Encode · Screen · Manufacture

The AI-Driven
Full-Stack Drug Delivery Platform

From molecular encoding to continuous-flow manufacturing — the delivery infrastructure powering next-gen biopharma

100K+Candidate Library
30+AI Models
5Major Hospital Validations
$ ΞSyn.deploy --pipeline encode→screen→manufacture
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The Problem

Delivery: The Bottleneck
of Drug Innovation

<1%
Endosomal Escape Efficiency
Key gatekeeper for nucleic acid drug potency — <1% of dose reaches the target
<10%
Oral Absolute Bioavailability
Drugs degrade rapidly in vivo or get cleared by the immune system
3 Barriers
Biological Barriers Are Hard to Cross
Cell membrane · BBB · Endosome — each barrier dramatically reduces effective dose

Drug R&D has made breakthroughs in target discovery, but getting the drug to the target remains the industry's core bottleneck. Delivery capability determines molecular value.

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Market Opportunity

A $100B+ Market
With Multiple High-Growth Segments

$160B+
TAM · Global Advanced Complex Formulations (2030)
CAGR ~8% · Frost & Sullivan
$28-35B
SAM · AI + Microfluidics Addressable Market
Delivery R&D Services · Reachable within 5 years
SegmentCurrent SizeProjected SizeCAGR
Global Drug Delivery Systems$44.2B (2025)$62.9B (2030)7.2%
Oligonucleotide Drugs—$20.6B (2029)29.4%
AI Drug Discovery—$4.8B (2029)29.6%
China Advanced Formulations¥28B (2025)¥50-60B (2030)15-20%
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Our Solution

The SynX Full-Stack Delivery Platform
Four Core Modules

01 GreenMatrix Materials Library
100K+ candidates encoded in machine language · Lipids/polymers/proteins/inorganic nanoparticles · 100+ green microcapsule systems · Queryable · Computable · Combinable
02 OpenGMater Large Model
30+ validated AI models · Multi-agent orchestration · Formulation recommendation + stability prediction + scale-up assessment · Million-level formulation design space · 60% shorter delivery cycles
03 Ultra-High Throughput Microfluidics
μL-level sample consumption · Thousands of parameters scanned daily · In-situ vision with AI · 5 functional modules · Particle size/encapsulation/stability
04 SynShell™ Continuous Flow
Modular continuous manufacturing · LNP/nanoparticles/microcapsules/microspheres · CV<5% · μg→kg seamless scale-up · The critical path from lab to plant
>> GreenMatrix.query({payload:"nucleic_acid"}) → OpenGMater.recommend(top_k:5) → μFluidics.screen(throughput:"1000s/day") → SynShell.manufacture(batch:"kg") // Every project makes the system smarter
Explore the Platform
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Core Moat

The AI × Lab Flywheel
A Moat That Gets Stronger With Every Project

01
AI Design
OpenGMater
Million-formula space
→
02
Microfluidic HT Prep
μL samples
1000s params/day
→
03
In-Situ Detection
AI vision-coupled
Size/encapsulation
→
04
Data Feedback
Auto-feed to AI
Model iteration
Core Moat: With every client project, the platform becomes smarter. This flywheel effect — getting stronger with use — is a systemic advantage that single-point technology companies cannot replicate. Traditional CROs rely on people: senior formulation scientists hand-tuning formulas project by project. ΞSyn uses AI to compute first, microfluidics to validate, and data feedback to train models. The more we do, the faster we get.
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Platform Roadmap

v2.0 Adds 5 Automation Modules
Closing the Full-Stack Loop

&circled1; Formulation Translation Model
μL formulation → L/kg continuous flow parameters
Auto-bridging validation to production
Bridge: Validation → Production
&circled2; Online PAT Closed Loop
Real-time production monitoring · Auto data feedback to AI
Full-chain transparent and controllable
Embedded in production layer
&circled3; Continuous Purification Module
TFF tangential flow filtration · Online dialysis · Continuous lyophilization
True end-to-end production line
Production → Final product
&circled4; Stability Prediction Engine
Accelerated short-term studies → Long-term stability prediction
Prioritize process-stable formulations
Embedded in AI design layer
&circled5; Knowledge Graph
Auto-archive all experiments · Train models on high-value cases
Cross-project knowledge accumulation
Pervasive infrastructure layer
2-3 year build
Covered by Seed round
In Progress
v1.0 Current
AI design + microfluidics
+ continuous flow · Delivered
→
Seed Round
v2.0 Complete
+5 modules · Full-stack automation
Data loop · 2-3 years
→
Post-Series A
v3.0 Platform
Input → Auto-output
Self-evolving knowledge
↓60%
Project Delivery Cycle
↑3×
Success Rate
↓80%
Manual Intervention
↓50%
Cost Per Project
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Platform Coverage

