The 2020 SLAS Technology Top Ten: Translating Life Sciences Innovation

Fast and Label-Free Isolation of Circulating Tumor Cells from Blood: From a Research Microfluidic Platform to an Automated Fluidic Instrument, VTX-1 Liquid Biopsy System

Clementine A. Lemaire, Sean Z. Liu, Charles L. Wilkerson, Vishnu C. Ramani, Nasim A. Barzanian, Kuo-Wei Huang, James Che, Michael W. Chiu, Meghah Vuppalapaty, Adam M. Dimmick, Dino Di Carlo, Michael L. Kochersperger, Steve C. Crouse, Stefanie S. Jeffrey, Robert F. Englert, Stephan Hengstler, Corinne Renier, and Elodie Sollier-Christen

Tumor tissue biopsies are invasive and costly, and they collect a limited cell population not completely reflective of patient cancer cell diversity. Circulating tumor cells (CTCs) can be isolated from a simple blood draw and may be representative of the diverse biology from multiple tumor sites. The VTX-1 Liquid Biopsy System was designed to automate the isolation of clinically relevant CTC populations, making the CTCs available for easy analysis. We present here the transition from a cutting-edge microfluidic innovation in the lab to a commercial, automated system for isolating CTCs directly from whole blood. As the technology evolved into a commercial system, flexible polydimethylsiloxane microfluidic chips were replaced by rigid poly(methyl methacrylate) chips for a 2.2-fold increase in cell recovery. Automating the fluidic processing with the VTX-1 further improved cancer cell recovery by nearly 1.4-fold, with a 2.8-fold decrease in contaminating white blood cells and overall improved reproducibility. Two isolation protocols were optimized that favor either the cancer cell recovery (up to 71.6% recovery) or sample purity (≤100 white blood cells/mL). The VTX-1’s performance was further tested with three different spiked breast or lung cancer cell lines, with 69.0% to 79.5% cell recovery. Finally, several cancer research applications are presented using the commercial VTX-1 system.

Emerging Microtechnologies and Automated Systems for Rapid Bacterial Identification and Antibiotic Susceptibility Testing

Yiyan Li, Xing Yang, and Weian Zhao

Rapid bacterial identification (ID) and antibiotic susceptibility testing (AST) are in great demand due to the rise of drug-resistant bacteria. Conventional culture-based AST methods suffer from a long turnaround time. By necessity, physicians often have to treat patients empirically with antibiotics, which has led to an inappropriate use of antibiotics, an elevated mortality rate and healthcare costs, and antibiotic resistance. Recent advances in miniaturization and automation provide promising solutions for rapid bacterial ID/AST profiling, which will potentially make a significant impact on the clinical management of infectious diseases and antibiotic stewardship in the coming years. In this review, we summarize and analyze representative emerging micro- and nanotechnologies, as well as automated systems for bacterial ID/AST, including both phenotypic (e.g., microfluidic-based bacterial culture and digital imaging of single cells) and molecular (e.g., multiplex PCR, hybridization probes, nanoparticles, synthetic biology tools, mass spectrometry, and sequencing technologies) methods. We also discuss representative point-of-care (POC) systems that integrate sample processing, fluid handling, and detection for rapid bacterial ID/AST. Finally, we highlight major remaining challenges and discuss potential future endeavors toward improving clinical outcomes with rapid bacterial ID/AST technologies.

3D Culture as a Clinically Relevant Model for Personalized Medicine

Eliza Li Shan Fong, Tan Boon Toh, Hanry Yu, and Edward Kai-Hua Chow

Advances in understanding many of the fundamental mechanisms of cancer progression have led to the development of molecular targeted therapies. While molecular targeted therapeutics continue to improve the outcome for cancer patients, tumor heterogeneity among patients as well as intratumoral heterogeneity limit the efficacy of these drugs to specific patient subtypes and contribute to relapse. Thus, there is a need for a more personalized approach toward drug development and diagnosis that takes into account the diversity of cancer patients as well as the complex milieu of tumor cells within a single patient. 3D culture systems paired with patient-derived xenografts or patient-derived organoids may provide a more clinically relevant system to address issues presented by personalized or precision medical approaches. In this review, we cover the current methods available for applying 3D culture systems toward personalized cancer research and drug development, as well as key challenges that must be addressed to fully realize the potential of 3D patient-derived culture systems for cancer drug development. Greater implementation of 3D patient-derived culture systems in the cancer research field should accelerate the development of truly personalized medical therapies for cancer patients.

