Systems and methods for multi-modal continuous analyte monitoring

Abstract

A wearable biosensing platform continuously accesses biological fluid via a hollow microneedle array to detect two or more molecular analytes and monitor physiological parameters. The platform comprises electrochemical aptamer-based sensors configured to generate signals associated with analyte concentrations, a fluid integrity monitoring subsystem configured to assess biological fluid transport conditions, a sensor fusion engine configured to generate confidence-weighted analyte outputs based on the signals and the transport conditions and transmits data to a computing device. An edge and cloud-based analytics system that processes the confidence-weighted analyte outputs to generate individualized outputs, including AI insights, trend predictions and physiological state classifications. An applicator is configured to control insertion depth, angle, and force to establish fluidic coupling. A modular sensing architecture comprising a reusable command module and interchangeable sensing modules enables multi-modal operation. A power management system and integrated safety framework support continuous operation.

Description

Attorney Docket No. 147702-0103SYSTEMS AND METHODS FOR MULTI-MODAL CONTINUOUS ANALYTE MONITORINGCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 788,085, filed April 13, 2025; U.S. Provisional Patent Application No. 63 / 922,961, filed November 21, 2025; U.S. Provisional Patent Application No. 63 / 923,031, filed November 22, 2025; U.S. Provisional Patent Application No. 63 / 941,638, filed December 15, 2025; U.S. Provisional Patent Application No. 63 / 941,651, filed November 24, 2025; U.S. Provisional Patent Application No.63 / 941,654, filed December 16, 2025; U.S. Provisional Patent Application No. 63 / 941,659, filed December 16, 2025; U.S. Provisional Patent Application No. 63 / 941,664, filed December 16, 2025; U.S. Provisional Patent Application No. 63 / 941,670, filed December 16, 2025; U.S. Provisional Patent Application No. 63 / 941,682, filed December 16, 2025; and U.S. Provisional Patent Application No. 63 / 956,711, filed January 8, 2026; each of which is incorporated herein by reference in its entirety for all purposes.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] Not Applicable.INCORPORATION BY REFERENCE

[0003] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. To the extent publications and patents or patent applications incorporated by reference contradict the disclosure contained in the specification, the specification is intended to supersede and take precedence over any such contradictory material. The following references may be relevant:

[0004] U.S. Patent Documents:8,708,966 B2 12 / 2014 Allen et al.10,099,043 B2 10 / 2018 Berry et al.Attorney Docket No. 147702-0103,045,142 Bl 6 / 2021 Windmiller et al.,238,683 Bl 2 / 2022 Mars et al.,272,885 B2 3 / 2022 Pushpala et al..284.816 B2 3 / 2022 Shah et al.,410,765 B2 8 / 2022 WHOOP, Inc.,478,194 B2 10 / 2022 Windmiller et al.,524,290 B2 12 / 2022 Francis et al..654.270 B2 5 / 2023 Mansfield et al.,672,965 B2 6 / 2023 Mansfield et al.,684,298 B2 6 / 2023 Tehrani etal.,707,262 B2 7 / 2023 Harshman et al.,813,056 B2 11 / 2023 Singamaneni et al.,819,650 B2 11 / 2023 Pushpala et al.,857,344 B2 1 / 2024 Windmiller et al.,872,055 B2 1 / 2024 Tangney et al.,877,846 B2 1 / 2024 Wei Gao et al.,904,127 B2 2 / 2024 Mansfield et al.,963,796 Bl 4 / 2024 Windmiller et al.,986,614 B2 5 / 2024 Mansfield et al.,011,294 B2 6 / 2024 Campbell et al.,070,313 B2 8 / 2024 Alonso Soski et al.,074,637 B2 8 / 2024 Vallius et al.,097,046 B2 9 / 2024 Avirovikj et al., 109,019 B2 10 / 2024 Yoshikawa et al., 109,032 Bl 10 / 2024 Windmiller et al.,171,555 B2 12 / 2024 Tehrani et al.,220,221 B2 2 / 2025 Pho et al.,279,888 B2 4 / 2025 Campbell et al..285.271 B2 4 / 2025 Campbell et al.,290,359 B2 5 / 2025 Wang et al..336.816 B2 6 / 2025 Campbell et al.Attorney Docket No. 147702-010312,369,830 B2 7 / 2025 Windmiller et al.12,453,516 B2 10 / 2025 Tangney et al.12,465,250 B2 11 / 2025 Tehrani et al.

[0005] U.S. Patent Application Publications:2010 / 0096278 Al 4 / 2010 Shah et al.2014 / 0336487 Al 11 / 2014 Wang et al.2019 / 0336054 Al 11 / 2019 Shah et al.2020 / 0254240 Al 8 / 2020 Windmiller et al.2020 / 0390395 Al 12 / 2020 Pushpala et al.2021 / 0022651 Al 1 / 2021 Emaminejad et al.2021 / 0393201 Al 12 / 2021 Morelock et al.2022 / 0031209 Al 2 / 2022 Windmiller et al.2022 / 0031244 Al 2 / 2022 Windmiller et al.2022 / 0370011 Al 11 / 2022 Windmiller et al.2023 / 0074798 Al 3 / 2023 Tangney et al.2023 / 0083562 Al 3 / 2023 CVS Pharmacy, Inc.2023 / 0094419 Al 3 / 2023 Mansfield et al.2023 / 0099617 Al 3 / 2023 Mansfield et al.2023 / 0137258 Al 5 / 2023 Windmiller et al.2024 / 0325001 Al 10 / 2024 Gao et al.2025 / 0069753 Al 2 / 2025 Aetna Inc.2025 / 0147052 Al 5 / 2025 Wolfe et al.

[0006] International Patent Publications:WO 2017 / 164982 Al 2017 Plaxco et al.TECHNICAL FIELD

[0007] The present disclosure relates to wearable biosensing systems, and more particularly to a multi-modal wearable platform integrating sensing capabilities; hollow microneedle-mediatedAttorney Docket No. 147702-0103interstitial fluid (TSF) sampling, real-time fluid integrity monitoring, electrochemical aptamerbased (EAB) molecular sensing, physiological sensing, environmental sensing, edge-based sensor fusion, a transmitter, and a modular replaceable sensing architecture enabling continuous, minimally invasive biomarker monitoring with cloud-connected artificial intelligence analytics.BACKGROUND

[0008] Chronic and metabolic diseases, including cardiovascular disease, stroke, dementia, Alzheimer's disease, diabetes, obesity, and certain cancers, remain leading causes of morbidity and mortality worldwide. This burden is further compounded by hormonal dysregulation across the human lifespan, including perimenopause, menopause, andropause, postpartum hormonal disruption, fertility disorders, and ovulatory dysfunction, each characterized by dynamic biochemical fluctuations that are not adequately captured by existing monitoring approaches. Conventional diagnostic methods, including laboratory-based blood and urine assays, provide only episodic measurements that are temporally insufficient to capture rapid or transient changes in biomarker concentrations. Existing continuous monitoring devices are generally limited to single-analyte detection using enzymatic sensing architectures and have not been extended to multi-analyte panels spanning hormonal, metabolic, and inflammatory biomarkers.

[0009] No prior wearable continuous monitoring system is known to integrate electrochemical aptamer-based sensing of multiple analytes, including but not limited to estradiol, progesterone, testosterone, luteinizing hormone, and follicle-stimulating hormone with real-time verification of biological fluid transport conditions and end-to-end artificial intelligence analytics. In particular, existing systems lack a dedicated fluid integrity monitoring subsystem configured to compute a transport integrity score representing physical fluid transport conditions and to apply that score as a confidence weight to individual analyte measurements to produce validated analyte outputs. Nor do existing systems provide integrated architectures capable of generating individualized hormonal cycle phase determinations, predictive risk trajectories, and personalized behavioral recommendations from a single continuous biological fluid access point.

