Market Context — Why This Technology, Why Now

The accelerating shift towards remote patient monitoring and digital health solutions is transforming maternal care, driven by demands for greater accessibility, convenience, and cost efficiency. Regulatory bodies are increasingly supporting telehealth, while competitive pressures push providers to offer advanced, data-driven preventive tools. This technology aligns perfectly with these trends, enabling proactive management of high-risk pregnancies, reducing hospital visits, and enhancing patient engagement, positioning it as a key innovation in the evolving global health market.

Key Competitive Advantages
01

Achieves high-accuracy prediction of preeclampsia risk from daily home blood pressure data, comparable to traditional hospital tests, significantly reducing hospital visit burden.

02

Enables early intervention by analyzing advanced features, such as systolic blood pressure trends and correlations, to detect subtle physiological changes before preeclampsia onset.

03

Secures market superiority with robust patent rights, validated through overcoming 6 prior art documents and 2 office actions, providing a clear competitive differentiator.

Market Opportunity
🏥 Digital Health & Telemedicine Services
$2B–$2.5B globally (AI est.)
There is growing demand for services that allow pregnant women to share home blood pressure data with medical institutions via smartphone apps and cloud integration, enabling remote guidance from specialists.
Telehealth platform providers Digital health app developers Remote patient monitoring solution providers
🤰 Maternal & Child Health Services
$3B–$3.5B globally (AI est.)
Amid declining birth rates, there is increased willingness to invest in medical care per child. Technologies that can detect and mitigate risks like preeclampsia early offer significant value to pregnant women and their families.
Maternal care product manufacturers Pregnancy tracking app companies Women's health clinics
💊 Pharmaceutical & Medical Device Manufacturers
$1B–$1.5B globally (AI est.)
Integrating this technology into home blood pressure monitors and related devices could enhance product value and open new market segments. Collaboration with companies developing preventive or therapeutic drugs is also anticipated.
Home blood pressure monitor OEMs Wearable health device companies Pharmaceutical companies developing preeclampsia treatments
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a robust method, program, and device for predicting preeclampsia onset using specific blood pressure data features, including trends over gestational days and correlation coefficients. Its claims were established through a rigorous examination process, overcoming two office actions and six prior art references, indicating strong validity and low invalidation risk.

Competitive White Space

This patent primarily focuses on predictive algorithms for preeclampsia using blood pressure data. White space exists in integrating these predictions with personalized therapeutic interventions or drug delivery systems, or expanding the predictive model to other pregnancy complications using additional physiological markers beyond blood pressure.

Economic Impact
~$1.0M/year estimated healthcare cost reduction (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Early prevention of severe preeclampsia complications could shorten hospital stays and avoid intensive care. For example, if 20% of 100 severe patients become mild cases, and an average of ~$50,000 (AI est.) in annual medical costs (hospitalization, treatment) is saved per patient, the potential healthcare cost reduction is ~$1.0M/year (AI est.).

Speed to Market
6× faster than in-house development
This technology leverages data from existing home blood pressure monitors and implements a software-based feature calculation and prediction model. It requires no new hardware development, and the algorithm is detailed in the patent specification. This allows adopting companies to significantly reduce basic research and large-scale validation periods, focusing instead on integration into existing systems and application development, potentially accelerating market entry by approximately 2.5 years.
Competitive Positioning

X: Prediction Accuracy & Early Intervention
Y: Ease of Use & Accessibility

Business Models & Applications
🏥 License Provision to Medical Institutions
Offer this prediction program as a SaaS solution to hospitals and clinics, enabling medical professionals to manage patient data and utilize it for risk assessment.
⌚ Integration into Home Medical Devices
Partner with home blood pressure monitor manufacturers and wearable device companies to co-develop and market enhanced products incorporating this technology.
📱 Healthcare App Integration Services
Collaborate with pregnancy and parenting healthcare app providers to offer personalized health advice and risk notification features based on blood pressure data.
Adjacent Application Opportunities
👵 Elderly Care & Monitoring
Cardiovascular Disease Risk Prediction for the Elderly
This technology could predict cardiovascular disease risk, such as heart attacks or strokes, in the elderly from daily blood pressure data, potentially reducing emergency hospitalizations by ~15%. It integrates with home monitoring services to enable proactive preventive care.
🏥 Preventive Medicine
Early Risk Detection for Lifestyle Diseases
The algorithm could be adapted to analyze blood pressure patterns in patients with lifestyle diseases like diabetes, detecting complication risks ~6 months earlier. This could integrate with personal health management apps to guide early intervention.
🏃‍♂️ Sports & Health Management
Early Alert for Condition Abnormalities
This technology could detect early signs of overtraining or poor health in athletes and fitness enthusiasts from daily blood pressure and heart rate data, potentially reducing injury rates by ~10%. It prompts appropriate rest or medical consultation.
Integration Roadmap — Estimated 12-Month Deployment
Phase 1: Requirements & Data Design
Duration: 3 months
Define requirements and design data integration methods with existing systems and home blood pressure monitors. Establish functional requirements for the prediction program and confirm alignment with medical guidelines.
Phase 2: System Development & Validation
Duration: 6 months
Develop the prediction program and build a prototype based on defined requirements. Validate using actual blood pressure data in a controlled environment to optimize prediction accuracy.
Phase 3: Deployment & Optimization
Duration: 3 months
Conduct final adjustments for production deployment to healthcare services. Optimize algorithm and system operations based on post-deployment feedback, aiming for continuous value enhancement.
Technical Feasibility
This technology is a software-centric prediction method that utilizes daily systolic and diastolic blood pressure data measured by pregnant women at home. Based on the patent claims, it is determined that the algorithm for calculating features and making predictions can be easily integrated into existing digital health infrastructure, such as home blood pressure monitors and smartphone apps, minimizing the need for new hardware development.
Success Scenario
Implementing this technology could enable pregnant women to easily receive high-accuracy preeclampsia risk predictions at home. This may allow for appropriate medical intervention before severe complications arise, significantly reducing health risks for both mother and child. Furthermore, healthcare providers could improve screening efficiency, focus limited resources on higher-risk patients, and contribute to overall healthcare cost optimization.
Patent Record
APPLICATION NO.
特願2021-099260
REGISTRATION NO.
7734947
FILING DATE
2021/06/15
GRANT DATE
2025/08/29
EXPIRATION DATE
2041/06/15
PATENT HOLDER
国立大学法人富山大学
Examination History
2021年08月10日
手続補正書（自発・内容）
2024年04月25日
出願審査請求書
2025年02月03日
拒絶理由通知書
2025年03月25日
意見書
2025年03月25日
手続補正書（自発・内容）
2025年06月02日
拒絶理由通知書
2025年06月16日
手続補正書（自発・内容）
2025年06月16日
意見書
2025年08月18日
特許査定