High-Throughput 3D Tumor Spheroid Screening Method for Cancer Drug Discovery Using Celigo Image Cytometry

Sarah Kessel, Scott Cribbes, Olivier Déry, Dmitry Kuksin, Eric Sincoff, Jean Qiu, and Leo Li-Ying Chan

Oncologists have investigated the effects of protein or chemical-based compounds on cancer cells to identify potential drug candidates. Traditionally, the growth-inhibitory and cytotoxic effects of the drugs are first measured in two-dimensional (2D) in vitro models, and then further tested in 3D xenograft in vivo models. Although the drug candidates can demonstrate promising inhibitory or cytotoxicity results in a 2D environment, similar effects may not be observed under a 3D environment. In this work, we developed an image-based high-throughput screening method for 3D tumor spheroids using the Celigo image cytometer. First, optimal seeding density for tumor spheroid formation was determined by investigating the cell seeding density of U87MG, a human glioblastoma cell line. Next, the dose–response effects of 17-AAG with respect to spheroid size and viability were measured to determine the IC₅₀ value. Finally, the developed high-throughput method was used to measure the dose response of four drugs (17-AAG, paclitaxel, TMZ, and doxorubicin) with respect to the spheroid size and viability. Each experiment was performed simultaneously in the 2D model for comparison. This detection method allowed for a more efficient process to identify highly qualified drug candidates, which may reduce the overall time required to bring a drug to clinical trial.

A Novel Microplate 3D Bioprinting Platform for the Engineering of Muscle and Tendon Tissues

Sandra Laternser, Hansjoerg Keller, Olivier Leupin, Martin Rausch, Ursula Graf-Hausner, and Markus Rimann

2D cell cultures do not reflect the in vivo situation, and thus it is important to develop predictive 3D in vitro models with enhanced reliability and robustness for drug-screening applications. Treatments against muscle-related diseases are becoming more prominent due to the growth of the aging population worldwide. In this study, we describe a novel drug-screening platform with automated production of 3D musculoskeletal-tendon-like tissues. With 3D bioprinting, alternating layers of photo-polymerized gelatin–methacryloyl-based bioink and cell suspension tissue models were produced in a dumbbell shape onto novel postholder cell culture inserts in 24-well plates. Monocultures of human primary skeletal muscle cells and rat tenocytes were printed around and between the posts. The cells showed high viability in culture and good tissue differentiation, based on marker gene and protein expressions. Different printing patterns of bioink and cells were explored, and calcium signaling with Fluo4-loaded cells while electrically stimulated was shown. Finally, controlled co-printing of tenocytes and myoblasts around and between the posts, respectively, was demonstrated, followed by co-culture and co-differentiation. This screening platform combining 3D bioprinting with a novel microplate represents a promising tool to address musculoskeletal diseases.

Heart-on-a-Chip: An Investigation of the Influence of Static and Perfusion Conditions on Cardiac (H9C2) Cell Proliferation, Morphology, and Alignment

Anna Kobuszewska, Ewelina Tomecka, Kamil Zukowski, Elzbieta Jastrzebska, Michal Chudy, Artur Dybko, Philippe Renaud, and Zbigniew Brzozka

Lab-on-a-chip systems are increasingly used as tools for cultures and investigation of cardiac cells. In this article, we present how the geometry of microsystems and microenvironmental conditions (static and perfusion) influence the proliferation, morphology, and alignment of cardiac cells (rat cardiomyoblasts—H9C2). In addition, studies of cell growth after incubation with verapamil hydrochloride were performed. For this purpose, poly(dimethylsiloxane) (PDMS)–glass microfluidic systems with three different geometries of microchambers (a circular chamber, a longitudinal channel, and three parallel microchannels separated by two rows of micropillars) were prepared. It was found that static conditions did not enhance the growth of H9C2 cells in the microsystems. In contrast, perfusion conditions had an influence on the division, morphology, and arrangement of the cells. The highest number of cells, their parallel orientation, and their elongated morphology were obtained in the longitudinal microchannel. It showed that this kind of microsystem can be used to understand processes in heart tissue in detail and to test newly developed compounds applied in the treatment of cardiac diseases.

Theranostic Nanoparticles for Tracking and Monitoring Disease State

Cristina Zavaleta, Dean Ho, and Eun Ji Chung

The development of novel nanoparticles consisting of both diagnostic and therapeutic components has increased during the past decade. These “theranostic” nanoparticles have been tailored toward one or more types of imaging modalities and have been developed for optical imaging, magnetic resonance imaging, ultrasound, computed tomography, and nuclear imaging comprising both single-photon computed tomography and positron emission tomography. In this review, we focus on state-of-the-art theranostic nanoparticles that are capable of both delivering therapy and self-reporting/tracking disease through imaging. We discuss challenges and the opportunity to rapidly adjust treatment for individualized medicine.

