Methods and systems for multimodal measurement, forecasting, and modulation of aqueous outflow

1 . A method for measuring, forecasting, and modulating aqueous outflow, comprising:

providing an ocular microphysiological system reproducing a trabecular-meshwork-membrane-Schlemm's-canal interface operating under a defined hydrodynamic program comprising time-varying pressure-drop and shear waveforms generated by modulating the aqueous outflow through a microchannel;

acquiring, during execution of the defined hydrodynamic program, synchronized multimodal signals from said ocular microphysiological system including transepithelial/endothelial resistance (TEER) resistance, pressure-flow measurements, optical coherence tomography/optical coherence tomography angiography (OCT/OCTA) images, and Raman spectra;

encoding said multimodal signals into a device-agnostic feature representation comprising descriptors of junction continuity, belt thickness, tortuosity, pathway activity, and outflow-resistance proxies;

executing a physics-informed graph state-space model that fuses the device-agnostic feature representation into inferred parameters, the inferred parameters are inferred from barrier integrity, permeability, and outflow facility subject to monotonic constraints between structural and hydraulic variables, where the physics-informed graph state-space model includes a graph neural network and a physics-based constraint;

quantifying uncertainty from the inferred parameters;

generating calibrated forecasts of aqueous outflow performance; and

controlling a drive actuator according to the calibrated forecasts when the uncertainty and the calibrated forecasts, satisfy a safety gate criterion.

2 . The method of claim 1 , wherein the defined hydrodynamic program imposes a pressure drop of 0-10 mm Hg and shear stress of 0.5-5 dyn·cm −2 .

3 . The method of claim 1 , further comprising performing electrical calibration and optical wavelength calibration prior to acquisition.

4 . The method of claim 1 , wherein the Raman spectra are acquired with near-infrared excitation and spectral resolution of 4-10 cm −1 .

5 . The method of claim 1 , wherein the physics-informed graph state-space model represents trabecular-meshwork and Schlemm's-canal compartments as coupled nodes exchanging mechanical and biochemical messages.

6 . The method of claim 1 , wherein monotonic constraints enforce that increases in junction continuity or VEGFC signaling decrease hydraulic resistance, and increases in ALK5 signaling increase hydraulic resistance.

7 . The method of claim 1 , wherein the quantifying of uncertainty employs conformal prediction to establish coverage probabilities.

8 . The method of claim 1 , further comprising an active-learning controller that selects a next measurement configuration when uncertainty exceeds a defined threshold.

9 . The method of claim 1 , wherein the safety gate criteria restrict at least one of laser power, electrode current density, and maximum pressure drop.

10 . The method of claim 1 , wherein the ocular microphysiological system includes a porous membrane between trabecular-meshwork and Schlemm's canal chambers fabricated from a polycarbonate.

11 . The method of claim 1 , further comprising normalizing heterogeneous device outputs from cross-MPS (microphysiological systems) into a common latent space.

12 . The method of claim 1 , further comprising administering a pharmacologic intervention targeting ALK5/TGF-β pathways.

13 . The method of claim 12 , wherein the pharmacologic intervention includes administering a corticosteroid challenge and forecasts facility recovery under an ALK5 inhibitor regimen.

14 . The method of claim 1 , further comprising storing the device-agnostic feature representation, the inferred parameters, calibrated forecasts, model version, calibration record, and gate outcomes.

15 . A system for multimodal measurement, forecasting, and modulation of aqueous outflow, comprising:

an ocular microphysiological device including:

a trabecular-meshwork compartment,

a porous membrane, and

a Schlemm's canal channel with inlet and outlet ports;

a plurality of synchronized sensors connected to the ocular microphysiological device, the plurality of synchronized sensors configured to measure calibration, transepithelial/endothelial resistance (TEER), pressure-flow pairs, optical coherence tomography/optical coherence tomography angiography (OCT/OCTA) data, and Raman spectra into synchronized sensor data;

a timing hub configured to align the synchronized sensor data to a common clock into a multimodal feature set;

a computing module executing a physics-informed graph state-space model trained to infer uncertainty, barrier integrity, permeability, and outflow facility from the multimodal feature set into model forecasts, where the physics-informed graph state-space model includes a graph neural network and a physics-based constraint; and

a controller configured to control a drive actuator based on the model forecasts when the calibration and the uncertainty satisfy a safety gate criterion.

16 . The system of claim 15 , wherein the computing module applies device-agnostic encoders normalizing geometry, temperature, and sampling cadence.

17 . The system of claim 15 , wherein the drive actuator comprises a dosing pump configured for closed-loop regulation of pressure and flow.

18 . The system of claim 15 , further comprising a calibration subsystem performing transepithelial/endothelial resistance (TEER) blank correction, Raman wavelength alignment, and optical coherence tomography (OCT) scale verification.

19 . The system of claim 15 , wherein the physics-informed graph state-space model includes monotone constraints coupling junction features to hydraulic resistance.

20 . The system of claim 15 , wherein uncertainty and safety gates are implemented as acceptance metrics for coverage, drift, and power thresholds.

21 . The system of claim 15 , wherein the ocular microphysiological device further includes optical windows allowing simultaneous optical coherence tomography/optical coherence tomography angiography (OCT/OCTA) and Raman interrogation.

22 . The system of claim 15 , further comprising a data logger that records calibration artifacts, model parameters, and control histories for regulatory audit.

23 . The system of claim 15 , wherein the computing module executes active-learning logic selecting a next-best measurement.

24 . The system of claim 15 , wherein the plurality of synchronized sensors and the controller are network-connected to permit federated learning across multiple laboratory or clinical sites.

25 . A non-transitory computer-readable medium storing instructions that, when executed by one or more processors coupled to a pump actuator, cause the one or more processors to:

receive calibration and synchronized electrical, hydraulic, optical, and spectroscopic data from an ocular microphysiological system;

encode the synchronized electrical, hydraulic, optical, and spectroscopic data into device-agnostic features;

apply a physics-informed graph state-space model on the device-agnostic features to estimate barrier integrity, permeability, and outflow facility with uncertainty, where the physics-informed graph state-space model includes a graph neural network and a physics-based constraint; and

actuate the pump actuator when the calibration and the uncertainty satisfy a safety gate criterion.

26 . The non-transitory computer-readable medium of claim 25 , wherein the instructions further cause adaptive updating of model parameters based on calibration results or longitudinal drift.

27 . The non-transitory computer-readable medium of claim 25 , wherein the physics-informed graph state-space model employs monotonicity regularization and causal constraints derived from fluid-structure relations.

28 . The non-transitory computer-readable medium of claim 25 , wherein quantification of the uncertainty uses Bayesian techniques to define prediction intervals.

29 . The non-transitory computer-readable medium of claim 25 , wherein the instructions interface with an electronic laboratory notebook to export standardized diagnostic reports.

30 . The non-transitory computer-readable medium of claim 25 , wherein the instructions further cause computation of ALK5 and VEGFC signaling indices from Raman or omics features to forecast therapeutic response.