Derivative works — US Patent 12377204

Based on US Patent 12,377,204, the following defensive disclosure document outlines novel derivative works, variations, and cross-domain applications designed to publicly disclose incremental inventive steps, thereby rendering them part of the prior art.

Defensive Disclosure: Variations on Personalized Apheresis Systems and Methods

Publication Date: May 13, 2026
Subject Matter: Enhancements and alternative embodiments for systems and methods that calculate and collect a target volume of pure biological fluid from a composite source fluid by accounting for additives and subject-specific physiological parameters.

Disclosures Pertaining to the Method Claim

Axis 1: Material & Component Substitution

1.1. Method Using Raman Spectroscopy for Real-Time Component Analysis

Enabling Description: This method variation replaces inferential calculation of pure plasma volume with direct, real-time measurement. A Raman spectroscopy probe is integrated into the plasma outlet line. The controller is programmed with spectral signatures for plasma, red blood cells, and the specific anticoagulant in use (e.g., sodium citrate). As the collected fluid flows past the probe, the system performs continuous spectral analysis. A chemometric model (e.g., Partial Least Squares regression) running on the controller deconstructs the composite spectrum to provide a real-time, direct concentration measurement of pure plasma and anticoagulant (in g/L). This data is integrated over the flow rate to calculate the exact mass of pure plasma collected, eliminating the need for hematocrit input for this specific calculation and providing a more accurate result.

Mermaid Diagram:

sequenceDiagram
    participant Donor
    participant System
    participant RamanProbe
    participant Controller

    System->>Donor: Withdraw Whole Blood
    System->>System: Add Anticoagulant
    System->>System: Separate Components
    loop Real-time Collection
        System->>RamanProbe: Flow Plasma Mixture
        RamanProbe->>Controller: Transmit Spectral Data
        Controller->>Controller: Deconstruct Spectrum (Chemometrics)
        Controller->>Controller: Calculate Pure Plasma Mass
        alt Pure Plasma Mass < Target Mass
            Controller->>System: Continue Collection
        else Target Mass Reached
            Controller->>System: Stop Collection
            System->>Donor: Return RBCs
            break
        end
    end

1.2. Method Employing Microfluidic Vortex Separation

Enabling Description: This method replaces mechanical centrifugation with a disposable microfluidic separation cartridge. The cartridge contains a series of spiral channels that induce Dean vortices when whole blood is pumped through. These vortices cause heavier red blood cells to migrate towards the outer wall of the channel, while lighter plasma and platelets remain in the center. A channel bifurcation then splits the streams, diverting plasma to a collection line and red blood cells to a return line. The controller manages flow rate to optimize separation efficiency based on the initial hematocrit reading. This method eliminates large moving parts, reduces power consumption, and enables a more compact, portable system.

Mermaid Diagram:

flowchart TD
    A[Start] --> B{Withdraw Blood};
    B --> C[Mix with Anticoagulant];
    C --> D[Pump into Microfluidic Cartridge];
    subgraph Cartridge
        D -- Flow Induces Dean Vortices --> E{Component Migration};
        E -- Heavier --> F[RBCs at Outer Wall];
        E -- Lighter --> G[Plasma at Inner Core];
    end
    F --> H[Return Line to Donor];
    G --> I[Plasma Collection Line];
    I --> J{Calculate Pure Plasma Volume};
    J --> K{Target Volume Reached?};
    K -- No --> D;
    K -- Yes --> L[Stop Process];
    L --> M[End];

Axis 2: Operational Parameter Expansion

2.1. Method for Field-Portable, Low-Volume Plasmapheresis

Enabling Description: This disclosure describes the method applied to a ruggedized, battery-powered device for battlefield or disaster-relief scenarios, specifically for collecting convalescent plasma. The total collection volume is limited to 250 mL of pure plasma to minimize donor stress. The controller operates in a low-power state, using a simplified algorithm based on weight and a pre-set hematocrit of 45% to conserve processing power. Separation is achieved via an acoustic separator using ultrasonic standing waves, which consumes significantly less energy than a mechanical centrifuge. The entire procedure is designed to be completed in under 30 minutes.