Digital Assays Part I: Partitioning Statistics and Digital PCR

Amar S. Basu

A digital assay is one in which the sample is partitioned into many small containers such that each partition contains a discrete number of biological entities (0, 1, 2, 3, . . .). A powerful technique in the biologist’s toolkit, digital assays bring a new level of precision in quantifying nucleic acids, measuring proteins and their enzymatic activity, and probing single-cell genotypes and phenotypes. Part I of this review begins with the benefits and Poisson statistics of partitioning, including sources of error. The remainder focuses on digital PCR (dPCR) for quantification of nucleic acids. We discuss five commercial instruments that partition samples into physically isolated chambers (cdPCR) or droplet emulsions (ddPCR). We compare the strengths of dPCR (absolute quantitation, precision, and ability to detect rare or mutant targets) with those of its predecessor, quantitative real-time PCR (dynamic range, larger sample volumes, and throughput). Lastly, we describe several promising applications of dPCR, including copy number variation, quantitation of circulating tumor DNA and viral load, RNA/miRNA quantitation with reverse transcription dPCR, and library preparation for next-generation sequencing. This review is intended to give a broad perspective to scientists interested in adopting digital assays into their workflows. Part II focuses on digital protein and cell assays.

A Combined Use of Intravoxel Incoherent Motion MRI Parameters Can Differentiate Early-Stage Hepatitis B Fibrotic Livers from Healthy Livers

Yì Xiáng J. Wáng, Min Deng, Yáo T. Li, Hua Huang, Jason Chi Shun Leung, Weitian Chen, and Pu-Xuan Lu

This study investigated a combined use of intravoxel incoherent motion (IVIM) parameters—Dslow (D), PF (f), and Dfast (D*)—for liver fibrosis evaluation. Sixteen healthy volunteers (F0) and 33 hepatitis B patients (stage F1 = 15; stages F2–F4 = 18) were included. With a 1.5 T magnetic resonance (MR) scanner and respiration gating, IVIM diffusion-weighted imaging was acquired using a single-shot echo-planar imaging sequence with 10 b values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm². Signal measurement was performed on right liver parenchyma. With a 3D tool, Dslow, PF, and Dfast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate healthy volunteers from patients. The 3D tool demonstrated that healthy volunteers and all patients with liver fibrosis could be separated. Classification and regression tree showed that a combination of PF (PF < 12.55%), Dslow (Dslow < 1.152 × 10⁻³ mm²/s), and Dfast (Dfast < 13.36 × 10⁻³ mm²/s) could differentiate healthy subjects and all fibrotic livers (F1–F4) with an area under the curve of logistic regression (AUC) of 0.986. The AUC for differentiation of healthy livers versus F2–F4 livers was 1. PF offered the best diagnostic value, followed by Dslow; however, all three parameters of PF, Dslow, and Dfast contributed to liver fibrosis detection.

Optimizing Combination Therapy for Acute Lymphoblastic Leukemia Using a Phenotypic Personalized Medicine Digital Health Platform: Retrospective Optimization Individualizes Patient Regimens to Maximize Efficacy and Safety

Dong-Keun Lee, Vivian Y. Chang, Theodore Kee, Chih-Ming Ho, and Dean Ho

Acute lymphoblastic leukemia (ALL) is a blood cancer that is characterized by the overproduction of lymphoblasts in the bone marrow. Treatment for pediatric ALL typically uses combination chemotherapy in phases, including a prolonged maintenance phase with oral methotrexate and 6-mercaptopurine, which often require dose adjustment to balance side effects and efficacy. A major challenge confronting combination therapy for virtually every disease indication, however, is the inability to pinpoint drug doses that are optimized for each patient, and the ability to adaptively and continuously optimize these doses to address comorbidities and other patient-specific physiological changes. To address this challenge, we developed a powerful digital health technology platform based on phenotypic personalized medicine (PPM). PPM identifies patient-specific maps that parabolically correlate drug inputs with phenotypic outputs. In a disease mechanism–independent fashion, we individualized drug ratios and dosages for two pediatric patients with standard-risk ALL in this study via PPM-mediated retrospective optimization. PPM optimization demonstrated that dynamically adjusted dosing of combination chemotherapy could enhance treatment outcomes while also substantially reducing the amount of chemotherapy administered. This may lead to more effective maintenance therapy, with the potential for shortening duration and reducing the risk of serious side effects.

In addition, SLAS would like to recognize the following top articles during the past 10 years, reflecting the most highly cited articles from both SLAS Technology and Journal of Laboratory Automation: