Korea Healthcare AI Innovation Fund 2026
Korea's Healthcare AI Innovation Fund supports hospitals, medical device companies, and healthtech startups in developing AI-powered diagnostic tools, treatment planning systems, and patient care solutions. This specialized program provides substantial R&D funding to advance Korea's position in medical AI innovation while ensuring patient safety and regulatory compliance.
- Korean hospitals and academic medical centers
- Medical device manufacturers with Korean R&D operations
- Pharmaceutical companies (Korean or with Korea operations)
- Healthtech startups with Korean registration
- University medical schools and research institutes
- Access to medical data with proper ethics approvals
- Clinical validation partnerships with hospitals secured or planned
- Regulatory expertise or consultants for MFDS approval pathway
- AI/ML technical team with healthcare experience
- Patient safety protocols and data privacy compliance (PIPA)
- Identify clinical problem and unmet medical need with quantified impact
- Design AI solution with explainability for clinicians and EMR integration plan
- Secure hospital partnership agreements for clinical validation
- Obtain IRB (Institutional Review Board) ethics approval or submit application
- Develop MFDS regulatory strategy document with device classification
- Prepare clinical validation protocol with study design and endpoints
- Create data governance plan compliant with PIPA privacy regulations
- Write comprehensive technical proposal (30-50 pages) with multi-year budget
- Assemble team CVs (clinical investigators + AI engineers)
- Submit application by April deadline
- Participate in technical and clinical review presentations (May-June)
- If approved, negotiate contract and begin project in October
Overview
Korea's Healthcare AI Innovation Fund, administered by KIAT in partnership with the Ministry of Health and Welfare, provides comprehensive funding for medical artificial intelligence research and development. With grants up to ₩600 million and subsidy rates of 50-70%, this program enables hospitals, medical device manufacturers, pharmaceutical companies, and healthtech startups to develop AI solutions that improve diagnostic accuracy, optimize treatment planning, enhance patient outcomes, and reduce healthcare costs.
Eligible Healthcare AI Applications
Medical Imaging & Diagnostics
- AI-powered radiology analysis (X-ray, CT, MRI, ultrasound)
- Pathology slide analysis and cancer detection
- Retinal imaging for disease screening
- Dental imaging and diagnosis
- Dermatology image analysis
Clinical Decision Support
- Treatment recommendation systems
- Drug interaction and adverse event prediction
- Patient risk stratification
- Sepsis prediction and early warning systems
- Personalized medicine protocols
Disease Detection & Screening
- Cancer screening and early detection
- Cardiovascular disease prediction
- Diabetes complication prediction
- Rare disease identification
- Mental health assessment tools
Hospital Operations & Workflow
- Patient flow optimization
- Emergency department triage
- Bed management and capacity planning
- Clinical documentation automation
- Medication management systems
Drug Discovery & Development
- Molecular design and screening
- Clinical trial patient matching
- Adverse event monitoring
- Drug repurposing identification
- Biomarker discovery
Remote Care & Monitoring
- Telemedicine AI assistants
- Wearable device data analysis
- Home health monitoring systems
- Chronic disease management
- Elderly care and fall detection
Funding Structure
Grant Amounts
- Early Stage (Proof of Concept): ₩200-300 million (2 years)
- Clinical Validation: ₩300-450 million (2-3 years)
- Commercialization: ₩450-600 million (3-4 years)
Subsidy Rates
- Hospitals & Academic Medical Centers: Up to 70%
- Startups & SMEs: Up to 70%
- Large Medical Device Companies: Up to 50%
- Industry-Academia Consortia: Up to 65%
Eligible Costs
- AI/ML development (data scientists, engineers)
- Clinical validation studies
- Medical data acquisition and annotation
- Regulatory consulting (MFDS approval pathway)
- Cloud infrastructure and compute
- Ethics board approvals and compliance
- Patient safety monitoring
- Pilot deployment in hospitals
Application Requirements
Organization Eligibility
Qualified Applicants:
- Korean hospitals and medical centers
- Medical device manufacturers (Korean or with Korean R&D)
- Pharmaceutical companies
- Healthtech startups
- University medical schools and research institutes
Required Capabilities:
- Access to medical data (with proper ethics approval)
- Clinical validation partnerships with hospitals
- Regulatory expertise or consultants (MFDS pathway)
- AI/ML technical team
- Patient safety and data privacy protocols
Technical Proposal Components
-
Clinical Problem & Unmet Need
- Current diagnostic/treatment challenges
- Patient population and impact
- Clinical workflow integration
- Healthcare cost implications
-
AI Solution Design
- Technology approach and algorithms
- Data sources and privacy protections
- Model validation methodology
- Explainability for clinicians
- Integration with hospital EMR/PACS systems
-
Clinical Validation Plan
- Partner hospitals and patient recruitment
- Study design (retrospective vs. prospective)
- Sample size calculations
- Clinical endpoints and success criteria
- Comparison to current standard of care
-
Regulatory Strategy
- MFDS (Ministry of Food & Drug Safety) classification
- Approval pathway timeline
- Clinical trial requirements (if needed)
- Post-market surveillance plan
- International regulatory plans (FDA, CE mark)
-
Commercialization & Impact
- Target Korean and global markets
- Reimbursement strategy (National Health Insurance)
- Pricing and business model
- Clinical and economic value proposition
Application Process
Annual Timeline
- January: Call for proposals
- February-March: Application preparation
- April: Submission deadline
- May-June: Technical and clinical review
- July: Funding decisions
- August-September: Contract negotiation
- October: Project start