Mermaid Diagram:

stateDiagram-v2
    [*] --> Initialize
    Initialize --> Configure: Enter Donor Weight
    Configure --> Collection: Start Low-Power Process
    state Collection {
        [*] --> DrawBlood
        DrawBlood --> AddAnticoagulant
        AddAnticoagulant --> AcousticSeparation
        AcousticSeparation --> CalculateYield: Simplified Algorithm
        CalculateYield --> CheckTarget: Target = 250mL
        CheckTarget --> DrawBlood: Target Not Met
    }
    Collection --> Finalize: Target Met
    Finalize --> ReturnComponents
    ReturnComponents --> [*]

Axis 3: Cross-Domain Application

3.1. Aerospace: Method for Reclaiming Ethylene Glycol from Engine Coolant

Enabling Description: A method for on-orbit maintenance of a spacecraft's thermal control loop. The coolant ("whole blood") is a mixture of water, ethylene glycol ("plasma"), and suspended corrosion particulates ("blood cells"). The system withdraws coolant, and an online particle counter determines the particulate concentration ("hematocrit"). A chelating agent ("anticoagulant") is added to bind metallic ions. The mixture is then processed through a reverse osmosis filter to separate the pure water/glycol solution from particulates and chelated ions. The controller calculates the volume of pure glycol recovered based on the initial concentration and the volume of chelating agent added, stopping when a target reclamation purity is achieved.

Mermaid Diagram:

flowchart LR
    subgraph Thermal Loop
        A[Coolant Reservoir]
    end
    subgraph Reclamation System
        B(Withdraw Coolant)
        C(Measure Particulate Concentration)
        D(Inject Chelating Agent)
        E(Reverse Osmosis Separation)
        F[Pure Glycol/Water]
        G[Waste Particulates]
        H(Calculate Pure Glycol Volume)
        I{Target Reached?}
    end
    A --> B --> C --> D --> E
    E --> F --> H --> I
    E --> G
    I -- No --> B
    I -- Yes --> J[Stop Process]

3.2. AgTech: Method for Automated Maple Syrup Tapping and Grading

Enabling Description: A method for optimizing the extraction and grading of maple sap. The raw sap ("whole blood") is drawn from the tree. An in-line refractometer measures the sugar content, or Brix ("hematocrit"). Based on the initial Brix, the controller calculates the total volume of pure sugar available. The sap is then passed through a pre-filter, and a clarifying agent ("anticoagulant") is added. The controller calculates the volume of pure sugar collected in a container, accounting for the added agent. The system stops drawing from the tap once a target sugar yield is met, preventing over-tapping which can harm the tree.

Mermaid Diagram:

sequenceDiagram
    participant Tree
    participant TappingSystem
    participant Controller
    TappingSystem->>Tree: Draw Sap
    TappingSystem->>Controller: Send Brix Reading
    Controller->>Controller: Calculate Target Sugar Yield
    TappingSystem->>TappingSystem: Add Clarifying Agent
    loop Collection
        TappingSystem->>Controller: Send Volume Data
        Controller->>Controller: Calculate Pure Sugar Collected
        alt Yield < Target
            Note right of Controller: Continue
        else
            Controller->>TappingSystem: Stop Drawing
            break
        end
    end

Axis 4: Integration with Emerging Tech

4.1. Method Using AI-Driven Predictive Risk Stratification

Enabling Description: This method integrates a machine learning model (specifically, a gradient-boosted decision tree) into the controller. Before the procedure, the donor's weight, height, hematocrit, and age are input. The model, trained on a dataset of millions of prior donations, outputs a predicted risk score for a vasovagal reaction or citrate toxicity. Based on this score, the controller automatically adjusts the "target percentage of plasma" to be collected. For a high-risk donor, the target might be lowered from 28.5% to 26.5% of total plasma volume, and the saline compensation volume is increased. During the procedure, the model continuously updates the risk score based on real-time return line pressure and collection speed.

Mermaid Diagram:

flowchart TD
    A[Input Donor Data: Ht, Wt, Hct, Age] --> B{AI Model: Predict Risk Score};
    B --> C{Set Procedure Parameters};
    C -- Low Risk --> D[Target Percentage = 28.5%];
    C -- High Risk --> E[Target Percentage = 26.5%];
    D --> F{Begin Collection};
    E --> F;
    subgraph Real-time Loop
        F --> G[Monitor Pressure, Flow Rate];
        G --> H{AI Model: Update Risk Score};
        H --> I{Adjust Parameters?};
        I -- Yes --> J[Reduce Flow/Target];
        I -- No --> K[Continue];
        J --> K;
        K --> L{Target Reached?};
        L -- No --> G;
    end
    L -- Yes --> M[End Collection];

