Patent 12234236

Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

✓ Generated

The following defensive disclosure aims to create prior art by outlining various derivative variations of the technology described in US patent 12234236. The focus is on the compound of Formula (I) and related therapeutic methods, extending its scope into areas that would render future incremental advancements by competitors obvious or non-novel.

Derivative Variations of US12234236

The primary subject of derivation is the compound of Formula (I), a GLP-1R agonist, and its application in therapeutic methods.

1. Material & Component Substitution

Derivative 1.1: Alternative Bicyclic Heteroaryl Moieties for Z2

  • Enabling Description: A compound analogous to Formula (I) wherein the Z2 moiety, defined as 5- to 10-membered heteroaryl substituted with one halogen and one C3-15 cycloalkyl or C1-6 alkyl-C3-15 cycloalkyl, is replaced with alternative bicyclic heteroaryl systems. Specific substitutions include replacing the indazolyl group with 5,6,7,8-tetrahydro-1,8-naphthyridinyl, 1H-pyrrolo[2,3-b]pyridinyl, or benzothiazolyl, each maintaining the substitution pattern of one halogen (e.g., fluoro, chloro) and one C3-15 cycloalkyl (e.g., cyclopropyl, cyclohexyl) or C1-6 alkyl-C3-15 cycloalkyl (e.g., cyclopropylmethyl) group. These substitutions are chosen to explore iso(bio)steric replacements while maintaining or modulating GLP-1R binding affinity and efficacy, leveraging known scaffold hopping strategies in medicinal chemistry.
  • Specific Technical Terminology: Bicyclic heteroaryl, 5,6,7,8-tetrahydro-1,8-naphthyridinyl, 1H-pyrrolo[2,3-b]pyridinyl, benzothiazolyl, iso(bio)steric replacement, scaffold hopping, GLP-1R binding affinity, efficacy, medicinal chemistry.
classDiagram
    class FormulaI {
        +Z2_Indazolyl
    }
    class Derivative1_1 {
        +Z2_Tetrahydronaphthyridinyl
        +Z2_Pyrrolopyridinyl
        +Z2_Benzothiazolyl
    }
    FormulaI --|> Derivative1_1 : Z2 Moiety Substitution
    Derivative1_1 : +Substituents (Halogen, Cycloalkyl/Alkyl-Cycloalkyl)

Derivative 1.2: Fluoroalkyl/Fluoroalkoxy Substitution for C1-6 Alkyl/Alkoxy Groups

  • Enabling Description: A compound of Formula (I) where one or more C1-6 alkyl or C1-6 alkoxy substituents (e.g., on Q1, Q2, R1-R8) are systematically replaced with their corresponding fluoroalkyl (e.g., CF3, CHF2, CH2F) or fluoroalkoxy (e.g., OCF3, OCHF2, OCH2F) analogs. This substitution aims to enhance metabolic stability, lipophilicity, and potentially membrane permeability, which are critical for oral bioavailability and sustained systemic exposure. For example, a phenyl group (Q1) optionally substituted with C1-6 haloalkyl instead of C1-6 alkyl, or a heterocyclic Q2 group substituted with C1-6 haloalkoxy.
  • Specific Technical Terminology: Fluoroalkyl, fluoroalkoxy, C1-6 alkyl, C1-6 alkoxy, metabolic stability, lipophilicity, membrane permeability, oral bioavailability, sustained systemic exposure, haloalkyl, haloalkoxy.
graph TD
    A[Original Formula I Structure] --> B{Identify C1-6 Alkyl/Alkoxy Position}
    B -- R_alkyl --> C[Replace with C1-6 Haloalkyl]
    B -- R_alkoxy --> D[Replace with C1-6 Haloalkoxy]
    C --> E[Derivative with Enhanced PK]
    D --> E
    E --> F[In vitro/In vivo Metabolic Stability Assay]