[0010] Accordingly, a need exists for an integrated, continuous multi-analyte biosensing platform that combines aptamer-based molecular sensing, real-time fluid transport integrity monitoring, and Al-driven analytics to enable reliable, longitudinal monitoring of hormonal,Attorney Docket No. 147702-0103metabolic, and inflammatory biomarkers. Such a system would support improved detection, prediction, and management of chronic disease risk, hormonal health, and metabolic dysfunction across the human lifespan.BRIEF SUMMARY

[0011] In one embodiment, a biosensing device or system is disclosed. The device or system comprises a body interface module comprising a hollow microneedle array, a microfluidic layer, a molecular sensing module comprising one or more electrochemical aptamer-based sensors, a fluid integrity monitoring subsystem, an edge processor, and a wireless communication module, wherein the edge processor is configured to compute a confidence score for each analyte measurement and generate a validated analyte output from two or more analytes detected in a biological fluid.

[0012] In another embodiment, a method of continuous biological monitoring is disclosed. The method comprises accessing a biological fluid through a hollow microneedle array, monitoring fluid transport integrity, generating signals associated with two or more analyte concentrations, computing a confidence score, generating a validated analyte output, and transmitting the validated analyte output to a computing device.

[0013] In another embodiment, a non-transitory computer-readable medium is disclosed. The medium stores instructions that, when executed by an edge processor of a biosensing device, cause the edge processor to receive signals from one or more electrochemical aptamer-based sensors, receive a transport integrity signal, compute a confidence score, generate a validated analyte output, and cause transmission of the validated analyte output to a computing device.

[0014] Other features and advantages will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, various features of embodiments of the disclosure.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIGS. 1A and IB are a block diagram illustrating an end-to-end system architecture of a biosensing platform in accordance with embodiments of the present disclosure.Attorney Docket No. 147702-0103FIG. 2 is a schematic cross-sectional view of a body interface module comprising a hollow porous microneedle array and microfluidic layer in accordance with embodiments of the present disclosure.FIGS. 3A and 3B is a schematic diagram illustrating an electrochemical aptamer-based sensor electrode configuration in accordance with embodiments of the present disclosure.FIG. 4 is a schematic diagram illustrating a fluid integrity monitoring subsystem comprising flow detection electrode pairs, a transport integrity score output, and a fault status signal, in accordance with embodiments of the present disclosure.FIG. 5 is a block diagram illustrating a modular replaceable sensing architecture comprising a reusable and one or more removable sensing modules in accordance with embodiments of the present disclosure.FIG. 6 is a data flow diagram illustrating a sensor fusion engine and confidence- weighted analytics pipeline in accordance with embodiments of the present disclosure.FIG. 7 is a block diagram illustrating an end-to-end Al processing and electronic system integration architecture in accordance with embodiments of the present disclosure.FIG. 8 is a flowchart illustrating a method of continuous biological monitoring, validated analyte output generation, and Al-driven health intervention in accordance with embodiments of the present disclosure.DETAILED DESCRIPTION

[0016] While preferred embodiments of the present disclosure have been shown and described herein, it will be understood by those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions may occur without departing from the scope of the present disclosure. Various alternatives to the embodiments described herein may be employed. It is intended that the following claims define the scope of the present disclosure and that methods and structures within the scope of these claims and their equivalents be covered thereby.Attorney Docket No. 147702-0103

[0017] Definitions.The following definitions govern the meaning of the corresponding terms as used throughout the present disclosure and in the appended claims. Where a term defined herein is used in a claim, the definition provided herein shall control the meaning of that term. Terms not defined herein shall be given their ordinary and customary meaning as understood by a person of ordinary skill in the relevant art.

[0018] The indefinite articles "a" and "an" mean "one or more" and do not exclude a plurality unless the context expressly dictates otherwise; accordingly, "a," "an," "one or more," and "at least one" are used interchangeably throughout the present disclosure.

[0019] As used herein, the terms “tissue interface” and “body interface” are used interchangeably to refer to any surface, boundary, or region of a subject’s body through which a biosensing device accesses a biological fluid, contacts a tissue, or transmits or receives signals, and the use of either term in the specification or claims is not intended to limit the scope of the present disclosure. The terms “biological fluid” and “biological sample” are used interchangeably to refer to interstitial fluid, blood, plasma, serum, lymph, sweat, saliva, or any other fluid compartment accessible through a tissue interface of a subject. The term “subject” refers to any human or non-human animal. As used herein, the term "transmitter" refers to an electronic module operatively coupled to the molecular sensing module and configured to receive electrochemical signals generated by the one or more electrochemical aptamer-based sensors, process and package the signals into data transmissions, and communicate the data transmissions wirelessly to a computing device. The term "command module" may be used interchangeably with "transmitter" throughout the present disclosure. The transmitter or command module may be configured to include, without limitation, one or more of a microprocessor, a radio frequency communication circuit, a battery, a memory element, or electrode contact points configured to interface with the molecular sensing module. In certain embodiments, the transmitter or command module may be integrated with the body interface module as a single unit or may be configured as a separable component.Attorney Docket No. 147702-0103

[0020] System Overview.

[0021] FIGS. 1 A and IB is a block diagram of an end-to-end biosensing system 100 in accordance with embodiments of the present disclosure. The system 100 comprises a biosensing device 102 configured to access biological fluid from a subject 112 through a tissue interface and to generate validated analyte outputs, a computing device 110 configured to receive and display analyte data, and a cloud Al analytics layer 106 and any computing device e.g., a mobile device 110 configured to perform population-level and subject-specific analytics and to exchange data with one or more electronic systems 108. The biosensing device 102 may be configured as a wearable patch, wristband, ring, watch, or implantable device, or any combination thereof. Each component may operate independently, in coordination with one or more other components, or as part of a fully integrated system.

[0022] In certain embodiments, the biosensing system comprises one or more hollow microneedles defining fluidic pathways configured for continuous extraction and transport of a biological fluid to one or more integrated sensing elements, wherein the sensing elements comprise one or more biorecognition agents including nucleic acid-based, aptamer-based, or programmable binding constructs configured for selective detection of one or more molecular targets. The hollow microneedles may further comprise one or more structural or surface-modification features configured to maintain fluidic patency and signal reliability during continuous wear, including anti-coring tip geometries, lumen-stabilizing structures, or anti-biofouling surface treatments. In certain embodiments, the microneedle array, fluid transport pathways, and sensing elements are co-configured as an integrated microfluidic sensing architecture enabling continuous, multianalyte detection with controlled analyte transport and reduced signal degradation under dynamic physiological conditions.

[0023] Embodiments of the present disclosure may comprise an integrated, multi-modal, end-to-end biosensing platform. The platform may comprise one or more transduction elements configured to interface with a biological matrix, an external environment, or a combination of both. The platform may operate in a non-diagnostic wellness monitoring mode, a diagnostic-support mode, or a hybrid mode, or any combination thereof. Any combination of the foregoing components may be implemented to support management of, reduce the risk of, or supportAttorney Docket No. 147702-0103prevention of one or more chronic diseases, hormonal dysfunction events, or metabolic dysfunction events, including but not limited to cancer, diabetes, cardiovascular disease, stroke, dementia, Alzheimer's disease, obesity, perimenopause, menopause, andropause, postpartum hormonal disruption, fertility disorders, and ovulatory dysfunction.

[0024] Body Interface Module (BIM).

[0025] FIG. 2 is a cross-sectional schematic of a body interface module 200 in accordance with embodiments of the present disclosure. The body interface module 200 may comprise of one or more hollow porous 224 microneedle array 202 one or more shorter microneedles 201 that may be configured for biological fluid flow, sensing, or drug delivery, a microfluidic layer 204, and a molecular sensing module 206, which may further comprise one or more physiological sensing elements 208, one or more environmental sensing elements 210, and one or more combinations of aptamers 212, or any combination thereof.

