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Translating biophysics to reduced healthcare costs

By Henry T.K. Tse, Dino Di Carlo, Daniel R. Gossett

A new platform, using microfluidic techniques to measure biophysical and mechanical changes in cells may provide healthcare savings. The platform is able to detect malignant cells with a high degree of confidence.

Current paradigms of medical care have been deemed unsustainable. In part, this is due to a traditional focus on a one-size-fits-all therapeutics approach rather than personalized approaches in disease screening and treatment monitoring. As such, the healthcare system incurs unnecessary costs of ineffective therapeutics, compounded costs due to delay in providing effective treatments, and costs in treating therapeutic related side-effects – which contributes to the 18% of the US GDP currently spent on healthcare (highest in the world) which is projected to balloon to 34% of GDP by 2040. Only recently, companion diagnostics are being more widely employed to predict an individual’s response to a treatment, reducing unnecessary and toxic treatments and improving patient outcomes. Many of the companion tests, while effective, are based on complex molecular biology assays often ranging between $1,000-$5,000 per test. Currently, the majority of the assay costs are associated with sample preparation and readouts requiring specialist interpretation. One promising approach to bringing down the cost of these personalized assays is to make use of easily evaluated physical biomarkers requiring fewer reagents, labels, and steps.

New technologies, like diagnostics based on label-free physical biomarkers, promise to bring down costs but only when applied strategically. Cutting-edge biomedical technologies should be simple, requiring little if any additional logistical infrastructure, and scalable. In diagnostics, technologies should strive for requiring few steps, automation, and robustness outside of the research lab, in addition to high sensitivity and specificity. Lacking any of these key attributes will spell failure either in development, evaluation, or in clinical adoption. For example, a highly sensitive but poorly specific biomarker seeds suspicion for disease, eliciting costly and invasive follow-ups, hospital stays, and patient discomfort. Other times, powerful biomarkers based on molecular species perform poorly in clinical settings due to difficulty robustly repeating complex sample preparation procedures. Technologies measuring molecular biomarkers also require rigid calibration and quality control to prevent error due to batch differences in affinity. And, these biomarkers can change with time and disease treatment.

In addition to molecular biomarkers, biophysical biomarkers have been classically employed for diagnostics and screening. For example, blood analyzers or flow cytometers are employed in blood panels, discriminating populations of cells by their optical scattering properties or electrical impedance, which are independent from molecular affinity and do not require as much sample preparation to obtain. Further, clinical cytology has used visual inspection of cells to diagnose malignancy in biopsies and biological fluids (note, this does require staining and sample preparation), but this method is often ill-equipped to deal with the complexity of biological specimens, often suffering from low sensitivity in samples which are either dilute or contain large backgrounds of other cells, respectively.

In recent decades, biologists have increasingly connected physical properties of cells (size, shape, mass, electrical properties, and mechanical properties) with biological processes (e.g., differentiation, motility, invasiveness). There is extensive work underway in multiple fields to make use of this knowledge to develop physical biomarkers for cell state and disease. Potentially, these label-free biomarkers can have significant contributions in biomedicine such as cancer diagnostics, regenerative medicine therapeutics, and other high-impact application areas are outlined in Figure 1. However, in order to be useful clinically and take advantage of the key aspects of physical biomarkers, technologies for measuring them must meet the same high standards that are applied to molecular diagnostics: robust practice in a clinical setting, low assay complexity, quantitative readouts, high accuracy, and high-throughput.

Figure 1: Translational applications of biophysical markers of cell state
Figure 1: Translational applications of biophysical markers of cell state, adapted from [1].

