The 2025 SLAS Innovation Award Finalists: A Celebration of Excellence in Laboratory Technology

S. Tori Ellison (NCATS): Developed a 3D bioprinted skin tissue model composed of fibroblasts and keratinocytes arranged in a multi-well plate to mimic the human dermis and epidermis. This innovative model accurately reproduces HSV infection pathways, distinguishing between injury-induced and bloodstream infections. Leveraging this scalable platform, over 700 antiviral compounds were screened for efficacy and cytotoxicity, uncovering variations in potency based on cell type and mechanism of action. This advancement surpasses traditional 2D assays in predicting drug responses.

[“A 3D Bioprinted Skin Assay Platform to Perform High-Throughput Screens and Identify Potent HSV Antivirals”]

Keisuke Goda (University of Tokyo): Introduced image-activated cell sorting (IACS), an AI-powered technology allowing for real-time imaging to sort live cells based on visual and functional traits.
IACS combines AI-driven imaging with real-time sorting to analyze cellular morphology and functions. Unlike traditional fluorescence sorting, it offers multi-dimensional analysis, enabling precise sorting of live cells. Its applications range from microbiology and immunology to cancer and food science, addressing cell population heterogeneity with unparalleled throughput and accuracy.

[“Intelligent Image-Activated Cell Sorting & Beyond”]

Sunghoon Kwon (Seoul National University): Explored AI-driven spatial technologies in oncology, using a “Smart Laser Gun” for spatial omics to identify biomarkers and bridge lab discoveries to real-world therapeutic applications.

[“AI-Driven ‘Smart Laser Gun’ for Spatial Omics”]

Nitin Joshi (Brigham and Women’s Hospital–Harvard Medical School): Developed BraiN-TNGS, a high-throughput in vivo screening method using DNA-barcoded nanoparticles to track and optimize formulations for targeted brain delivery. It addresses the blood-brain barrier and cell-specific delivery challenges, identifying nanoparticles with high brain accumulation and specificity. This approach reduces animal use while improving delivery efficiency for neurological therapies.

[“Unlocking Nano-Bio Interactions in the Brain for Precision Delivery of Gene Therapies”]

Justin Langerman (UCLA):Created Secretion Encoded single-Cell sequencing (SEC-seq), a method using hydrogel nanovials to capture single-cell transcriptomic data and secretions. SEC-seq identified a stromal cell population with high regenerative capacity and shed light on early cell-cell communication. This technique allows detailed study of secretory processes and early embryonic patterning events.

[“Utilizing Nanovials to Associate Secretions and Transcriptomes of Single Cells”]

Maria Bueno Alvez Lim (KTH Royal Institute of Technology): Conducted a pan-cancer study comparing 1,463 proteins from over 1,400 patients, identifying specific cancer biomarkers. Expanding to 59 diseases, this work created the Human Disease Blood Atlas, advancing precision diagnostics and biomarker discovery.  Remarkably, this method improves disease-specific marker discovery beyond conventional case-control studies.
[“Comprehensive Blood Proteome Profiling for Pan-Cancer and Pan-Disease Biomarker Discovery”]

Babak Mahjour (MIT): Designed an advanced cheminformatic workflow that leverages reaction templates to predict and validate multicomponent chemical reactions systematically. By combining a highly connected mechanistic network with robotics-assisted experimentation, this innovative approach enables the rapid discovery of novel reactions. Experimentally validated through robotic dosing and parallel reactions, it accelerates chemical space exploration while offering deeper insights into reaction kinetics and conditions.

[“Ideation and Evaluation of Novel Multicomponent Reactions via Mechanistic Network Analysis”]

Caitlin Mills (Harvard Medical School): Developed the Dye Drop microscopy assay, a high-throughput imaging method for non-disruptively staining and fixing cells in culture. This innovative approach collects single-cell phenotypic data and analyzed 67 small molecules across 58 breast cancer cell lines, linking drug responses to kinase inhibition. By advancing the understanding of kinase-targeted therapies in cancer and neurodegeneration, this method delivers cost-effective, high-resolution workflows for robust drug development.

[“Drug Response Phenotyping and Target Deconvolution Using Dye Drop Multiplexed Imaging”]

Taci Pereira (Systemic Bio): Tackled preclinical data challenges with h-VIOS™, an advanced bioprinted tissue platform. By integrating endothelialized vasculatures with organ-chips, it enables the generation of complex human-like tissue models. Applications include assessing drug-induced liver injury, vascular toxicity, and off-target cancer effects, providing scalable and highly human-relevant data for preclinical studies.

[“h-VIOS: A Human-Relevant Drug Discovery and Development Platform”]

Ritu Raman (MIT): Developed engineered neuromuscular tissues integrated with a patented flexure platform to accurately measure muscle strength, function, and fatigue. Leveraging linear elastic mechanisms, this platform enables high-throughput functional assays for drug screening, accelerating the discovery of effective therapies for neuromuscular diseases and mobility impairments.

[“Tissue Engineering High-Throughput Models of the Neuromuscular System”]