[0026] Embodiments of the present disclosure, the hollow microneedle array 202 may comprise one or more hollow microneedles configured to penetrate a tissue interface of a subject and access a biological fluid. In certain embodiments, the microneedle array may comprise one or more microneedles selected from hollow microneedles, hollow-bore microneedles, porous microneedles 224, coated microneedles, solid microneedles, or hybrid combinations thereof, configured for biological fluid access, transport, sensing, or drug delivery.

[0027] In certain embodiments, one or more microneedles comprise a tip geometry configured to facilitate insertion into the tissue interface, including one or more of beveled, angled, asymmetric, sharpened, or multi-faceted tip geometries. Such tip geometries may be configured to reduce insertion force, minimize tissue deformation, improve penetration efficiency, or maintain fluidic coupling during insertion and continuous wear. Individual microneedles may range in length from typically 150 to 1,500 micrometers and may have a base diameter of typically 50 to 300 micrometers, though the foregoing ranges are illustrative and not limiting. A microneedle may define one or more lumens including a transport lumen 220 configured to draw biological fluid from the tissue interface and a venting lumen 222 configured to provide pressure equalization, wherein a dual-lumen configuration may maintain continuous biological fluid flow during extended wear periods. A microneedle array may be arranged in a geometric patternAttorney Docket No. 147702-0103comprising typically 9 to 400 hollow microneedles, though the foregoing quantities are illustrative and not limiting.

[0028] Embodiments of the present disclosure, the microfluidic layer 204 may comprise channels, chambers 310, ports 312, vents 312, reservoirs, membranes, capillary structures, and one or more biological fluid safety architecture elements, or any combination thereof. Biological fluid transport may be driven by passive capillary forces, augmented by a water-absorbing polymer acting as a passive osmotic pump 412, or by a micro-pump or electroosmotic pump integrated into the microfluidic layer, or any combination thereof.

[0029] In certain embodiments, the biosensing device further comprises a housing and an attachment interface configured to maintain stable positioning of the microneedle array relative to the tissue interface during operation. The attachment interface may comprise an adhesive layer or other fixation mechanism configured to maintain fluidic coupling, reduce motion-induced artifacts, and preserve signal integrity during continuous wear. In certain embodiments, the housing and attachment interface are configured to distribute mechanical forces and maintain consistent insertion depth and orientation of the microneedle array.

[0030] Electrochemical Aptamer-Based Sensors.

[0031] FIGS. 3A and 3B is a schematic diagram illustrating an EAB sensor configuration 300 in accordance with embodiments of the present disclosure. The molecular sensing module 206 may comprise one or more EAB sensors 302 disposed on one or more functionalized electrodes 304, each individually addressable and functionalized with a biorecognition element specific to a different target analyte, with shared or per-electrode counter 306 and reference electrodes 308.

[0032] Embodiments of the present disclosure may include one or more signal amplification elements operatively coupled to the molecular sensing module, including but not limited to analog instrumentation amplifiers configured to condition electrochemical signals generated by the one or more electrochemical aptamer-based sensors, nanomaterial-based signal enhancement structures comprising gold nanoparticles or graphene integrated at the electrode surface, nucleic acid amplification strategies including rolling circle amplification operatively coupled to the biorecognition layer, or polymer-based amplification materials including PEDOT :PSS; such signalAttorney Docket No. 147702-0103amplification elements may be configured to increase the amplitude or power of the electrochemical signal prior to processing by the edge processor, thereby improving signal-to-noise ratio and enabling detection of target analytes at concentrations not otherwise detectable by the biosensing device without access to one or more biological fluid compartments through a biological interface.

[0033] Embodiments of the present disclosure, EAB sensors may comprise aptamers that, upon binding to a target analyte, undergo a conformational change that alters the proximity of an electrochemical redox reporter group, including but not limited to methylene blue, to the electrode surface, producing a measurable change in faradaic current proportional to analyte concentration. Electrochemical measurements may be performed using square wave voltammetry (SWV), differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS), or any combination thereof. EAB sensors may support electrochemical regeneration wherein an applied potential waveform dissociates bound analyte from the biorecognition element after each measurement cycle, restoring the sensor to its unbound baseline state and enabling continuous monitoring over an intended wear period.

[0034] Embodiments of the present disclosure, the molecular sensing module may be configured to detect two or more analytes in the biological fluid simultaneously from a single biological fluid sample. Target analytes may include but are not limited to glucose, estradiol, progesterone, testosterone, cortisol, lactate, C-reactive protein, beta-amyloid, carboxyhemoglobin, prostatespecific antigen (PSA), tumor necrosis factor-alpha (TNF-alpha), p-tau217, luteinizing hormone (LH), follicle-stimulating hormone (FSH), or any other species detectable by a biorecognition element, or any combination thereof. Analytes may be selected from one or more of the following categories: hormonal analytes, metabolic analytes, inflammatory analytes, neurological analytes, or oncological analytes, or any combination thereof.

[0035] Embodiments of the present disclosure, the scalable analyte panel of the molecular sensing module may comprise any two or more analytes detectable by one or more electrochemical aptamer-based sensors of the platform, without limitation to the specific analytes enumerated herein. The analytes detectable by the platform include, but are not limited to: metabolic analytes such as glucose, lactate, ketones, urea, creatinine, uric acid, triglycerides, cholesterol, and aminoAttorney Docket No. 147702-0103acids; hormonal analytes such as estradiol, progesterone, testosterone, cortisol, luteinizing hormone (LH), follicle-stimulating hormone (FSH), thyroid-stimulating hormone (TSH), insulin, glucagon, growth hormone, dehydroepiandrosterone (DHEA), and melatonin; inflammatory analytes such as C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-8 (IL-8), cytokines, tumor necrosis factor-alpha (TNF-alpha), procalcitonin, and fibrinogen; neurological analytes such as beta-amyloid, p-tau217, alpha-synuclein, neurofilament light chain (NIL), and brain-derived neurotrophic factor (BDNF); oncological analytes such as prostate-specific antigen (PSA), carcinoembryonic antigen (CEA), cancer antigen 125 (CA-125), and circulating tumor DNA; pharmacological analytes such as vancomycin, tobramycin, doxorubicin, irinotecan, and therapeutic drug metabolites; and any other analyte for which a specific aptamer-based biorecognition element has been or can be identified using SELEX or equivalent in vitro selection processes, or any combination thereof.

[0036] Embodiments of the present disclosure, the identity and number of analytes comprising the scalable analyte panel may be selected based on the target disease domain, subject population, clinical application, or operational context, without departing from the scope of the claimed invention. Analyte panels may be configured to support monitoring of one or more of metabolic health and diabetes management; female hormonal health including fertility, ovulatory function, perimenopause, and menopause; male hormonal health including andropause; postpartum hormonal recovery; cardiovascular health; inflammatory and immune status; neurological health and dementia risk; oncological monitoring and therapeutic response; therapeutic drug monitoring and pharmacovigilance; occupational and military readiness; and environmental chemical exposure assessment, or any combination thereof. The foregoing enumeration of analytes and application domains is illustrative and not limiting, and additional analytes and application domains are within the scope of the present disclosure as aptamer-based biorecognition elements for additional analyte targets continue to be identified and validated.

[0037] Embodiments of the present disclosure, the EAB sensor architecture operates according to a unified physical and chemical principle that is predictably applicable across a broad range of target analytes. The unifying principle enables one of ordinary skill in the art to construct an EAB sensor for any analyte for which a specific binding aptamer has been identified or can be identified using known aptamer selection methods, without undue experimentation. The predictability of thisAttorney Docket No. 147702-0103principle across diverse analyte classes — including small molecule metabolites such as glucose and cortisol, hormones such as estradiol and testosterone, proteins such as C-reactive protein and prostate-specific antigen, and neurological biomarkers such as beta-amyloid and p-tau217 — has been established in the scientific literature and is within the ordinary skill of the art. Accordingly, the phrase "two or more electrochemical aptamer-based sensors" as used in the appended claims encompasses EAB sensors configured to detect any two or more analytes for which specific binding aptamers have been or can be identified, and is not limited to the specific analyte examples enumerated herein. EAB sensors are structurally and mechanistically distinct from enzymatic biosensors used in prior art continuous glucose monitoring and multi-analyte wearable sensing systems; the specific electrode surface chemistry, aptamer functionalization, redox reporter attachment, and electrochemical interrogation protocol of EAB sensors are not interchangeable with enzymatic sensor architectures and cannot be combined with hollow microneedle microfluidic systems used in prior enzymatic sensing platforms without substantial redesign beyond ordinary skill.

