This invention improves blood clotting diagnostics by using a tiny blood sample on a special glass slide with color markers and AI imaging analysis. It observes platelets in near-real conditions instead of suspending blood in a solution. An advanced imaging system tracks how platelets change and clot over time, and AI algorithms predict bleeding or clotting risks. The system produces results quickly (15–50 minutes) and can work with just a few microliters of blood. This makes it practical for use with children or vulnerable patients who cannot give large samples. The main users would be hospitals, labs, and doctors who monitor patients with clotting disorders, who need precise, real-time information for surgeries or treatments. The benefits are fast, accurate assessment of clotting risk, enabling more personalized treatment decisions (for example in trauma care, surgeries, or conditions like thrombosis, preeclampsia, or COVID-related coagulopathy). Overall, it offers greater precision and safety in blood diagnostics, potentially making procedures safer and improving patient outcomes.
Problem
Existing blood clotting tests (such as TEG and ROTEM) rely on large blood samples and non-physiological conditions, making them unreliable for real-world predictions of bleeding or clotting risk. This creates a diagnostic gap, especially for critical surgeries or treatment decisions where accurate assessment of clotting tendency is vital.
Target Customers
Not explicitly specified. Likely customers include hospitals and clinical labs performing surgeries or treating clotting disorders. This could include cardiac surgery centers, trauma units, pediatric hospitals, and maternal-fetal medicine clinics, as well as medical device manufacturers serving those markets.
Existing Solutions
Currently, the problem is addressed with viscoelastic tests like TEG and ROTEM and conventional coagulation labs (e.g., PT/PTT tests). These require larger blood samples and operate under artificial conditions, so they may miss important physiological platelet behavior. The patent implies that prior methods are less accurate or slower, but it does not detail specific competing products or techniques.
Market Context
As a medical diagnostic tool, this invention fits into blood testing and point-of-care diagnostics. It targets a healthcare niche involving bleeding and thrombotic risks, which is significant for surgeries and critical care. The application is broad across health systems (potentially global), but the specific market size and demand are not provided. Adoption may depend on clinical validation and integration into medical workflows.
Regulatory Context
This is clearly a medical device/diagnostic test, so it would be subject to regulatory approval (e.g. FDA clearance or CE marking). Such devices typically require clinical trials and must meet standards for safety and accuracy. Liability and compliance in healthcare diagnostics are important considerations.
Trends Impact
This invention aligns with trends in digital health and precision medicine. It uses AI and advanced imaging for diagnostics, fitting with the move toward data-driven, patient-specific healthcare. It also addresses needs highlighted by COVID-19 (coagulopathy) and the focus on less-invasive, rapid medical tests. Overall, it follows trends in healthcare innovation and AI-driven diagnostics.
Limitations Unknowns
Specific performance metrics, development status, cost of implementation, and clinical validation data are not provided. It is unknown how mature the technology is or what regulatory hurdles remain. These missing details limit the assessment of feasibility and commercial readiness.
Rating
The analysis finds this invention addresses a critical healthcare need with an innovative approach, giving it high scores on problem importance and novelty. It aligns well with AI-driven healthcare trends and promises clear benefits (small sample size, fast results, more accurate risk predictions). However, information is missing on technical readiness, patent scope, and clinical validation. The requirement for medical regulatory approval and potential adoption challenges temper its prospects. Overall, its strong potential impact is offset by these practical uncertainties, leading to a moderate-high overall rating.
Problem Significance ( 9/10)
The patent describes a critical gap in medical diagnostics for predicting bleeding/clotting risk. Inaccurate clotting tests can have serious safety impacts in surgeries and for vulnerable patients, suggesting this is a high-impact, high-stakes problem affecting many healthcare cases.
Novelty & Inventive Step ( 8/10)
The core idea of using a tiny blood sample, fluorescent platelet markers, imaging, and AI analysis is not found in standard coagulation tests. This appears to be a non-trivial new combination of imaging and AI for clotting diagnostics. The description claims a significant leap over suspension tests, though without claim details, prior art comparison is limited.
IP Strength & Breadth ( 5/10)
No claims or patent scope are given, so protection is hard to judge. The idea is specific to micro-imaging of platelets with AI, which seems narrower than a broad platform. It may protect a useful method, but could be designed around, implying moderate IP strength.
Advantage vs Existing Solutions ( 9/10)
The invention promises several clear benefits over traditional tests: much smaller sample volume, rapid results, and more accurate risk prediction. These advantages address specific shortcomings of TEG/ROTEM tests (as noted in the text). If achieved, these represent a substantial improvement over existing methods.
Market Size & Adoption Potential ( 7/10)
The market is potentially large (global healthcare and surgery diagnostics), since many patients require clotting assessment. The problem spans multiple medical specialties (surgeries, critical care, pediatrics). However, no market figures are provided, and adoption would depend on clinical validation and integration into hospitals, so some uncertainty remains.
Implementation Feasibility & Cost ( 5/10)
The concept uses existing technologies (imaging and AI), so it is feasible, but combining them into a reliable medical device requires significant R&D. The description is high-level, so detailed technical challenges and costs are unclear. Likely development would be complex with moderate cost.
Regulatory & Liability Friction ( 3/10)
As a blood diagnostic device, it would face substantial regulatory requirements (e.g. FDA or CE approvals) and liability considerations. Such approvals can be lengthy and costly. This suggests high regulatory friction typical for medical devices.
Competitive Defensibility (Real-World) ( 5/10)
If protected by patents, it offers some defensibility, but others could potentially develop similar imaging/AI diagnostics. The concept does not inherently create a long-term moat beyond the IP. Competitors could catch up, so advantage may be moderate.
Versatility & Licensing Potential ( 4/10)
The invention is specific to blood clotting diagnostics. Potential licensees would be in the medical device and healthcare space (e.g. lab equipment makers). It has multiple medical use cases, but it does not extend far beyond this healthcare niche, limiting broad licensing opportunities.
Strategic & Impact Alignment ( 8/10)
This addresses major healthcare needs (patient safety, personalized medicine, use of AI in diagnostics). Improved surgical safety and management of clotting issues align with public health goals. It fits well with trends in digital health and precision medicine, implying a strong positive impact.