Six Delivery Platforms
Cross-Scale · Cross-Cargo

PlatformRouteCore FormulationTypical Applications
TransdermalSkinNanovesicles/HydrogelsAesthetics · Functional skincare · Local anesthesia
OralGI tractMicrocapsulesGastric acid-resistant · Intestinal targeting · Live biotherapeutic delivery
Local InjectionTissue localGel microspheresIn-situ gelation · Long retention · Arthritis
Tissue EngineeringIn vitro/ImplantGranular hydrogels3D printing · Cell delivery · Organ regeneration
Regenerative MedicineBone/CartilageHydrogels/ExosomesBone repair · Cartilage regeneration · Angiogenesis
IntravenousBlood circulationLiposomes/LNPCardiovascular · Nucleic acid targeting · Tumor targeting

From micron-scale (microcapsules/microspheres) to nano-scale (LNP/liposomes/exosomes), from transdermal to IV — full route coverage. This cross-scale, cross-cargo system-level platform is uniquely positioned in the industry.

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Technology Moat

20 Years of Academic Depth
Decades of Discovery, Now Deploying

21+1
Invention Patents + PCT
Microfluidics · Microcapsules · Continuous Flow · AI
100+
Top Journal Papers
Nat. Commun. · Angew. Chem. · Adv. Mater. · Small
h213 + h108
World-Class Scientific Advisors
Weitz (Harvard · NAS/NAE/AAAS) · Knowles (Cambridge)
¥40M+
Total Research Funding
National Key R&D Programs · NSFC Projects
4 Industries
Cross-Industry Validation
Pharma MediShell™ · Personal Care AromaShell™ · Agrochemical AgriCore™ · Food NutriCaps™
Cross-Industry Validation = Platform Transferability: Covering pharma, personal care, agrochemical, and food. Precision agriculture "self-burst" microcapsule pesticide burst rate >94%, D90≤15μm (fully surpassing BASF's Zorvec); functional skincare oil-concentrate beads already commercialized (comparable to L'Oréal Gold Series) — validated in real industry settings. Four completely different industries, all proven — the platform itself is transferable.
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Validation

5 Major Teaching Hospitals · 5 Therapeutic Scenarios

CaseHospitalPublicationKey Data
Bone RepairNanjing First HospitalSmall, 2024Osteogenic genes↑6.5-14.3× · BMD↑26% · 28-day sustained release
Enteritis TargetingFirst Affiliated Hospital of USTCAdv. Funct. Mater., 2022SGF survival 89.67% · NO-triggered release 67.86%
Myocardial InfarctionNanjing Drum Tower HospitalCEJ, 2026 · JCR, 2024CTP-targeted enrichment · EF/FS significantly improved
Diabetic WoundsZhongshan Hospital, Fudan UniversityAdv. Science, 2025Day 12 wound closure ∼ 90% · Dual mechanism
Transdermal DeliveryThe Sixth Affiliated Hospital of SYSU—Transdermal efficiency↑4× · Bioavailability↑16.6×
>> validation.summary() hospitals: 5, scenarios: 5, papers: 100+, patents: 21+1 >> // Pipeline: Liposome microcapsules · Hair-growth liposomes · Electrosurgery microcapsules
View Case Details
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Competition · 1/2

The Only Full-Stack Closed-Loop Platform
Deep Competitive Analysis Across 20 Players

The delivery space intersects across four dimensions: technology route × delivery modality × AI maturity × commercialization stage. ΞSyn is the only company operating at industrial-grade in both "AI design" and "continuous-flow manufacturing" simultaneously.

CompanyTechValuationAICargosClosed Loop
☆ ΞSynAI Full-Stack¥200M★★★★★6+Full Stack
METiSAI+LNPHKD 18B★★★★2AI Strong
AlnylamGalNAc$35B★1Liver Targeting
ModernamRNA LNP$12B★★★1mRNA Specialist
BioNTechmRNA LNP$18B★★★2Cancer Vaccines
GenerateGenAI Protein$1.5B+★★★★★3AI Strong
ArrowheadTRiM$2.5B★★2Extrahepatic RNAi
BeamBase Editing$1.8B★★3LNP Delivery
Differentiation Formula
ΞSyn = Full-Stack Closed Loop(AI+microfluidics+continuous flow)
× Cross-Scale Cross-Cargo(micron+nano×6 cargos)
Alnylam focuses on liver×siRNA (vertical depth) · METiS excels in AI design, needs manufacturing · Moderna/BioNTech LNP mature, focused on mRNA · CDMOs strong in manufacturing, need AI design. ΞSyn is the only platform covering both dimensions.
→ Next: Competitive Quadrant
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Competition · 2/2