[0038] Fluid Integrity Monitoring Subsystem.

[0039] FIG. 4 is a schematic diagram illustrating the FIMS 400 in accordance with embodiments of the present disclosure. The FIMS 400 comprises at least two flow detection electrode pairs 402 disposed distally 408 and proximally 410 at spaced positions along the microfluidic layer 204, a flow rate computation module 404, and a fault classification module 406. Transport of biological fluid 414 by a water-absorbing polymer with one or more passive osmotic pumps 412 via one or more vents 312 through one or more microneedles 201.

[0040] Embodiments of the present disclosure provide that the fluid integrity monitoring subsystem (FIMS) computes a real-time biological fluid flow rate 404 based on transit time between a proximal 410 and distal electrode 408 pair 402 and determines a transport integrity score (TIS) as a continuous variable derived from one or more parameters including measured flow rate, flow rate variability, impedance characteristics, and time since a last validated flow event. The FIMS may further classify fault conditions including but not limited to low-flow, noflow, high-flow, and flow instability, each associated with one or more of microneedle clogging, biofouling, air-lock, tissue delamination, improper insertion depth, or microvascular breach. TheAttorney Docket No. 147702-0103TIS may be used by a sensor fusion algorithm, with or without Al integration, as a confidence weight applied to one or more analyte readings, wherein analyte measurements obtained during periods of reduced transport integrity are assigned proportionally lower confidence weights or withheld from reporting pending restoration of fluid flow.

[0041] Embodiments of the present disclosure, the transport integrity score computed by the FIMS represents a hardware-anchored, physical measurement of biological fluid transport conditions within the microfluidic layer 204 and is not equivalent to software-based signal quality metrics or mathematical corrections applied by a general -purpose processor. The application of the transport integrity score as a confidence weight to individual analyte measurements, producing a validated analyte output, constitutes a physical hardware-integrated data validation mechanism not present in prior art wearable biosensors. This architecture provides a technical improvement to wearable biosensor reliability that is not achievable by abstract data processing or by biosensing systems lacking a dedicated fluid transport monitoring subsystem.

[0042] Modular Replaceable Sensing Architecture.

[0043] FIG. 5 is a block diagram illustrating the MRSA 500 in accordance with embodiments of the present disclosure. The MRSA 500 comprises a reusable command module 502 and one or more removable sensing modules 504. The reusable command module 502 may contain an edge processor 506, a wireless communication module 508, a power management module 510, nonvolatile memory 512, amplifier 536, and a module interface 514, or any combination thereof. Each body interface sensing layers 504 may comprise at least one of a molecular sensing layer 516 comprising one or more EAB sensors configured to detect one or more analytes 530 in a biological fluid accessed through a hollow microneedle array, an optical sensing layer 518 comprising one or more photoplethysmographic sensors configured to measure physiological parameters of the subject, an environmental sensing module 520 comprising one or more chemical or physical threat detection elements 534, or a drug delivery module 522 comprising one or more therapeutic delivery ports and microfluidic pathways that may be configured to deliver one or more therapeutic agents through or adjacent to a body interface module 532, or a bioelectrical impedance analysis 526 configured to apply an alternating electrical current at one or more frequencies to a tissue interface of a subject and to measure resulting impedance to generate one or more of a bodyAttorney Docket No. 147702-0103composition estimate, a hydration status estimate, or a phase angle measurement, or any combination thereof.

[0044] Embodiments of the present disclosure, the MRSA enables multi-modal reconfiguration of the biosensing device by permitting replacement of sensing modules of fundamentally different sensing modalities. A subject or clinician may replace a molecular sensing module with a different molecular sensing module functionalized with a different analyte panel, replace a molecular sensing module with an optical sensing module, or add an environmental sensing module to an existing device configuration, without replacing the reusable command module. This multi-modal reconfigurability enables the sensing capabilities of the biosensing device to adapt to the evolving monitoring needs of a subject, including transitions between metabolic monitoring, hormonal monitoring, therapeutic drug monitoring, and environmental threat detection applications, using a single reusable command module.

[0045] Embodiments of the present disclosure, the module interface 514 may employ a mechanical and electrical connector architecture comprising pogo-pin contacts 528, magnetic alignment and keying features, or bayonet or clip-lock retention mechanisms, or any combination thereof. The module interface may further support digital authentication of each sensing module via near-field communication (NFC) or radio-frequency identification (RFID) protocols, enabling the command module to verify module authenticity, retrieve calibration data, and prevent use of incompatible modules.

[0046] Embodiments of the present disclosure, the power management module 510 may comprise one or more of a disposable or rechargeable batteries, including but not limited to a solid-state lithium-ion battery, a lithium-polymer battery, or a thin-film battery; a replaceable primary battery, including but not limited to a coin cell, button cell, or cartridge-format primary battery configured to be replaced without tools; an energy harvesting element, including but not limited to a photovoltaic element, a thermoelectric generator, or a biofuel cell 524 configured to oxidize one or more metabolic substrates; or a wireless charging receiver configured for inductive or resonant energy transfer, or any combination thereof.Attorney Docket No. 147702-0103

[0047] Sensor Fusion and Confidence-Weighted Analytics.

[0048] FIG. 6 is a data flow diagram illustrating a sensor fusion engine 600 and confidence-weighted analytics pipeline 602 in accordance with embodiments of the present disclosure. The sensor fusion engine 600 may integrate data streams from the molecular sensing module 206, one or more physiological sensing elements 208, one or more environmental sensing elements 210, and the FIMS 400 to generate a validated analyte output 604 accompanied by a confidence score 606.

[0049] Embodiments of the present disclosure, the sensor fusion engine may assign a confidence weight to each analyte measurement based on the transport integrity score from the FIMS, the signal quality index from each EAB measurement, the motion artifact severity estimated from accelerometer data, the temperature deviation from sensor calibration temperature, and the time since last validated calibration event, or any combination thereof. The composite confidence score may range from 0.0 to 1.0 and may be reported alongside each analyte reading. An artifact rejection engine within the sensor fusion module may identify and exclude electrochemical signal artifacts caused by motion, electromagnetic interference, electrode biofouling, or reference electrode drift. The edge processor may compute a biological-fluid-lag correction for each analyte measurement using perfusion data from one or more optical sensors. Environmental data from one or more environmental sensing elements may be used to apply temperature compensation corrections to EAB and optical measurements.

[0050] Tri-Shield Safety Architecture.

[0051] Embodiments of the present disclosure may implement a multi-layer safety architecture comprising a hardware safety layer, a firmware safety layer, and an Al safety layer, or any combination thereof. The hardware safety layer may comprise the fluid integrity monitoring subsystem (FIMS) 400, which monitors biological fluid transport conditions through physical flow detection electrode pairs 402 disposed along the microfluidic layer and generates a hardware fault status signal independent of software processing. The firmware safety layer may comprise one or more interrupt-driven fault handlers executing on the edge processor 506 that, upon receipt of a hardware fault status signal, suspend analyte reporting, log a fault event to non-volatile memory, and initiate a subject-facing alert through the wireless communication module 508 or theAttorney Docket No. 147702-0103computing device. The Al safety layer may comprise one or more machine learning models configured to detect anomalous analyte concentration patterns, rate-of-change outliers, or physiological state inconsistencies in the validated analyte output stream and to generate a risk escalation signal transmitted to the computing device or to one or more electronic systems via the cloud Al analytics layer 706. The fluid integrity monitoring subsystem represents the primary hardware-anchored safety element of the Tri-Shield architecture and constitutes a physical improvement to biosensor reliability not achievable by software-based signal quality assessment alone.