2. Operational Parameter Expansion

Derivative 2.1: Ultra-Low Dose Continuous Infusion for Chronic Management

  • Enabling Description: Administration of a compound of Formula (I) via a miniaturized, implantable osmotic pump or transdermal patch system, delivering an ultra-low, constant therapeutic dose (e.g., 0.00001 to 0.0001 mg/kg/day) over extended periods (months to years). This contrasts with intermittent dosing, aiming to maintain steady-state plasma concentrations, minimize peak-trough fluctuations, and reduce side effects associated with high Cmax, particularly for conditions requiring chronic GLP-1R modulation like pre-diabetes or very early-stage obesity. The system would allow for remote programming of infusion rates.
  • Specific Technical Terminology: Implantable osmotic pump, transdermal patch, ultra-low dose, constant therapeutic dose, steady-state plasma concentration, peak-trough fluctuations, Cmax, chronic GLP-1R modulation, pre-diabetes, early-stage obesity, remote programming, infusion rates.
flowchart TD
    A[Compound of Formula I] --> B(Micro-reservoir/Formulation)
    B --> C(Miniaturized Osmotic Pump / Transdermal Patch)
    C --> D{Implant / Apply to Patient}
    D --> E[Continuous Ultra-Low Dose Release]
    E --> F[Stable Plasma Concentration]
    F --> G[Chronic GLP-1R Modulation]
    G --> H[Reduced Side Effects]

Derivative 2.2: Pulsatile Dosing for Enhanced Physiological Mimicry

  • Enabling Description: A compound of Formula (I) delivered using a pulsatile release pharmaceutical formulation or an electronically controlled pump, designed to mimic the endogenous post-prandial release profile of GLP-1. This involves administering boluses of the compound (e.g., 0.1-1 mg/kg/dose) at specific intervals relative to meal times (e.g., 15-30 minutes before or immediately after), or in response to real-time glucose fluctuations detected by continuous glucose monitoring. This approach aims to maximize acute insulinotropic effects, enhance satiety signaling, and potentially overcome receptor desensitization observed with continuous high-level agonism, for conditions like post-prandial hyperglycemia.
  • Specific Technical Terminology: Pulsatile release, electronically controlled pump, endogenous post-prandial release, bolus administration, meal times, continuous glucose monitoring (CGM), insulinotropic effects, satiety signaling, receptor desensitization, post-prandial hyperglycemia.
sequenceDiagram
    participant Patient
    participant CGM_Sensor [Continuous Glucose Monitor]
    participant Smart_Pump [Pulsatile Delivery Pump]
    participant Formula_I [Compound]

    CGM_Sensor ->> Smart_Pump: Real-time Glucose Data
    Patient ->> Smart_Pump: Meal Time Input
    Smart_Pump -->> Smart_Pump: Calculate optimal bolus timing/amount
    Smart_Pump ->> Formula_I: Dispense bolus dose
    Formula_I ->> Patient: Acute GLP-1R activation
    Patient ->> CGM_Sensor: Post-prandial glucose control

3. Cross-Domain Application

Derivative 3.1: Aquaculture Feed Additive for Fish Growth and Health

  • Enabling Description: A compound of Formula (I) incorporated as a feed additive in aquaculture for fish species (e.g., salmon, tilapia, carp) to enhance growth rates, improve feed conversion ratio (FCR), and modulate immune response. The compound would be microencapsulated in a water-stable, gastric-resistant coating suitable for aquatic environments (e.g., alginate-chitosan nanoparticles or lipid-based encapsulation) to ensure stability in water and targeted delivery to the fish gut. Dosage would be optimized based on fish species, age, and farming conditions, delivered through commercial feed pellets.
  • Specific Technical Terminology: Aquaculture, feed additive, fish growth rates, feed conversion ratio (FCR), immune response, microencapsulation, water-stable coating, gastric-resistant coating, alginate-chitosan nanoparticles, lipid-based encapsulation, targeted delivery, feed pellets.
graph TD
    A[Formula I Compound] --> B(Encapsulation Process)
    B --> C{Water-Stable, Gastric-Resistant Microcapsules}
    C --> D(Aquafeed Production)
    D --> E[Commercial Fish Feed Pellets]
    E --> F[Fish Consumption]
    F --> G[Targeted GLP-1R Activation in Fish Gut]
    G --> H[Enhanced Growth, Improved FCR, Modulated Immunity]

