# An integrated acoustofluidic droplet-sorting platform for classification of lymphocyte activity and functional phenotyping at single cell level

> **NIH NIH R01** · NORTHEASTERN UNIVERSITY · 2020 · $268,302

## Abstract

Abstract
 The outcome of many pathological diseases such as infection and cancer is determined by the interaction
of diseased cells with various immune cell subsets, both of which are phenotypically and functionally diverse.
Induced resistance to chemo- and immuno-therapeutic drugs remain one of the main challenges in modern
medicine. Moreover, there exists significant inter-patient and even intra-patient variability in response to well-
established drug regimens, making it difficult to predict a patient's response to applied treatments. Single-cell
analysis techniques have great potential in revealing, and ultimately utilizing, patient-specific cellular
information to devise a more personalized approach to therapeutic regimens. Thus, developing a rapid
screening system for assessing target-immune cell interactions, which are modulated by immunogenic
treatments, will allow clinicians to predict the patient's response to a treatment, streamline treatment protocols
and improve the efficacy of immunotherapeutic strategies in patient-specific manner. Here, we propose to
develop an integrated microfluidic droplet based platform that permits quantitative analysis of the efficiency of
immune reactions (responsive vs. non-responsive and fast vs. slow kinetics) and subsequent sorting and
recovery of functionally distinct subsets for molecular (transcriptomic) characterization. We propose to
integrate large-scale droplet microfluidic arrays with dual acoustofluidic sorters that achieve a level of
throughput (>18,000 events/sec) and controllability (four-channel sorting) that no microfluidic droplet sorter has
been able to achieve. Collectively, the sorters and the droplet docking arrays will allow for selection,
enrichment and visualization of droplets of interest containing effector immune and target cells at different cell
ratios, thereby allowing dynamic analysis of cell-cell interaction to identify predictive phenotypic classifiers. The
sorted cells will then be analyzed by global transcriptomic profiling and unbiased systems biology approaches
to identify the correlation between key molecular signatures and functional heterogeneity. This multifunctional
analytical platform will further enable screening and validation of targeted therapies at single-cell level by
sequentially exposing the encapsulated effector/target cells to first and second generation drugs via an
integrated droplet merging junction. This approach will greatly enhance the identification of drug candidates
prior to therapeutic administration to assist in disease - and patient-specific treatment decisions. We will
validate our platform by functionally classifying lymphoma-Natural Killer (NK) cell interaction in the presence of
approved anti-CD20 immunotherapy to (1) determine optimal immune activity required to achieve highly
effective response to anti-CD20 immunotherapy; and (2) obtain critical insights into the development of
resistance to anti-CD20 therapy in cancer. We envision thi...

## Key facts

- **NIH application ID:** 9918430
- **Project number:** 5R01GM127714-03
- **Recipient organization:** NORTHEASTERN UNIVERSITY
- **Principal Investigator:** Tania Tali Konry
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $268,302
- **Award type:** 5
- **Project period:** 2018-08-10 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9918430

## Citation

> US National Institutes of Health, RePORTER application 9918430, An integrated acoustofluidic droplet-sorting platform for classification of lymphocyte activity and functional phenotyping at single cell level (5R01GM127714-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9918430. Licensed CC0.

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