[0052] End-to-End Al Integration and Electronic System Connectivity.

[0053] FIG. 7 is a block diagram illustrating an end-to-end Al processing and electronic system integration architecture 700 in accordance with embodiments of the present disclosure. The architecture 700 comprises an edge Al layer 702 executing on the edge processor 506, a computing application 704 executing on the computing device 110, and a cloud Al analytics layer 706 configured to perform population-level and subject-specific analytics and to exchange data with one or more electronic systems 108.

[0054] Embodiments of the present disclosure, the end-to-end Al architecture may be configured as an integrated Al subsystem anchored to specific hardware elements of the biosensing device 102. Al and machine learning models described herein operate on inputs derived from one or more physical hardware elements of the biosensing device, including electrochemical signals from one or more EAB sensors functionalized to specific target analytes, transport integrity signals from FIMS electrode pairs disposed along the microfluidic layer, and perfusion signals from one or more optical sensing elements; this hardware-anchored input architecture provides a technical improvement to the reliability and clinical utility of analyte measurements that is not achievable by Al or machine learning models operating on physiological sensor data alone and that is not abstract. Biological fluid analyte signals processed by the Al subsystem may be obtained from biorecognition elements coupled to one or more microneedles or microfluidic elements. Physiological data processed by the Al subsystem may be obtained from one or more optical sensing elements. Fluid integrity validation inputs to the Al subsystem may be obtained from the FIMS.Attorney Docket No. 147702-0103

[0055] Embodiments of the present disclosure, the Al subsystem may generate one or more outputs from validated analyte outputs including but not limited to physiological state classifications, chronic disease risk trajectories, hormonal cycle phase outputs, and personalized behavioral recommendations configured to support management of, or reduce the risk of, one or more of cancer, diabetes, cardiovascular disease, stroke, dementia, Alzheimer's disease, obesity, perimenopause, menopause, andropause, postpartum hormonal disruption, fertility disorders, and ovulatory dysfunction. One or more Al models configured to generate chronic disease risk trajectories, hormonal cycle phase outputs, or physiological state classifications may be trained on one or more of longitudinal biosensor data comprising validated analyte outputs from two or more analytes; physiological parameter data from optical sensing elements; population-level health outcome data; or subject-specific historical biosensor data. Training datasets, model architectures, and hyperparameter selection for such Al models may be determined by one of ordinary skill in the art based on the target disease domain and available data, without undue experimentation. The selection of convolutional neural network, long short-term memory, transformer, or equivalent deep learning architectures for execution on the edge processor 506, computing device 110, or cloud Al analytics layer 706 does not alter the scope of the claimed invention.

[0056] In certain embodiments, the Al subsystem is configured to generate one or more conditionspecific risk indices or state classifications based on validated analyte outputs, including infection risk, inflammatory state, or hormonal cycle phase. In certain embodiments, the system may further implement a closed-loop control architecture in which one or more sensed analytes are used to determine and initiate a therapeutic or interventional response. Such outputs are derived from inputs obtained from physical biosensing elements and fluid transport monitoring subsystems.

[0057] In certain embodiments, the biosensing system is configured as a closed-loop monitoring and control system in which validated analyte outputs are used to dynamically control one or more system operations, including output presentation, alert generation, or therapeutic or behavioral response. The system may selectively operate in one or more modes, including a wellnessmonitoring mode and a diagnostic-support mode, based on one or more of sensor integrity, fluid transport integrity, and signal confidence parameters. Mode selection and system responses may be automatically adjusted based on the validated analyte output and associated confidence metrics derived from hardware-based sensing subsystems. In certain embodiments, one or more systemAttorney Docket No. 147702-0103outputs, alerts, or responses are enabled, modified, or suppressed based on the signal confidence parameters.

[0058] Embodiments of the present disclosure, the edge Al layer 702 may execute one or more machine learning models on the edge processor to perform real-time biomarker quantification, trend analysis, anomaly detection, signal artifact discrimination, and physiological state classification. The edge Al layer may implement an early-exit neural network architecture configured to terminate on-device inference when a confidence score exceeds a defined threshold and to escalate inference to cloud-based computing resources when confidence falls below the defined threshold.

[0059] Embodiments of the present disclosure, the cloud Al analytics layer 706 may execute population-level and subject-specific analytics including personalized biological-fluid-lag model training, analyte trend prediction and anomaly detection, circadian rhythm and hormonal cycle (from reproductive to menopause and andropause) phase modeling from hormone panel data, federated learning model updates, and health risk stratification algorithms, or any combination thereof. The cloud Al analytics layer may implement a federated learning architecture wherein model training may occur on locally distributed device data without centralizing raw individual subject data, preserving subject privacy while enabling population-level model improvement. The cloud Al analytics layer may implement an agentic orchestration system that autonomously routes data for processing, generates personalized feedback and recommendations, and interfaces with one or more external electronic systems.

[0060] Embodiments of the present disclosure, the platform may be configured for integration with one or more electronic systems 108, including but not limited to electronic health record systems, healthcare information technology systems, enterprise systems, research data platforms, payor and insurance systems, telehealth platforms, educational systems, laboratory information management systems, or any combination thereof, via applicable interoperability interfaces including but not limited to HL7 FHIR-compatible APIs, RESTful APIs, or equivalent standard or proprietary interfaces. Data transmitted to electronic systems may include quality tags comprising confidence score, transport integrity status, and device operating mode, and use-constraint metadata specifying the regulatory context of each analyte reading. The cloud Al analytics layerAttorney Docket No. 147702-0103may generate structured clinical documentation, care gap alerts, adverse event notifications, and clinical decision support outputs formatted for direct integration with one or more electronic systems.

[0061] Embodiments of the present disclosure, the computing application 704 may be configured to receive the validated analyte output and to generate one or more of a trend visualization, a rate-of-change indicator, a health alert, or a personalized Al-driven behavioral recommendation on a display of the computing device. The computing application may present analyte data in a nondiagnostic wellness monitoring mode or a diagnostic-support mode. The computing application may operate on validated analyte outputs and associated confidence metrics that may be derived from the biosensing device and does not generate independent analyte determinations absent such hardware-derived inputs. The computing application may incorporate a natural language generation module configured to produce subject-facing plain-language narratives describing biosensor-derived outputs, derivative metrics, and health alerts, constrained to inputs derived from the physical hardware of the biosensing device.

[0062] Method of Continuous Biological Monitoring.

[0063] FIG. 8 is a flowchart illustrating a method 800 of continuous biological monitoring and Al-driven health intervention in accordance with embodiments of the present disclosure. The method 800 begins at START 802, which may be viewed as equivalent to having properly positioned and activated the biosensing device 102 at a tissue interface of a subject.

[0064] Operation 804 accesses a biological fluid from the tissue interface using the hollow microneedle array 202 and transports the biological fluid through the microfluidic layer 204 to the molecular sensing module 206 and the FIMS 400. Operation 806 monitors, by the FIMS, a rate of biological fluid transport through the microfluidic layer and generates a fault status signal upon detection of a fault condition. Operation 808 generates, by the one or more EAB sensors, signals associated with concentrations of two or more analytes in the biological fluid. Operation 810 computes through the command module 104, by the edge processor, a confidence score for each analyte measurement based at least in part on the fault status signal and a signal quality assessment and generates a validated analyte output. Validation is based on sensor integrity status, fluid transport integrity, and signal quality index.Attorney Docket No. 147702-0103

[0065] Operation 812 transmits the validated analyte output to a computing device and, to a cloud Al analytics layer for further processing. Operation 814 can apply one or more Al models to the one or both modes of analyte output to generate one or more of a physiological state classification, a chronic disease risk trajectory, a hormonal cycle phase output, or a personalized behavioral recommendation and transmit to computing device. Operation 816 compares whether the validated analyte output satisfies a wellness-grade or diagnostic-support-grade threshold. If no threshold is satisfied, operation 818 presents the output in a wellness-monitoring mode, may store the output in memory for subsequent review or federated model update. If a threshold is satisfied, 820 transmits a structured clinical alert, progress note, or clinical decision support output to one or more electronic systems including but not limited to an electronic health record system, a healthcare IT system, a payor system, or a telehealth platform, via an applicable interoperability interface. One or more modes may be transmitted to electronic systems for clinical or wellness support. The method 800 may then return to operation 804 to continue continuous monitoring.