Derivative 3.2: Companion Animal Weight Management (Veterinary)

  • Enabling Description: A veterinary pharmaceutical composition containing a compound of Formula (I) specifically formulated for oral administration to companion animals (e.g., dogs, cats) for weight management and treatment of companion animal type 2 diabetes. The formulation would be a palatable, chewable tablet or an oral suspension, optimized for animal pharmacokinetics. Dosage would be calculated based on species, weight, and existing metabolic conditions, with veterinary supervision. This extends the patent's described use in "domestic animals" to a specific therapeutic application in a high-value veterinary market.
  • Specific Technical Terminology: Veterinary pharmaceutical, companion animals, weight management, companion animal type 2 diabetes, palatable chewable tablet, oral suspension, animal pharmacokinetics, veterinary supervision.
flowchart TD
    A[Obese/Diabetic Companion Animal] --> B{Veterinary Diagnosis}
    B -- Yes --> C[Prescribe Formula I (Oral Form)]
    C --> D[Animal Ingests Daily Dose]
    D --> E[GLP-1R Activation in Animal]
    E --> F[Reduced Appetite, Improved Glucose Homeostasis]
    F --> G[Weight Loss / Diabetes Management]
    C --> H[Regular Vet Check-up & Dose Adjustment]

Derivative 3.3: Pest Control (Insect Metabolism Modulation)

  • Enabling Description: A compound of Formula (I) or a structural analog designed to modulate GLP-1R-like receptors in insect pests (e.g., agricultural pests, disease vectors). The compound would be formulated as a bait or spray, disrupting insect feeding behavior, metabolism, and reproductive cycles. This novel approach to pest control would target metabolic pathways distinct from conventional insecticides, potentially reducing resistance development and improving selectivity. Delivery would involve slow-release matrices or microencapsulated formulations suitable for environmental application.
  • Specific Technical Terminology: GLP-1R-like receptors, insect pests, agricultural pests, disease vectors, feeding behavior, metabolism, reproductive cycles, bait formulation, spray formulation, slow-release matrices, microencapsulated formulations, insecticide resistance.
graph TD
    A[Formula I Analog] --> B(Insecticide Formulation)
    B --> C[Environmental Application (Bait/Spray)]
    C --> D[Insect Ingestion/Exposure]
    D --> E[GLP-1R-like Receptor Activation in Insect]
    E --> F{Disrupted Metabolism / Feeding / Reproduction}
    F --> G[Pest Population Reduction]

4. Integration with Emerging Tech

Derivative 4.1: AI-Optimized Compound Synthesis and Process Control

  • Enabling Description: The manufacturing process for compounds of Formula (I) controlled and optimized by an AI system. This AI leverages sensor data from reaction vessels (temperature, pressure, pH, reagent addition rates) and real-time analytical data (HPLC, NMR, mass spectrometry) to predict reaction kinetics, optimize yield, control purity, and minimize side-product formation. The AI adjusts process parameters autonomously, learns from previous batch data, and ensures consistent quality. This includes predictive maintenance schedules for synthesis equipment.
  • Specific Technical Terminology: AI system, reaction kinetics, yield optimization, purity control, side-product formation, autonomous process control, predictive maintenance, HPLC, NMR, mass spectrometry, reaction vessels, real-time analytical data.
flowchart TD
    A[Raw Material Input] --> B(Reaction Vessel with Sensors)
    B -- Process Data (Temp, pH, Pressure) --> C(Real-time Analytics - HPLC, NMR)
    C -- Analytical Data --> D(AI Process Control Engine)
    D -- Optimization Commands --> B
    D -- Predictive Maintenance --> E[Equipment Maintenance System]
    B --> F[Formula I Output (Optimized Yield/Purity)]

Derivative 4.2: IoT-Enabled Smart Packaging for Adherence and Cold Chain Monitoring