Competitive Quadrant · Delivery Cargo Breadth × Platform Engineering Maturity

X-axis: Single cargo → All cargos · Y-axis: Traditional manual → AI closed-loop continuous manufacturing · Bubble size = valuation/market cap (log scale)

012345 Single CargoDual Cargo Multi-Cargo (3-4)Cross-Category (5+) All Cargos 012345 Traditional ManualBasic Computation AI-Assisted + AutomationAI-Driven + HT Screening AI Closed Loop + Continuous Manufacturing Delivery Cargo Breadth → Platform Engineering Maturity → Alnylam Sarepta Moderna BioNTech Arrowhead Intellia Beam Alkermes Kindeva LTS RiboBio Orna Capricor Neurophth Sirnaomics Generate METiS Luye NanoMed ΞSyn Bio Full-Stack Platform Leader AI Full-Stack AI+LNP mRNA siRNA AAV Exosomes Microspheres Transdermal circRNA
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Business Model

Three Revenue Layers
Same Client · Continuous Monetization

Revenue LayerTriggerBillingGross Margin
&circled1; Upfront CRO Service FeeAt signing · One-timePharma ¥1.5M / Aesthetics ¥600K / 818 ¥400K40-50%
&circled2; Raw Material SupplyAnnual recurring · Scales with clinical stageRevenue × material ratio (5-8%) × stage multiplier60-70%
&circled3; Royalty SharePost-launch · 7-year exclusivityRevenue × 3% (w/ upfront fee) / 8% (no upfront fee · risk sharing)90%+
Short-term 0-3Y
Customer acquisition · CRO service driven
New clients 4→35→90/year
Revenue ¥3.23M→¥64.08M
Y3 breakeven · Net profit ¥11.16M
Team 15→25→40
Mid-term 3-5Y
Material supply scales · Clients enter late-stage trials
Pipeline progression → stage coefficient 0.001→0.1→1.0
Revenue ¥142.76M→¥359.71M (Y5)
Net margin 17%→49% · Team expands to 70→100
Ending cash ¥370M · Self-sustaining
Long-term 5Y+
Royalty stacking · Platform flywheel
Client products launching (7-year exclusivity)
Royalty 3-5% × stacked across pipelines
LTV per pharma client ¥210-260M
CRO fee <1% of LTV
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Financial Projections

5-Year Baseline — From Seed to Profitability

ItemY1Y2Y3Y4Y5
Revenue¥3.23M¥23.68M¥64.08M¥142.76M¥359.71M
Total Operating Costs¥14.90M¥25.95M¥49.20M¥78.50M¥123.00M
Net Profit-¥11.67M-¥2.27M¥11.16M¥48.20M¥177.53M
Net Margin——17%34%49%
Ending Cash¥27.13M¥148.46M¥157.42M¥198.61M¥369.14M
Breakeven
Y3
5-Year Cumulative Revenue
¥593M
Y5 Net Margin
49%
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Team · 1/3

Management Team:
15 Years of Industry Depth × Capital Markets Expertise

Gavin Huang
Founder & CEO
Education: University of Toronto, Biochemistry BSc · UPenn, Biotechnology MSc
Industry Experience: 15 years across the full pharma value chain — Drug discovery → Preclinical → CMC → Clinical → Commercial
Key Roles: WuXi AppTec · Fapon Biotech · Tigermed
Key Achievements: Closed orders >¥1B · Led multiple 0-to-1 commercialization projects
Core Competencies: Industry network · Business negotiation · Full-chain project management · Cross-border BD
Roy Wang
CFO
Education: Sun Yat-sen University, Economics
Investment Experience: IDG Capital, 5 years · Consumer/Healthcare/TMT
Notable Deals: Heytea · Wonderlab · Jiufeng Energy
Key Achievements: As CFO, completed 3 funding rounds totaling ¥400M (biotech company)
Core Competencies: Financial modeling · Fundraising · Post-investment management · Capital markets
Why this combo works: Gavin's 15-year full-chain pharma network (from WuXi to Tigermed, covering drug discovery through commercialization) means a ready-built client acquisition base; Roy Wang's IDG background manages fundraising cadence and investor relations. Both have entrepreneurial experience.
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Team · 2/3