[0066] The operations described above are intended to detect, monitor, and support management of multiple chronic disease states, hormonal dysfunction events, and metabolic dysfunction events concurrently. Physiological conditions may include but are not limited to cancer, diabetes, cardiovascular disease, stroke, dementia, Alzheimer's disease, obesity, perimenopause, menopause, andropause, postpartum hormonal disruption, fertility disorders, and ovulatory dysfunction. In preferred embodiments, multiple analyte data streams are processed simultaneously and their respective confidence scores are parsed concurrently. Accordingly, while the description above refers to particular embodiments of the disclosure, it will be understood that many modifications may be made without departing from the spirit thereof. The presently disclosed embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the disclosure being indicated by the appended claims and their equivalents.

[0067] Housing, Adhesive, and Applicators

[0068] In certain embodiments, the biosensing device further comprises a housing, an attachment interface, and an applicator that are co-configured to establish and maintain a target insertion profile of the microneedle array, wherein the attachment interface comprises an adhesive layer orAttorney Docket No. 147702-0103other fixation mechanism configured to distribute mechanical forces, maintain sealing around the microneedle insertion site, preserve fluidic transport conditions, and reduce motion-induced signal artifacts during continuous wear. In certain embodiments, the applicator is configured to control insertion depth, angle, and force of the microneedle array to achieve consistent engagement with the body interface, reduce tissue trauma, minimize occlusion, and support repeatable analyte measurements across subjects; in certain embodiments, the applicator may further be configured to receive one or more sensed conditions at the tissue interface and adjust one or more insertion parameters based thereon to maintain fluidic coupling and signal stability during operation. The housing, attachment interface, and applicator may be implemented using one or more mechanical, electromechanical, or material-based configurations suitable to achieve the described insertion control, spatial orientation, and coupling functions.

Claims

1. Attorney Docket No. 147702-0103CLAIMS1. A biosensing device or system comprising:a body interface module comprising a hollow microneedle array configured to penetrate a tissue interface of a subject and access a biological fluid therefrom, the hollow microneedle array comprising one or more fluid transport lumens;an applicator operatively coupled to the body interface module and configured to deploy the hollow microneedle array through the tissue interface with a controlled insertion depth, insertion angle, and insertion force;a microfluidic layer coupled to the hollow microneedle array and configured to transport the biological fluid to one or more sensing elements;a molecular sensing module comprising one or more electrochemical aptamer-based sensors configured to generate and condition signals associated with concentrations of two or more analytes in the biological fluid;a fluid integrity monitoring subsystem comprising one or more sensing elements disposed along the microfluidic layer and configured to detect biological fluid transport conditions and generate a transport integrity signal indicative thereof, wherein the one or more sensing elements comprise one or more of electrical, optical, pressure-based, thermal, or impedance-based sensing elements, wherein the transport integrity signal is derived from a physical measurement of biological fluid flow or transport within the microfluidic layer;an edge processor operatively coupled to the molecular sensing module and the fluid integrity monitoring subsystem, the edge processor configured to compute a confidence score for each analyte measurement based at least in part on the transport integrity and a signal quality assessment, and to generate a validated analyte output that is conditioned on the confidence score by selectively weighting, gating, or suppressing the analyte measurement based on the confidence score; anda wireless communication module configured to transmit the validated analyte output to a computing device.Attorney Docket No. 147702-01032. The biosensing device or system of claim 1, wherein the two or more analytes comprise two or more of glucose, estradiol, progesterone, testosterone, cortisol, lactate, C-reactive protein, carboxyhemoglobin, beta-amyloid, prostate-specific antigen, or any combination thereof, including combinations of two or more, three or more, four or more, or five or more of the foregoing.

3. The biosensing device or system of claim 1, wherein the molecular sensing module is configured to simultaneously detect, from a single biological fluid sample accessed through the hollow microneedle array, a scalable analyte panel comprising:(a) in a two-analyte configuration, two or more analytes detectable by one or more electrochemical aptamer-based sensors of the molecular sensing module, including but not limited to glucose, estradiol, progesterone, testosterone, cortisol, lactate, C-reactive protein, carboxyhemoglobin, beta-amyloid, prostate-specific antigen, luteinizing hormone, follicle-stimulating hormone, insulin, p-tau217, or any other analyte for which a specific aptamer-based biorecognition element has been or can be identified, or any combination thereof;(b) in a three-or-more-analyte configuration, three or more analytes detectable by the one or more electrochemical aptamer-based sensors, further comprising analytes from two or more analyte categories selected from hormonal analytes, metabolic analytes, inflammatory analytes, neurological analytes, oncological analytes, pharmacological analytes, or any other category of analytes detectable by aptamer-based biorecognition elements;(c) in a four-or-more-analyte configuration, four or more analytes detectable by the one or more electrochemical aptamer-based sensors, wherein each analyte is detected by an individually addressable working electrode functionalized with a biorecognition element specific to that analyte, the four or more analytes optionally selected to support monitoring of one or more of metabolic health, hormonal health, inflammatory status, neurological health, oncological monitoring, or therapeutic drug monitoring, or any combination thereof; or(d) any combination of the foregoing configurations.

4. The biosensing device or system of claim 1, wherein the two or more analytes are selected from two or more of the following categories: a hormonal analyte, a metabolic analyte, an inflammatory analyte, a neurological analyte, or an oncological analyte, or any combination thereof.Attorney Docket No. 147702-01035. The biosensing device or system of claim 1, wherein the biosensing device or system is configured as one or more of a wearable patch, a wristband, a ring, a watch, or an implantable device.

6. The biosensing device or system of claim 1, wherein the fault condition comprises one or more of microneedle clogging, biofouling, air-lock in the microfluidic layer, tissue delamination, improper insertion depth, or microvascular breach.

7. The biosensing device or system of claim 1, further comprising a modular replaceable sensing architecture comprising a reusable command module and one or more removable sensing modules, each removable sensing module independently removable and replaceable without replacing the reusable command module or any other sensing module, each removable sensing module comprising at least one of: a molecular sensing module comprising one or more electrochemical aptamer-based sensors configured to detect one or more analytes in a biological fluid accessed through the hollow microneedle array; an optical sensing module comprising one or more photoplethysmographic sensors configured to measure one or more physiological parameters of the subject; an environmental sensing module comprising one or more chemical or physical threat detection elements; or a drug delivery module comprising one or more therapeutic delivery ports and microfluidic pathways configured to deliver one or more therapeutic agents; or any combination thereof, wherein the removable sensing modules are independently configurable for different sensing modalities.

8. The biosensing device or system of claim 1, further comprising an optical sensing module comprising one or more photoplethysmographic sensors configured to measure one or more optical properties of perfused tissue of the subject, wherein the edge processor is further configured to compute a biological-fluid-lag correction for each analyte measurement using perfusion data from the optical sensing module.

9. The biosensing device or system of claim 1, further comprising a power management module comprising one or more of a disposable or rechargeable battery, a replaceable battery, an energy harvesting element, or a wireless charging receiver, the power management module configured to supply electrical power to the edge processor, the molecular sensing module, and the wireless communication module.Attorney Docket No. 147702-010310. The biosensing device or system of claim 1, wherein the edge processor is further configured to execute one or more machine learning models operating on validated analyte outputs generated from electrochemical signals of the one or more electrochemical aptamer-based sensors and transport integrity signals of the fluid integrity monitoring subsystem, to generate, from the validated analyte output, one or more of a physiological state classification, based on temporal relationships among the two or more analytes derived from continuous measurements, a chronic disease risk trajectory, a hormonal cycle phase output, or a personalized behavioral recommendation configured to support management of, or reduce the risk of, one or more of cancer, diabetes, cardiovascular disease, stroke, dementia, Alzheimer's disease, obesity, perimenopause, menopause, andropause, postpartum hormonal disruption, fertility disorders, or ovulatory dysfunction.