4.2. Method Using Blockchain for Verifiable Plasma Pedigree ("Vein-to-Vial")

Enabling Description: This method creates an immutable digital record for each plasma unit. When a collection procedure begins, the controller creates a new non-fungible token (NFT) on a private, permissioned blockchain (e.g., Hyperledger Fabric). Key data points—anonymized donor ID, weight, height, hematocrit, the machine's serial number, and the calculated target pure plasma volume—are written to the NFT's metadata. Upon successful collection, the final calculated pure plasma volume and a timestamp are appended to the record, and the transaction is cryptographically signed by the device. This provides a verifiable, tamper-proof audit trail for regulators and fractionators, guaranteeing the provenance and quality metrics of the plasma.

Mermaid Diagram:

erDiagram
    DONOR ||--o{ PROCEDURE : has
    PROCEDURE ||--|{ PLASMA_NFT : generates
    DEVICE ||--o{ PROCEDURE : performs

    DONOR {
        string anonymized_id PK
        float weight
        float height
        float hematocrit
    }
    DEVICE {
        string serial_number PK
    }
    PROCEDURE {
        string procedure_id PK
        datetime timestamp
        float target_volume
        float final_pure_volume
    }
    PLASMA_NFT {
        string token_id PK
        string procedure_id FK
        string transaction_hash
    }

Axis 5: The "Inverse" or Failure Mode

5.1. Method for Graceful Degradation during Anticoagulant Line Occlusion

Enabling Description: A method for safe operation when a partial or full occlusion is detected in the anticoagulant (AC) line, signaled by an over-pressure sensor. The controller immediately enters a "Citrate Rescue" mode. It pauses the whole blood draw pump and reverses the AC pump for a set number of rotations to attempt to clear the occlusion. If pressure does not normalize, it alerts the operator and enters a "Limp-Home" mode. In this mode, the whole blood draw speed is halved, and the AC-to-whole-blood ratio is intentionally increased by 20% to prevent clotting in the extracorporeal circuit at the lower flow rate. The pure plasma calculation is adjusted for the new, richer AC ratio, and the procedure continues to a reduced, safe-and-final collection volume.

Mermaid Diagram:

stateDiagram-v2
    state "Normal Operation" as Normal
    state "Citrate Rescue" as Rescue
    state "Limp-Home Mode" as Limp
    state "Operator Alert" as Alert

    [*] --> Normal
    Normal --> Normal: AC Pressure OK
    Normal --> Rescue: AC Over-pressure Detected
    Rescue --> Normal: Reversal Clears Occlusion
    Rescue --> Alert: Occlusion Persists
    Alert --> Limp: Operator Confirms
    Limp --> [*]: Procedure Complete (Reduced Target)
    Alert --> [*]: Operator Terminates

Combination Prior Art with Open-Source Standards

System Integration with HL7 FHIR Standard: A system where the controller acts as a FHIR client. On startup, it queries a hospital's EHR server via a RESTful API for the donor's Observation resource to retrieve the latest hematocrit value and Patient resource for height and weight. This eliminates manual data entry. Upon completion, the device POSTs a new Procedure resource to the EHR, containing the results: valueQuantity for pure plasma collected, usedCode for the anticoagulant type, and a link back to the Device resource instance. This enables seamless, standardized data flow in a clinical environment.
Controller Operating System based on a Yocto Project Build with a PREEMPT_RT Kernel: The system's embedded controller runs a custom Linux OS built using the Yocto Project for a minimal footprint and enhanced security. The Linux kernel is patched with PREEMPT_RT (real-time preemption) to guarantee deterministic response times for controlling the pumps and valves, which is critical for accurate volumetric calculations. The core apheresis application is isolated in a Docker container, allowing for secure over-the-air updates without altering the validated real-time OS.
Use of MQTT Protocol for Remote Monitoring and Fleet Management: Each plasmapheresis device in a fleet acts as an MQTT client. It securely publishes real-time, non-PHI data (e.g., machine state, error codes, current collected volume, pump RPMs) to an MQTT broker on a central server. This allows a central operations center to monitor the health and status of hundreds of devices simultaneously using a lightweight, low-bandwidth, publish/subscribe protocol. Technicians can be proactively dispatched for maintenance based on predictive failure alerts broadcast over a specific MQTT topic.