Standard dead-end sample filtration is used to improve sample purity, but is limited as particle build-up fouls the filter, leading to reduced recovery. The fouling layer can be periodically cleared with backflush algorithms applied through a customized fluidic actuator using variable duty cycles, significantly improving particulate recovery percentage. We show a Pulse Width Modulation (PWM) process can periodically backflush the filter membrane to repeatedly interrupt cake formation and reintegrate the fouling layer into the sample, improving net permeate flux per unit volume of sample by partially restoring filter flux capacity. PWM flow for 2.19 um (targeted) and 7.32 um (untargeted) polystyrene microbeads produced 18-fold higher permeate concentration, higher recovery up to 68.5%, and an 8-fold enrichment increase, compared to a uniform flow. As the duty cycle approaches 50%, the recovery percentage monotonically increases after a critical threshold. Further, we developed and validated a mathematical model to determine that fast, small-volume backflush pulses near 50% duty cycle yield higher recovery by decreasing fouling associated with the cake layer. Optimized PWM flow was then used to purify custom particles for immune activation, achieving 3-fold higher recovery percentage and providing a new route to improve purification yields for diagnostic and cellular applications. Dead-end filtration using patterned microsieves, fiber meshwork, and membranes of various materials is a standard technique to isolate desired particles of various sizes and is often used in clinical and laboratory settings for therapeutic and diagnostic applications 1-4. Both biological and physical suspensions can be filtered to yield high purity and enrichment at a high throughput. Dead-end filters are especially susceptible to fouling, however, which leads to lower recovery percentage and yield as a direct result 2,5,6. Because a decreasing yield negatively impacts therapeutic quality 7-9 , clinical and industrial therapeutic manufacturing will frequently change or increase the surface area of the dead-end filter 10 , or switch to crossflow filtration modalities 11,12 , which further decreases the throughput and increases processing time. Membrane fouling is caused by pore blocking followed by cake layer formation, resulting in an exponential decay with time in the flux of permeating particulate 13-19. Membrane fouling also affects crossflow systems and, in this case, numerous studies were conducted to disrupt cake formation and reintegrate particulates into the bulk flow feed stream 11,12,20-25. For example, crossflow filtration can disrupt caking by implementing an oscillatory flow with a sinusoidal flow velocity or a pulsatile flow, consisting of a steady flow with oscillations superimposed 20. These studies examined the effects of numerous waveforms, including variations of sinusoids, saw tooth, and square waves 12,20,23. Oscillatory and pulsatile techniques showed improved clearance of the crossflow membranes, leading to an incre...
Diagnostics, drug delivery, and other biomedical industries rely on cross-linking ligands to microbead surfaces. Microbead functionalization requires multiple steps of liquid exchange, incubation, and mixing, which are laborious and time intensive. Although automated systems exist, they are expensive and cumbersome, limiting their routine use in biomedical laboratories. We present a small, bench-top robotic system that automates microparticle functionalization and streamlines sample preparation. The robot uses a programmable microcontroller to regulate liquid exchange, incubation, and mixing functions. Filters with a pore diameter smaller than the minimum bead diameter are used to prevent bead loss during liquid exchange. The robot uses three liquid reagents and processes up to 107 microbeads per batch. The effectiveness of microbead functionalization was compared with a manual covalent coupling process and evaluated via flow cytometry and fluorescent imaging. The mean percentages of successfully functionalized beads were 91% and 92% for the robot and manual methods, respectively, with less than 5% bead loss. Although the two methods share similar qualities, the automated approach required approximately 10 min of active labor, compared with 3 h for the manual approach. These results suggest that a low-cost, automated microbead functionalization system can streamline sample preparation with minimal operator intervention.
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