11. The biosensing device or system of claim 1, wherein the hollow microneedle array comprises one or more structural features configured to maintain continuous fluid flow through the one or more fluid transport lumens during wear, including one or more of:(i) anti-coring geometries at a tip of one or more microneedles;(ii) lumen support structures configured to resist collapse of the one or more fluid transport lumens under compressive forces encountered during normal wear; or(iii) anti-fouling surface treatments applied to one or more interior or exterior surfaces of the hollow microneedle array.

12. The biosensing device or system of claim 1, wherein the one or more electrochemical aptamer-based sensors comprise one or more biorecognition agents that are:(i) nucleic acid-based, including one or more aptamers, DNAzymes, or nucleic acid-based CRISPR recognition elements;(ii) configurable to selectively bind a target analyte through sequence-dependent molecular recognition; and(iii) operatively coupled to an electrochemical transducer configured to generate a measurable signal upon target analyte binding.Attorney Docket No. 147702-010313. The biosensing device or system of claim 1, wherein the hollow microneedle array, the microfluidic layer, and the one or more electrochemical aptamer-based sensors are configured as an integrated microfluidic sensing architecture in which:(i) biological fluid accessed from the tissue interface flows continuously from the one or more fluid transport lumens through the microfluidic layer to the one or more electrochemical aptamer-based sensors without interruption of the fluid pathway and without intermediate sample isolation or storage; and(ii) the integrated microfluidic sensing architecture is configured to enable continuous multi-analyte detection of two or more analytes simultaneously from a single biological fluid sample,wherein the two or more analytes are continuously detected from a single biological fluid access point defined by the hollow microneedle array.

14. The biosensing system of claim 1, wherein the edge processor is configured to generate a hormonal cycle phase output based on temporal patterns of two or more analytes detected from the biological fluid, wherein the hormonal cycle phase output is derived from signals generated by the one or more sensing elements and validated based on one or more hardware-derived signal quality or transport integrity parameters.

15. The biosensing system of claim 1 , wherein the edge processor is configured to generate a condition-specific risk index based on one or more analytes detected from the biological fluid, wherein the condition-specific risk index corresponds to a physiological or pathological state and is computed using inputs derived from the one or more sensing elements and one or more system-derived confidence or validation parameters.

16. The biosensing system of claim 1, further comprising a therapeutic delivery module, wherein the edge processor is configured to determine a therapeutic action based on the analyte output, wherein the therapeutic action is determined based on (i) satisfaction of one or more predefined analyte conditions and (ii) satisfaction of a corresponding confidence threshold derived from one or more hardware-derived validation parameters and to initiate delivery of a therapeutic agent via the therapeutic delivery module in response to the determined therapeutic action.Attorney Docket No. 147702-010317. The biosensing system of claim 1, wherein the edge processor is configured to operate the biosensing system as a closed-loop monitoring and control system,wherein one or more analyte outputs derived from the one or more sensing elements are used to dynamically control one or more system operations, including output generation, alert generation, or initiation of a responsive action, and wherein the analyte outputs are validated based on one or more hardware-derived parameters including signal quality or fluid transport integrity.

18. The biosensing system of claim 1, further comprising a housing and an attachment interface configured to maintain positioning of the microneedle array relative to a tissue interface during operation.

19. The biosensing system of claim 1, wherein the attachment interface comprises an adhesive layer configured to maintain fluidic coupling and reduce motion-induced signal artifacts during continuous wear.

20. The biosensing device or system of claim 1, wherein the applicator is configured to deploy the hollow microneedle array such that the controlled insertion depth, insertion angle, and insertion force are selected to:(i) establish and maintain fluidic coupling between the one or more fluid transport lumens and a biological fluid compartment of the subject during operation; and(ii) maintain signal stability of the one or more electrochemical aptamer-based sensors during continuous operation at the tissue interface.

21. The biosensing device or system of claim 1, wherein the edge processor is further configured to apply a sensor calibration correction to each analyte measurement by comparing a measured electrochemical signal from each of the one or more electrochemical aptamer-based sensors against a stored calibration reference associated with that sensor, and to generate a drift-corrected analyte concentration from the calibration correction, wherein the calibration correction is updated at each measurement cycle based on one or more of temperature data from an environmental sensor, signal baseline drift computed from a running signal average, or a factory calibration coefficient stored in non-volatile memory of the biosensing device wherein each validated analyte output is associated with a record comprising one or more of a sensor identifier, a calibration state, or a transport integrity score.Attorney Docket No. 147702-010322. The biosensing device or system of claim 1, wherein the wireless communication module is further configured to receive an over-the-air firmware update package from a computing device or a cloud computing system, and wherein the edge processor is further configured to authenticate the firmware update package, store the authenticated firmware update in non-volatile memory, and execute the updated firmware upon a subsequent device initialization, without requiring physical connection or removal of the biosensing device from a subject.

23. The biosensing device or system of claim 1, wherein the one or more electrochemical aptamer-based sensors are configured to undergo repeated binding and regeneration cycles while maintaining sensitivity to the target analyte within a predefined performance threshold over a continuous monitoring period during continuous in vivo operation.

24. The biosensing device or system of claim 1, wherein the microneedle array further comprises one or more microneedles selected from hollow-bore microneedles, porous microneedles, coated microneedles, solid microneedles, or hybrid combinations thereof.

25. The biosensing device or system of claim 1, wherein one or more microneedles comprise a tip geometry selected from beveled, angled, asymmetric, sharpened, or multi-faceted configurations configured to facilitate insertion into the tissue interface.

26. A method of continuous biological monitoring comprising:deploying, by an applicator, a hollow microneedle array through a tissue interface of a subject with a controlled insertion depth, insertion angle, and insertion force;accessing a biological fluid from a tissue interface of a subject using a hollow microneedle array of a biosensing device;transporting the biological fluid through a microfluidic layer to one or more electrochemical aptamer-based sensors;monitoring, by a fluid integrity monitoring subsystem, a rate of biological fluid transport through the microfluidic layer and generating a fault status signal upon detection of a fault condition;generating, by the one or more electrochemical aptamer-based sensors, signals associated with concentrations of two or more analytes in the biological fluid;Attorney Docket No. 147702-0103computing, by an edge processor, a confidence score for each analyte measurement based at least in part on the fault status signal and a signal quality assessment;generating, by the edge processor, a validated analyte output based on the signals and the confidence score; andtransmitting, by a wireless communication module, the validated analyte output to a computing device.

27. The method of claim 26, wherein the edge processor is configured to selectively operate the biosensing system in one of a plurality of operating modes, including but not limited to a wellness-monitoring mode and a diagnostic-support mode, based on one or more of analyte output, signal quality, fluid transport integrity, or a confidence score associated therewith.

28. The method of claim 26, wherein the edge processor is configured to condition one or more system responses on a confidence metric associated with the analyte output, such that one or more outputs, alerts, or actions are enabled, modified, or suppressed based on the confidence metric.

29. The method of claim 26, further comprising classifying each validated analyte output as a wellness-grade output or a diagnostic-support-grade output based on one or more of device configuration, signal quality metrics, or sensor integrity status.

30. The method of claim 26, further comprising regenerating the one or more electrochemical aptamer-based sensors by applying a potential waveform to dissociate bound analyte from an aptamer after each measurement cycle.

31. The method of claim 26, further comprising fusing the signals from the one or more electrochemical aptamer-based sensors with physiological data from one or more optical sensors to generate a confidence-weighted multi-modal analyte estimate.