At UCLA we have developed a high-throughput single-cell platform to measure biophysical and mechanical changes of cells. The platform – Deformability Cytometry – utilizes microfluidic techniques to position cells in flow and delivers these cells to impact uniformly on a fluid wall, where cells deform and measurements of intrinsic mechanical properties are recorded (Figure 2). This platform overcomes many hurdles that biophysical techniques have seen, such as high-throughput requirements (>1,000 cells/sec), complex heterogeneous samples, sample preparation requirements, and end-user requirements. This platform has enabled the exploration of both biological and clinical applications of mechanical biomarkers including in monitoring stem cell differentiation and screening for cancer. We have previously shown that the throughput of our platform enables high accuracy cellular identification within a defined problem regime. For example, in highly heterogeneous pleural fluids containing many subpopulations of leukocytes, benign mesothelial cells, and malignant cancer cells, the deformability cytometry platform is able to diagnose malignant effusions with 91% sensitivity and 86% specificity (Figure 3). The high confidence in a diagnosis based on this rapid, label-free, and straightforward microfluidic assay will improve clinical decision making: reducing costly and invasive follow-ups and accelerating the application of useful therapeutics. With a broad range of diseases which have been connected with biophysical changes, this method may ultimately provide systemic healthcare savings in the near future.

Figure 2: Deformability cytometry platform to measure mechanical properties of cells.
Figure 2: A) Top: Photograph of microfluidic device (scale bar 2 cm) with inset showing channel design (scale bar 200 µm, the red region highlights deformation junction shown in the bottom figure. Bottom: Extensional flow pattern stretches and deforms cells as they impact the fluidic wall. B) Time-lapse high-speed microscopy images of a cell from its initial relaxed state entering the junction, and impacting the opposing fluidic wall within a period of 28 µs. Scale bar 50 µm. Figure is adapted from [2].

Click to enlarge

Figure 3: Patient pleural effusion analysis by deformability cytometry.
Figure 3: Patient pleural effusion analysis by deformability cytometry. Notably, malignant specimens contains characteristically larger and highly deformable cells as compared to the negative specimen. Deformability biomarker is also sensitive to acute and chronic leukocyte activation.

For Further Reading

1. D. Di Carlo, “A mechanical biomarker of cell state in medicine,” J Lab Autom, vol. 17, no. 1, pp. 32 – 42, Feb. 2012.

2. D. R. Gossett, H. T. K. Tse, S. A. Lee, Y. Ying, A. G. Lindgren, O. O. Yang, J. Rao, A. T. Clark, and D. Di Carlo, “Hydrodynamic stretching of single cells for large population mechanical phenotyping,” Proc. Natl. Acad. Sci. U.S.A., vol. 109, no. 20, pp. 7630-7635, May 2012.

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December 2012 Contributors

Nitish V. ThakorNitish V. Thakor is a Professor of Biomedical Engineering at Johns Hopkins University, Baltimore, USA, as well as the Director of the newly formed institute for neurotechnology, SiNAPSE, at the National University of Singapore. Read more

Ali KhademhosseiniAli Khademhosseini, MASc, Ph.D., is an Associate Professor at Harvard-MIT's Division of Health Sciences and Technology (HST), Brigham and Women's Hospital... Read more

Rashid BashirRashid Bashir he is the Abel Bliss Professor of Electrical and Computer Engineering & Bioengineering, Director of the Micro and NanoTechnology Laboratory... Read more

Michelle KhineMichelle Khine is Associate Professor, Biomedical Engineering; and Associate Professor (Joint Appointment), Chemical Engineering and Materials Science, at the University of California, Irvine. Read more

Dr. Russell F. RossDr. Russell F. Ross is the Director of Product and Technology Development at Kimberly-Clark Corporation, leading the development of biomaterials for drug delivery and therapeutic applications. Read more

Dr. Tejal DesaiDr. Tejal Desai is currently Professor of Bioengineering and Therapeutic Sciences at the University of California, San Francisco. Read more

Henry T.K. TseHenry T.K. Tse is a postdoctoral fellow at UCLA where he had also received his Ph.D. in Biomedical Engineering in 2012 under the guidance of Dino Di Carlo. Read more

Dino Di CarloDino Di Carlo is an Associate Professor of Bioengineering at UCLA. He received his B.S. and Ph.D. from UC Berkeley in 2002 and 2006 respectively... Read more

Daniel GossettDaniel Gossett received his Ph.D. from the Biomedical Engineering Interdepartmental Program at the University of California, Los Angeles in the Spring of 2012... Read more