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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. In 20 10 , 600,000 patients were treated for end stage renal disease (ESRD) in the US alone Treatment Options:

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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 • In 2010, 600,000 patients were treated for end stage renal disease (ESRD) in the US alone • Treatment Options: • Kidney transplant • Donor Shortage • Dialysis • Costly and time consuming 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 These membranes must be thoroughly tested to verify their filtration characteristics These experiments are manually monitored, and data is collected by hand Current experiments are unable to simulate physiologically relevant fluid flow profiles, and are limited to constant flow rates There are no failsafes to protect theseexpensive and fragile membranes

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

  6. Goals Develop an intuitive graphical user interface (GUI) that allows the user to easily control the system Automate the experimental protocol and data collection Allow user-defined hardware setup so that numerous experiments can be run simultaneously Add programatic flow rate control to allow for pulsatility Include failsafes and shutdown procedures to protect these membranes

  7. Clinical Relevance

  8. Experiments • The solution must automate three modes of experimentation • Hydraulic Permeability Mode • Measures filtration rate as a function of pressure (uL/min/psi) • Filtration Mode • Collect filtrate samples for further analysis • Dialysis Mode • Collect samples in a closed blood/dialysate system • Filtration and Dialysis Mode should include an option to run with constant flow or a pulsatile waveform

  9. Experimental Setup – Hydraulic Permeability Peristaltic Pump Implantable Device Pressure Transducer Air Filtration Membrane Air Regulator 0.000 0.010 0.020 0.015 0.005 g Zero Water PSI To House Air

  10. Feedback Control Diagram Voltage Signal Pressure Transducer ADC Arduino/LabVIEW Setpoint Flow or Waveform Flow Rate Peristaltic Pump RS-232 Signal Hagen-Poiseuille Pump VI ΔP V PID Loop V Error Voltage Pressure Regulator Setpoint Pressure Σ Σ Convert VI Pressure Pressure Setpoint Mass Yes/No Comparison VI (Actual > Setpoint?) Shutdown? Filtration Membrane Sample Mass Filtration Rate Mass Balance

  11. Pulsatility: Replicating Arterial Pressure Waveforms ex vivo Modified from Zhang, Guanqun, Jin-Oh Hahn, and Ramakrishna Mukkamala. "Tube-load model parameter estimation for monitoring arterial hemodynamics." Engineering Approaches to Study Cardiovascular Physiology: Modeling, Estimation, and Signal Processing (2011): 20.

  12. 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

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

  14. 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

  15. Experimental Runtime GUI Experiment Overview Pressure Transducer Transducer Calibration

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

  17. Hydraulic Permeability Experiment Load from File

  18. Hydraulic Permeability Results Experiment Results Data Log

  19. 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

  20. Recent Progress • LabVIEW Control of • Pressure transducer (COMPLETE) • Pressure Regulator (COMPLETE) • Peristaltic Pump (COMPLETE) • Mass balance (COMPLETE) • Syringe Pump (TBD) • Initial iterations of pulsatile flow • Abstract submission to American Society for Artificial Internal Organs (ASAIO) Student Design Competition • Fully Automated Hydraulic Permeability and Filtration Experiments • Primary Fail-safes and Error handling • Parts have arrived

  21. Next Steps • Revisit pulsatility using known pressure profiles • Evaluate syringe pump functionality/feasibility • Compile individual components into a single, unified system • Order and assemble box

  22. Gantt Chart

  23. 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. A.B. Bonds • Dr. Matthew Walker III • JustMyPACE Peer Senior Design Group

  24. Questions?

  25. 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)

  26. 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

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

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

  29. Previous System

  30. Previous Interface

  31. 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)

  32. 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)

  33. Top Level Menu

  34. Hardware Select

  35. Design 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

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