32. The method of claim 26, further comprising executing, by the edge processor or a cloud Al analytics layer, one or more machine learning models operating on validated analyte outputs generated from electrochemical signals of the one or more electrochemical aptamer-based sensors and transport integrity signals of the fluid integrity monitoring subsystem, to generate from the validated analyte output one or more of a physiological state classification, a chronic disease riskAttorney Docket No. 147702-0103trajectory, a hormonal cycle phase output, or a personalized behavioral recommendation configured to reduce the risk of, or support management of, one or more of cancer, diabetes, cardiovascular disease, stroke, dementia, Alzheimer's disease, obesity, perimenopause, menopause, andropause, postpartum hormonal disruption, fertility disorders, or ovulatory dysfunction.

33. The method of claim 26, further comprising transmitting the validated analyte output from the computing device to a cloud Al analytics layer for longitudinal trend analysis, federated model training, or integration with one or more electronic systems.

34. The method of claim 26, further comprising delivering, by a drug delivery module of the biosensing device, one or more therapeutic agents through or adjacent to the hollow microneedle array in response to a validated analyte output satisfying a therapeutic threshold defined by one or more of analyte concentration, rate of change, or physiological state classification.

35. The method of claim 26, further comprising, upon detection of the fault condition by the fluid integrity monitoring subsystem: suspending transmission of validated analyte outputs; generating, by the edge processor, a fault event record comprising a fault classification, a timestamp, and a last known transport integrity score; transmitting, by the wireless communication module, a fault alert to the computing device; and, if a fault condition persists beyond a defined duration threshold, transmitting a structured fault notification to one or more electronic systems via an applicable interoperability interface.

36. A non-transitory computer-readable medium storing instructions that, when executed by an edge processor of a biosensing device comprising a hollow microneedle array, one or more electrochemical aptamer-based sensors individually addressable and each functionalized with a biorecognition element specific to a different target analyte, a microfluidic layer coupling the hollow microneedle array to the one or more electrochemical aptamer-based sensors, and a fluid integrity monitoring subsystem comprising at least two flow detection electrode pairs disposed at spaced positions along the microfluidic layer, a flow rate computation module configured to compute a real-time biological fluid flow rate based on transit time between the at least two flowAttorney Docket No. 147702-0103detection electrode pairs, and a fault classification module configured to classify fault conditions based on the computed flow rate, cause the edge processor to:receive signals from the one or more electrochemical aptamer-based sensors associated with concentrations of two or more analytes in a biological fluid accessed through the hollow microneedle array;receive a transport integrity signal from the fluid integrity monitoring subsystem monitoring biological fluid transport through the microfluidic layer;compute a confidence score for each analyte measurement based at least in part on the transport integrity signal and a signal quality assessment;generate a validated analyte output by applying the confidence score to gate, weight, or suppress each analyte measurement; andcause transmission of the validated analyte output to a computing device via a wireless communication module.

37. The non-transitory computer-readable medium of claim 36, wherein the instructions further cause the edge processor to perform one or more signal conditioning operations comprising: (i) executing an artifact rejection algorithm configured to identify and exclude one or more of motion artifacts, electromagnetic interference, or sensor drift from an analyte measurement; and (ii) applying a temperature compensation correction to the analyte measurement using data from one or more environmental sensors.

38. The non-transitory computer-readable medium of claim 36, wherein the instructions further cause the edge processor to execute a diagnostic-support gating function that conditionally enables diagnostic-grade analyte outputs based on verification of one or more of sensor integrity status, fluid transport integrity, signal quality index, or device calibration state, and to initiate transmission of a structured output to one or more electronic systems upon satisfaction of the diagnostic-support gating function, the one or more electronic systems comprising one or more of an electronic health record system, a healthcare information technology system, an enterprise system, a research data platform, a payor system, or a telehealth platform.

39. The biosensing device or system of claim 2, wherein the applicator is further configured to:Attorney Docket No. 147702-0103(i) receive one or more sensed conditions of the tissue interface prior to or during insertion of the hollow microneedle array, the one or more sensed conditions including one or more of tissue impedance, tissue compliance, surface hydration, or microneedle insertion force feedback; and(ii) adjust one or more insertion parameters selected from insertion depth, insertion angle, and insertion force based at least in part on the one or more sensed conditions, to maintain fluidic coupling and signal stability of the one or more electrochemical aptamer-based sensors.

40. The biosensing device or system of claim 2, wherein the two or more analytes comprise one or more of vancomycin, tobramycin, procalcitonin, C-reactive protein, interleukin-6, or any combination thereof, and wherein the edge processor is further configured to generate a sepsis risk score or a therapeutic drug concentration output from the validated analyte output.

41. The biosensing device or system of claim 2, wherein the environmental sensing module is configured to detect one or more of ambient temperature, humidity, barometric pressure, volatile organic compounds, or particulate matter concentration, and wherein the edge processor is further configured to correlate detected environmental parameters with concurrent validated analyte outputs to identify environment-associated biomarker perturbations.

42. The biosensing device or system of claim 7, wherein the drug delivery module is configured to deliver one or more therapeutic agents through or adjacent to the hollow microneedle array in response to one or more of a validated analyte output, a physiological state classification, or a clinician-initiated command transmitted from the computing device.

43. The biosensing device or system of claim 7, wherein the reusable command module further comprises a module authentication interface configured to authenticate each removable sensing module via near-field communication or radio-frequency identification protocols, wherein authentication comprises verifying module identity, retrieving calibration coefficients associated with the authenticated sensing module, and preventing activation of an incompatible or unauthenticated sensing module.

44. The biosensing device or system of claim 7, wherein one or more of the removable sensing modules further comprises a bioelectrical impedance analysis module 526 configured toAttorney Docket No. 147702-0103apply an alternating electrical current at one or more frequencies to a tissue interface of a subject and to measure resulting impedance to generate one or more of a body composition estimate, a hydration status estimate, or a phase angle measurement, wherein the edge processor is further configured to incorporate the bioelectrical impedance measurement into the validated analyte output or a composite physiological state classification.

45. The biosensing device or system of claim 7, wherein each removable sensing module comprises a unique identifier and an associated calibration dataset, and wherein the reusable command module is configured to authenticate the removable sensing module and apply the associated calibration dataset prior to enabling operation of the removable sensing module.

46. The biosensing device or system of claim 9, wherein the energy harvesting element comprises a biofuel cell configured to oxidize one or more metabolic substrates present in the biological fluid accessed through the hollow microneedle array, including but not limited to glucose, lactate, or any combination thereof, to generate electrical energy, wherein the biofuel cell is operatively coupled to the power management module to supplement or replace battery power during active monitoring.

47. The biosensing device or system of claim 16, wherein the therapeutic action is initiated only when the analyte output satisfies a predefined confidence threshold based on one or more hardware-derived validation parameters.

48. The biosensing device or system of claim 16, wherein the one or more machine learning models comprise a digital twin model configured to generate a time-evolving physiological state representation of the subject from longitudinal validated analyte outputs, wherein the digital twin model is updated at each monitoring cycle using validated analyte outputs generated from electrochemical signals of the one or more electrochemical aptamerbased sensors and transport integrity signals of the fluid integrity monitoring subsystem.

49. The biosensing device or system of claim 10, wherein the one or more machine learning models are configured to generate a hormonal cycle phase output from validated analyte outputs comprising two or more of estradiol, progesterone, luteinizing hormone, follicle-stimulating hormone, or testosterone, wherein the hormonal cycle phase output is not achievableAttorney Docket No. 147702-0103by a biosensing device or system that does not access one or more biological fluid compartments through a biological interface.

50. The method of claim 29, further comprising updating, by the edge processor or a cloud Al analytics layer, a digital twin model representing a time-evolving physiological state of the subject using the validated analyte output, and generating from the digital twin model one or more of a predictive health trajectory, a chronic disease risk score, or a personalized intervention recommendation.

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