  • Enabling Description: Pharmaceutical packaging for a compound of Formula (I) integrated with IoT sensors. Each blister pack or vial contains miniature sensors that detect removal of individual doses, providing adherence data. Additionally, temperature and humidity sensors within the packaging monitor cold chain integrity during storage and transport. This data is wirelessly transmitted to a patient's smartphone app and a cloud-based healthcare platform, allowing for real-time adherence tracking, identification of temperature excursions that might affect drug stability, and automated refill reminders.
  • Specific Technical Terminology: IoT sensors, smart packaging, blister pack, vial, miniature sensors, adherence data, temperature sensors, humidity sensors, cold chain integrity, wireless transmission, smartphone app, cloud-based healthcare platform, real-time adherence tracking, temperature excursions, drug stability, automated refill reminders.
sequenceDiagram
    participant Manufacturer
    participant Distributor
    participant Pharmacy
    participant Patient
    participant Smart_Packaging [IoT-Enabled Packaging]
    participant Cloud_Platform [Healthcare Cloud]

    Manufacturer->>Smart_Packaging: Integrates sensors
    Smart_Packaging->>Distributor: Monitors Cold Chain
    Distributor->>Pharmacy: Monitors Cold Chain
    Pharmacy->>Patient: Dispenses with Adherence Sensor
    Patient->>Smart_Packaging: Takes Dose
    Smart_Packaging->>Patient: Reminds Next Dose (App)
    Smart_Packaging->>Cloud_Platform: Transmits Adherence/Temp Data
    Cloud_Platform->>Pharmacy: Alerts on Non-Adherence/Excursions
    Cloud_Platform->>Manufacturer: Quality & Stability Insights

Derivative 4.3: Blockchain for Patient Consent and Data Governance in Clinical Trials

  • Enabling Description: Clinical trials involving a compound of Formula (I) utilize a decentralized blockchain system for managing patient informed consent and secure data sharing. Each patient's consent for data usage (e.g., physiological responses, adverse events, outcomes) is recorded as an immutable transaction on a blockchain. Patients retain control over their data, granting or revoking access to specific researchers or institutions through cryptographic keys. This ensures data provenance, auditability, and compliance with regulations like GDPR, while facilitating secure, transparent, and efficient multi-site clinical research.
  • Specific Technical Terminology: Decentralized blockchain system, patient informed consent, secure data sharing, immutable transaction, cryptographic keys, data provenance, auditability, GDPR compliance, multi-site clinical research, physiological responses, adverse events, clinical trial outcomes.
graph TD
    A[Patient] --> B{Grant Consent for Data Sharing}
    B -- Signed Consent (Cryptographic) --> C(Blockchain Network)
    C --> D[Immutable Consent Record]
    E[Clinical Site A] -- Uploads Anonymized Data --> C
    F[Clinical Site B] -- Uploads Anonymized Data --> C
    G[Researcher] -- Requests Access (Validated by Blockchain) --> C
    C -- Grants Access (if permitted) --> G[Access to Data]
    C -- Revokes Access --> A

5. The "Inverse" or Failure Mode

Derivative 5.1: GLP-1R Antagonist for Hypoglycemia Reversal

  • Enabling Description: A structurally modified compound of Formula (I) engineered to function as a selective GLP-1R antagonist. This "inverse" compound would competitively bind to the GLP-1 receptor without activating it, thus blocking the effects of endogenous GLP-1 or other GLP-1R agonists. Such an antagonist would be useful for rapidly reversing severe hypoglycemia, particularly in patients over-treated with insulin or GLP-1R agonists, or in rare cases of GLP-1oma. The compound would be formulated for rapid intravenous administration to ensure swift onset of action in emergency situations.
  • Specific Technical Terminology: GLP-1R antagonist, competitive binding, selective antagonist, hypoglycemia reversal, endogenous GLP-1, GLP-1R agonists, GLP-1oma, rapid intravenous administration, swift onset of action.
stateDiagram-v2
    state "Normal State" as Normal
    state "Hypoglycemic Event" as Hypoglycemia
    state "GLP-1R Antagonist Administered" as AntagonistAdmin
    state "GLP-1R Blocked" as ReceptorBlocked
    state "Glucose Levels Normalize" as GlucoseNormal