Core Technical Team:
Four Scientists · One Cambridge Connection

Prof. Yu Ziyi
CSO · Chief Scientific Officer
Nanjing Tech University, Professor/PhD Advisor · Deputy Director, State Key Lab of Materials-Oriented Chemical Engineering
Cambridge University, Postdoc · h-index 17 · 66 papers
4 NSFC grants + 2 National Key R&D Programs
Jiangsu Province "333 High-Level Talent Project"
Key Contribution: GreenMatrix materials library architecture · 100+ green microcapsule systems
Assoc. Prof. Zhang Jing
CTO · Chief Technology Officer
Nanjing Tech University, Associate Professor
Cambridge University + UCD Postdoc
h-index 27 · 60+ papers · 1,700+ citations
Nanoparticle drug delivery · Cancer nanotheranostics
Key Contribution: Ultra-high-throughput microfluidic system design · OpenGMater model framework
Dr. Hu Chi
Formulation Scientist
China Pharmaceutical University, Research Group Lead
Cambridge University, PhD · 50+ papers · 4 patents
High-impact journal publications
Key Contribution: Formulation development
Dr. Yang Zhaoxiang
Carrier Scientist
Renmin University, PhD · Cambridge University, Postdoc
h-index 18 · 40 papers · 5 patent applications
Nature Communications (2026) · Advanced Materials (2023)
Key Contribution: γ-PGA microcapsule system · NO-responsive release system
Cambridge Connection · Proven Collaboration: Yu, Zhang, Hu, and Yang — four core scientists all with Cambridge experience, forming natural academic synergy. Three have co-authored Angewandte Chemie (2025) — the team has long-term collaboration with proven output. The intersection density of microfluidics and delivery is unmatched among Seed Round companies.
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Team · 3/3

Scientific Advisory Board

David A. Weitz, Academician
Harvard University · Microfluidics Pioneer
Academic Standing: Triple US National Academy Member (NAS/NAE/AAAS) · Foreign Member, Chinese Academy of Engineering
h-index: 213 — Among the highest globally in microfluidics
Industry: Founded RainDance (acquired by Bio-Rad) · GnuBIO · HiFiBiO and 10+ biotech companies
Value to ΞSyn: Directly empowering ultra-high-throughput microfluidic platform design · World-class academic credibility · Industry network
Prof. Tuomas Knowles
University of Cambridge, Cavendish Laboratory
Academic Standing: Professor, Department of Chemistry & Cavendish Laboratory, Cambridge
h-index: 108 · 450+ papers · 40,000+ citations
Industry: Transition Bio Co-founder & CTO ($50M Series A in 2022) · 4-5 companies total
Value to ΞSyn: Theoretical authority on protein/macromolecule delivery · Cambridge network · 2019 Academic Entrepreneur of the Year
Team Structure — "Sky, Bridge, Ground"
Sky: Weitz (h213, Harvard Tri-Academy) + Knowles (h108, Cambridge) — World-class academic authorities who defined the field of microfluidics and delivery
Ground: Gavin (15-year pharma chain) + Roy Wang (IDG Capital) — Industry execution, turning technology into business
Bridge: Yu, Zhang, Hu, Yang — Four Cambridge-trained scientists translating academic breakthroughs into deliverable products
Three-tier talent structure — Academician advisors, Cambridge-trained scientists, industry veterans — unique at the Seed Round stage.
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Funding

Seed Round · ¥40M

¥200M
Post-Money · 20% dilution
25 months
Runway · Fully funded
Use%Amount
Lab + Equipment25%¥10M
R&D + Pipeline30%¥12M
Team Compensation15%¥6M
BD + Business Development10%¥4M
Operations + Compliance8%¥3.2M
Working Capital12%¥4.8M
Valuation Benchmark & Exit Path
Direct Benchmark: METiS angel round valued at ~¥300-500M → HKEX IPO in 5 years, market cap HKD 18B (36-60× angel return)
RoundTimingAmountValuation
SeedM0¥40M¥200M post
Series AM24-30¥100-150M¥600M-1B pre
ExitM72-96IPO/M&AHKEX Chapter 18C
The platform model stacks multiple out-licensing pipelines — any single pipeline success can deliver outsized returns to investors.
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Investment Highlights

The AI-Driven
Delivery Infrastructure

AI design → Microfluidic HT screening → Continuous-flow manufacturing — the integrated closed-loop, system-level delivery platform
Scientific Advisors: Academician Weitz (h213) + Prof. Knowles (h108)
Seed ¥200M vs METiS angel ¥300-500M → 5Y HKD 18B — 30-60× return range
Cross-Industry Validation: Agriculture (surpassing BASF) + Skincare (comparable to L'Oréal) — platform transferability
ΞSyn.invest(round: "angel", amount: "¥40M", valuation: "¥200M") → // [email protected]
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