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Towards a Bioartificial Kidney: Validating Nanoporous Filtration Membranes

Towards a Bioartificial Kidney: Validating Nanoporous Filtration Membranes. Jacob Bumpus, BME/EE 2014 Casey Fitzgerald, BME 2014 Michael Schultis, BME/EE 2014. Background. 600,000 patients were treated for end stage renal disease (ESRD) in the US alone in 2010

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Towards a Bioartificial Kidney: Validating Nanoporous Filtration Membranes

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  1. Towards a Bioartificial Kidney: Validating Nanoporous Filtration Membranes Jacob Bumpus, BME/EE 2014 Casey Fitzgerald, BME 2014 Michael Schultis, BME/EE 2014

  2. Background • 600,000 patients were treated for end stage renal disease (ESRD) in the US alone in 2010 • Current treatment procedures include kidney transplant and routine dialysis • Dialysis: COSTLY • $$: ~$65,000/patient/yr. • TIME: often requiring 3 treatments /wk. • Significant shortage of donor organs for transplant means that many patients are left with no options other than years of routine dialysis • Development of an implantable bioartificial kidney (BAK) would revolutionize treatment of end stage renal disease (ESRD). • Improve patient outcomes • Reduce economic burden of treatment Concept illustration of an implantable bioartificial kidney. Courtesy of Shuvo Roy Image Citation: Fissell, William H., Shuvo Roy, and Andrew Davenport. "Achieving more frequent and longer dialysis for the majority: wearable dialysis and implantable artificial kidney devices." Kidney international 84.2 (2013): 256-264.

  3. Background Dr. Fissell is working to develop an implantable bioartificial kidney using nanoporous silicon membranes as biological filters These chips feature nanometer-scale pore arrays, invisible to optical characterization methods Screenshots courtesy UCSF School of Pharmacy http://pharmacy.ucsf.edu/kidney-project/

  4. Problem Statement In order to verify the silicon chips received from their collaborators, the Fissell Lab uses a set of experiments to measure the chips’ filtration performance under a variety of conditions and correlate this to their pore sizes The Fissell lab must manually configure these filtration experiments, monitor them continuously throughout their duration (sometimes days to weeks long), and collect data by hand Current experiments are unable to simulate physiologically relevant fluid flow profiles, and are limited to constant flow rates No failsafes exist in order to protect the silicon membranes from being damaged in the event of deviations from preset conditions

  5. Clinical Relevance • Our design: • Increases efficiency of experimentation by fully automating a variety of test protocols, allowing the group to characterize more chips • Reduces project risk of lost time and money by adding failsafes against chip fracture ($1000’s/chip) • Maximizes experimental control by tightly coupling pressure monitoring to hardware output and adjusting for temporal drift • Adds greater experimental relevance by allowing an adaptable physiological input platform, including simulation of pathophysiologic pressure conditions (hypertension)

  6. Needs Statement To design an integrated hardware/software suite that will streamline verification of these silicon membranes while maximizing experimental control and precisionand minimizing user involvement

  7. Goals Experimental setups should be fully automated, permitting the lab technician to begin the experiments and then cease involvement except for occasional system monitoring Allow user-defined hardware setup so that numerous different experiments can be run from the same system that is modular and expandable An intuitive graphical user interface (GUI) should be developed in order to allow the user to control multiple experiments in an effective and efficient manner so that setting the experiment parameters is secondary to deciding what the parameters should be. Add flow rate control and dialysate measurement to the current pressure control feedback system.

  8. Factors • Software Platform • LabVIEW more $ / much less development time • Software concurrency • More fewer programs running but internals are more complex • Hardware connections • Fewer cheaper in size and $ but more technically challenging

  9. Experiments • The solution must automate three modes of experimentation • Hydraulic Permeability Mode • Measures convective flow across membrane at various pressures (uL/min/psi) • Filtration Mode • Collect filtrate samples at various pressures for further analysis • Dialysis Mode • Sets and Measures diffusive flow across membrane with no pressure differential • Filtration and Dialysis Mode should include an option to run with constant flow or a periodic waveform

  10. System and Environment

  11. Experimental Setup – Dialysis Mode Filtration Membrane Peristaltic Pump Peristaltic Pump Pressure Transducer Pressure Transducer Air Air Air Regulator Syringe Pump Dialysate Side Blood Side PSI PSI To House Air To House Air