    Normal --> Hypoglycemia : Insulin Overtreatment / GLP-1oma
    Hypoglycemia --> AntagonistAdmin : Emergency Intervention
    AntagonistAdmin --> ReceptorBlocked : Rapid Binding
    ReceptorBlocked --> GlucoseNormal : Block GLP-1R activity -> increased glucose
    GlucoseNormal --> Normal : Recovery

Derivative 5.2: Self-Limiting Prodrug with pH-Sensitive Deactivation

  • Enabling Description: A prodrug of a compound of Formula (I) designed with a pH-sensitive linker that undergoes rapid hydrolysis and deactivation at physiological pH values slightly outside the normal range (e.g., below pH 6.0 or above pH 8.0), or in specific pathological conditions (e.g., acidic tumor microenvironment). The prodrug would release the active Formula (I) slowly under normal conditions, but in case of systemic acidosis (e.g., severe diabetic ketoacidosis) or alkalosis, the prodrug would rapidly break down into inactive metabolites, thereby reducing the effective circulating concentration of the active drug and preventing exacerbation of metabolic distress or other adverse effects.
  • Specific Technical Terminology: Prodrug, pH-sensitive linker, rapid hydrolysis, deactivation, physiological pH, pathological conditions, acidic tumor microenvironment, systemic acidosis, severe diabetic ketoacidosis, alkalosis, inactive metabolites, circulating concentration, metabolic distress, adverse effects.
graph TD
    A[Prodrug (Formula I Linked)] --> B{Normal pH (6.5-7.5)?}
    B -- Yes --> C[Slow Active Drug Release]
    C --> D[Therapeutic Effect]
    B -- No (pH < 6.0 or pH > 8.0) --> E[Rapid Hydrolysis / Deactivation]
    E --> F[Inactive Metabolites]
    F --> G[Self-Limiting Safety Mechanism]
    D --> G

5.3: Limited-Functionality Diagnostic Tracer (Non-Activating)

  • Enabling Description: A non-activating derivative of a compound of Formula (I) designed exclusively as a GLP-1R imaging tracer, incorporating a non-radioactive tag (e.g., a fluorescent probe, a heavy atom for X-ray contrast, or a paramagnetic metal chelator for MRI). This compound would bind selectively to GLP-1R but lack intrinsic agonist activity. Its purpose is to visualize GLP-1R distribution and density in tissues (e.g., pancreas, brain, heart) for diagnostic purposes (e.g., early detection of beta-cell loss in diabetes, localization of GLP-1R expressing tumors), without altering physiological function. The non-activating nature ensures safety and prevents confounding therapeutic effects during imaging.
  • Specific Technical Terminology: Non-activating derivative, GLP-1R imaging tracer, non-radioactive tag, fluorescent probe, heavy atom, X-ray contrast, paramagnetic metal chelator, MRI, selective binding, intrinsic agonist activity, GLP-1R distribution, GLP-1R density, pancreas, brain, heart, beta-cell loss, GLP-1R expressing tumors, diagnostic imaging.
classDiagram
    class FormulaI_Active {
        +Binds_GLP-1R()
        +Activates_GLP-1R()
        +Therapeutic_Effect()
    }
    class FormulaI_Tracer {
        +Binds_GLP-1R()
        -Activates_GLP-1R()
        +Imaging_Probe_Attached()
        +Diagnostic_Imaging()
    }
    FormulaI_Active <|-- FormulaI_Tracer : Structural Analogue
    FormulaI_Tracer : Binds without activation

Combination Prior Art Scenarios

These scenarios combine the inventive concepts of US12234236 with existing open-source standards, demonstrating how the patent's technology could be integrated with readily available, non-proprietary frameworks.

Combination Prior Art Scenario 1: Formula (I) + Open-Source Electronic Health Record (EHR) Standard (FHIR)

  • Enabling Description: The use of a compound of Formula (I) for treating GLP-1R-mediated diseases, where patient demographics, diagnosis (e.g., T2DM, obesity, NASH), prescribed dosage, administration route (e.g., oral, subcutaneous), observed therapeutic outcomes (e.g., HbA1c, weight, liver fat content), and any adverse drug reactions are meticulously documented within an open-source Electronic Health Record (EHR) system. This system adheres strictly to the Fast Healthcare Interoperability Resources (FHIR) standard (e.g., version R4 or newer) for data exchange. This enables seamless and secure interoperability with other FHIR-compliant systems (e.g., pharmacies, laboratories, insurance providers), facilitating real-world evidence generation, population health management, and personalized treatment adjustments based on standardized, machine-readable data. The integration would involve FHIR resources such as 'MedicationRequest', 'Observation', 'Condition', and 'Patient'.
  • Specific Technical Terminology: Electronic Health Record (EHR), Fast Healthcare Interoperability Resources (FHIR) standard, FHIR R4, GLP-1R-mediated diseases, T2DM, obesity, NASH, HbA1c, liver fat content, adverse drug reactions, interoperability, real-world evidence, population health management, personalized treatment, machine-readable data, FHIR resources (MedicationRequest, Observation, Condition, Patient).

Combination Prior Art Scenario 2: Formula (I) Manufacturing + Open-Source Laboratory Automation (Python/Open-Robot Control)

  • Enabling Description: The large-scale synthesis of a compound of Formula (I) utilizing an automated flow chemistry platform, where all liquid handling, reagent addition, temperature control, and in-line analytical sampling are orchestrated by an open-source laboratory automation system. This system is programmed using Python-based scripting frameworks (e.g., PyLabware, opentrons-api) and communicates with robotic components via open-robot control protocols (e.g., ROS - Robot Operating System). Real-time process data is streamed and stored in an open-source database (e.g., PostgreSQL). This allows for highly reproducible and scalable synthesis, rapid experimentation with reaction parameters, and decentralized sharing of synthesis protocols across different research and manufacturing sites without proprietary software lock-in.
  • Specific Technical Terminology: Automated flow chemistry platform, liquid handling, reagent addition, temperature control, in-line analytical sampling, open-source laboratory automation system, Python-based scripting frameworks, PyLabware, opentrons-api, open-robot control protocols, ROS (Robot Operating System), PostgreSQL, reproducible synthesis, scalable synthesis, decentralized sharing, synthesis protocols, proprietary software lock-in.

Combination Prior Art Scenario 3: Formula (I) Drug Design + Open-Source Cheminformatics & Molecular Modeling Tools

  • Enabling Description: The rational design, virtual screening, and lead optimization of novel GLP-1R agonists based on the scaffold of Formula (I), performed entirely using open-source cheminformatics and molecular modeling software. This workflow includes:
    1. Ligand preparation and 2D/3D descriptor generation using RDKit.
    2. Molecular docking simulations against publicly available GLP-1R crystal structures (e.g., from PDB) using AutoDock Vina or smina.
    3. Molecular dynamics (MD) simulations to assess ligand-receptor stability and binding free energies with GROMACS.
    4. ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) prediction using open-source machine learning models trained on publicly accessible datasets.
      This combination demonstrates a comprehensive, cost-effective, and transparent in silico drug discovery pipeline that can be readily replicated and extended by any researcher, accelerating the development of further GLP-1R modulators.
  • Specific Technical Terminology: Rational drug design, virtual screening, lead optimization, GLP-1R agonists, open-source cheminformatics, molecular modeling software, ligand preparation, 2D/3D descriptor generation, RDKit, molecular docking simulations, GLP-1R crystal structures, PDB, AutoDock Vina, smina, molecular dynamics (MD) simulations, GROMACS, ADMET prediction, machine learning models, in silico drug discovery pipeline.

Generated 5/18/2026, 12:46:37 AM