreements with Leading Pharmaceutical and Biotech Companies
Multiple Collaboration and Out-Licensing Agreements with Leading Pharmaceutical and Biotech Companies since 2021 2021 2022 2023 2023 2024 QPCTL Co-development Up to 2 + 4 USP1 KAT6 KIF18A & 4 Collaboration Targets Collaboration Targets Out-licensing Out-licensing Out-licensing Upfront of $13 million
Slide 26: Financials
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Slide 27: Financial Highlights
Financial Highlights Revenue (USD MM) Gross Profit (USD MM) Expenses (USD MM) 85.8 2.1 63.4% 75.4% 90.4% 4.0 77.6 122.5 114.9 51.2 99.0 17.3 17.5 3.4 15.4 79.7 38.6 30.1 1.5 97.3 91.9 47.8 19.1 78.2 28.6 5.4 7.8 5.5 1 2022 2023 2024 2022 2023 2024 2022 2023 2024 Drug Discovery and Pipeline Developme
Slide 28: Largest Pipeline and is the Most Innovative among AIDD Companies
Largest Pipeline and is the Most Innovative among AIDD Companies Recursion Number of AI Novel ：Non-novel Company Discovered Target in LSD1 PI3Kα ENPP1 Target Proprietary Pipeline Insilico Relay Therapeutics Insilico Medicine 28 3:25 Medicine MALT1 ENPP1 Pan-KRAS GIPR Relay 5 0:5 NRAS MEK Therapeutic
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