  12. Feedback Control Diagram Pressure Transducer 1 Voltage Signal 1 Pressure (Blood) ADC Arduino/LabVIEW Peristaltic Pumps Flow Rate Setpoint Flows or Waveforms Σ RS-232 Signals Pump VI HP ΔP PID Loop ΔV Pressure Regulator 1 Error Voltage Pressure (Blood) Σ Σ Voltage Pressure Regulator 2 Voltage Pressure (Dialysate) Setpoint Pressure Σ Conversion VI ADC Pressure Transducer 2 Voltage Signal 2 Pressure (Dialysate)

  13. Control Box Concept 1 2 3 4 6 5 AC Power Line H 7 8 N Pressure Transducers Power Supply G 24 Pressure Regulators 12 1 2 4 5 6 3 7 8 5 -12 General Purpose USB 2 4 5 1 3 6 7 Through Hole Board R 9 10 11 12 8 13 14 C Control Box: Front View USB Hubs and Female Connector Ports Control Box: Top View

  14. Ultrasound Blood Velocity Reading

  15. Estimated Waveform Velocity (cm/s) Time (s)

  16. Generated Pressure Waveform

  17. Comparison

  18. Software Architecture Diagram Top Level Menu Quadrant 4 Quadrant 1 Quadrant 2 Quadrant 3 Hydraulic Permeability Filtration Dialysis

  19. Hardware select (Pump, Transducer/Regulator, Balance) Hardware select (Pump, Transducer/Regulator, Balance) Hardware select (2x Pump, 2x Transducer/Regulator, Balance, Syringe Pump) Experimental Runtime GUI Peristaltic Pump Mass Balance Pressure Transducer Syringe Pump ExperimentOverview Air Regulator Calibration

  20. Top Level Menu

  21. Hardware Select

  22. Experimental Runtime GUI Experiment Overview Pressure Transducer Transducer Calibration

  23. Experimental Runtime GUI Mass Balance Peristaltic Pump Syringe Pump In Progress

  24. Hydraulic Permeability Experiment Load from File

  25. Hydraulic Permeability Results Experiment Results Data Log

  26. Fail Safes • Set point = 0 • Overrides the PID controller • Record Max/Min Pressure • Alert user of potential errors • Next: Automatic shut-down • Error Handling • What to do if something goes wrong? Error Handling Demo gif

  27. Recent Progress • LabVIEW Control of • Pressure transducer (COMPLETE) • Pressure Regulator (COMPLETE) • Peristaltic Pump (COMPLETE) • Mass balance (COMPLETE) • Syringe Pump (IN PROGRESS) • LabVIEW PID feedback loop for pressure setup • Improved/updated circuitry • Initial iterations of pulsatile flow • Abstract submission to American Society for Artificial Internal Organs (ASAIO) Student Design Competition • Fully Automated Hydraulic Permeability Experiment • Initial Fail-safes and Error handling

  28. Next Steps • Continue to iterate towards more physiologically relevant pulsatility • Develop Dialysate Mode Automation • Incorporate syringe pump control into complete system • Finalize power supply and order all components • Develop a 1st iteration CAD model of our hardware container

  29. Gantt Chart

  30. Special Thanks To: • Vanderbilt University Medical Center • Vanderbilt School of Engineering • Vanderbilt Renal Nanotechnology Lab • Dr. William Fissell • Joey Groszek • Dr. Amanda Buck • Dr. Tim Holman • Dr. Matthew Walker III • JustMyPACE Peer Senior Design Group

  31. Questions?

  32. Hydraulic Permeability Mode Fissell, William H., et al. "High-performance silicon nanopore hemofiltration membranes." Journal of membrane science 326.1 (2009): 58-63.

  33. Filtration/Dialysis Mode Filtrate Mass/ Original Mass (θ) Ideal Filtration Example 1 psi Pressure Example 2 psi Pressure 0 Size (arbitrary units)

  34. Previous System

  35. Previous Interface

  36. Appendix: Feedback Control Simplified Pressure Transducer 1 Voltage Signal 1 Pressure (Blood) ADC Arduino/LabVIEW PID Loop ΔV Pressure Regulator 1 Error Voltage Σ Σ Voltage Setpoint Pressure Pressure Regulator 2 Voltage Conversion VI ADC Pressure Transducer 2 Voltage Signal 2 Pressure (Dialysate)

  37. Appendix: Feedback Control Diagram Pressure Transducer 1 Voltage Signal 1 Pressure (Blood) ADC Arduino/LabVIEW Peristaltic Pump Setpoint Flow or Waveform Σ Flow Rate RS-232 Signal Pump VI PID Loop ΔV Pressure Regulator 1 Error Voltage Pressure (Blood) Σ Σ Voltage Setpoint Pressure Pressure Regulator 2 Voltage Conversion VI ADC Pressure Transducer 2 Voltage Signal 2 Pressure (Dialysate)

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