Required Documents
- Application form (Korean)
- Technical proposal (30-50 pages)
- Clinical validation protocol
- IRB (Institutional Review Board) approval or application
- Budget breakdown (multi-year)
- Hospital partnership agreements
- MFDS regulatory strategy document
- Team CVs (clinical + technical)
- Data governance and privacy plan
Review Criteria
- Clinical Impact (35%): Patient benefit and unmet need significance
- Technical Excellence (30%): AI approach innovation and feasibility
- Regulatory Feasibility (20%): MFDS pathway clarity and timeline
- Commercialization Potential (15%): Market size and business viability
Success Stories
AI Diabetic Retinopathy Screening
Organization: University hospital + ophthalmology startup consortium Funding: ₩480 million (70% subsidy, 3 years) Outcome: 94% sensitivity for sight-threatening retinopathy detection, deployed in 150 clinics nationwide, reduced specialist referral time from 3 weeks to 24 hours, received MFDS approval and CE mark, now entering US market
Lung Cancer CT Screening AI
Organization: Major hospital network + medical imaging company Funding: ₩550 million (50% subsidy, 4 years) Outcome: Detected 87% of stage 1 lung cancers (vs. 62% radiologist baseline), reduced false positive rate by 35%, published in Radiology journal, integrated into National Cancer Screening Program
ICU Sepsis Prediction System
Organization: Large academic medical center Funding: ₩380 million (70% subsidy, 3 years) Outcome: 6-hour advance warning for sepsis onset with 82% accuracy, reduced ICU mortality by 14%, saved estimated ₩8 billion annually in intensive care costs, licensing to 20+ Korean hospitals
Application Tips
Do's
✅ Partner with respected clinical institutions for validation ✅ Show clear MFDS regulatory pathway (Class I/II/III) ✅ Demonstrate access to high-quality medical data ✅ Include clinician co-investigators (not just AI engineers) ✅ Address AI explainability for clinical trust ✅ Plan for health insurance reimbursement ✅ Show patient safety monitoring protocols
Don'ts
❌ Don't ignore regulatory complexity of medical AI ❌ Don't underestimate clinical validation requirements ❌ Don't skip patient privacy and data protection (PIPA compliance) ❌ Don't overlook hospital IT integration challenges ❌ Don't propose solutions without clear clinical evidence needs
Regulatory Considerations
MFDS (Korea FDA) Classifications
- Class I: Low risk, software-only diagnostic aids
- Class II: Moderate risk, CAD (computer-aided diagnosis) systems
- Class III: High risk, autonomous diagnostic/treatment decisions
Higher classes require clinical trials and more extensive validation.
Data Privacy (PIPA)
- De-identification of patient data required
- Informed consent for data usage
- Secure data storage and transfer
- Data retention and deletion policies
- Audit trails for data access
Contact Information
KIAT Healthcare AI Program
- Website: https://www.kiat.or.kr/eng/
- Email: healthcare-ai@kiat.or.kr
- Phone: +82-2-6009-3200
Ministry of Food & Drug Safety (Regulatory)
- Website: https://www.mfds.go.kr/eng/
- Medical Device Division: +82-43-719-3800
Related Resources
- KHIDI (Korea Health Industry Development Institute): Additional healthcare innovation funding
- Seoul National University Hospital Innovation Center: Clinical trial support
- Korean Society of Medical AI: Professional network
Contact Pertama Partners
Pertama Partners has helped Korean healthtech companies and hospitals secure Healthcare AI Innovation funding. Our services include:
- Grant application strategy and writing
- Clinical validation protocol design
- Hospital partnership facilitation
- MFDS regulatory pathway consulting
- Medical data strategy and privacy compliance
- Health economics analysis
- Reimbursement strategy development
- International expansion planning (FDA, CE mark)
Contact us to discuss your healthcare AI funding needs and maximize your application success.
Frequently Asked Questions
Frequently Asked Questions
Yes, you don't need MFDS approval before applying - but you must have a clear regulatory strategy. Your proposal should identify the device classification (Class I/II/III), outline the approval pathway, and estimate timeline. KIAT funds the development AND regulatory approval process. Many successful applicants are in early R&D stage and use grant funds for clinical validation required for MFDS submission.
Requirements vary by MFDS classification: Class I (software aid) may only need retrospective validation with 100-500 cases. Class II (CAD system) typically requires prospective study with 500-2000 cases. Class III (autonomous diagnosis) requires full clinical trial with 1000+ patients. Budget 30-50% of project costs for clinical validation. Partner with multiple hospitals to recruit sufficient patients.
Foreign companies can participate as consortium members, but lead applicant must be Korean entity. Many international medical AI companies establish Korean subsidiaries or partner with Korean hospitals/universities to access this funding. If you have promising technology, finding a Korean academic medical center as lead applicant is a common successful strategy.
Extremely strict. All projects must comply with Korea's Personal Information Protection Act (PIPA) for medical data. Requirements: (1) IRB approval for data usage, (2) Patient consent (or waiver for retrospective studies), (3) Data de-identification, (4) Secure storage with access controls, (5) Data retention and deletion policies. Include data privacy compliance budget - typically 5-10% of project costs for security infrastructure and audits.
- •AI for Healthcare & Medical Diagnostics
- •Medical Imaging AI & Deep Learning
- •Clinical Decision Support Systems
- •Healthcare Data Privacy & PIPA Compliance
- •AI Model Explainability for Medical Applications
- •Regulatory Affairs for Medical AI (MFDS)
- •Machine Learning for Drug Discovery
- •Natural Language Processing for Clinical Notes
- •Biostatistics for Clinical Validation
- •Health Economics & Outcomes Research
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