SLAS Technology unveils AI-powered diagnostics & future lab tech

Oak Brook, IL – Volume 33 of SLAS Technology, includes one literature highlights column, eight original research articles and four Special Issue (SI) features.

Literature Highlights

• Literature highlights column: From the literature life sciences discovery and technology highlights
  SLAS Technology Section Editors Jamien Lim, PhD (TDK Electronics, Inc.) and Tal Murthy, PhD (Strain LLC) review noteworthy research articles pertaining to advances in biotechnology, artificial intelligence in science and advances in nanotechnology.

Original Research

• Enhanced high-throughput embryonic photomotor response assays in zebrafish using a multi-camera array microscope
  This study validates the Kestrel™ imaging platform—a 24-camera system capturing 10+ Hz, 9.6 µm-resolution video across 96-well plates—to overcome limitations in zebrafish-based drug/toxicology screening.
• Multi-model machine learning framework for lung cancer risk prediction: A comparative analysis of nine classifiers with hybrid and ensemble approaches using behavioral and hematological parameters
  This study evaluates 9 ML algorithms on 2,000 patient records to predict lung cancer risk from 34 demographic, behavioral and hematologic factors. Ensemble methods and regularization techniques proved most robust, enabling integration into EHR systems for early risk stratification.
• PRIMDEx: Prototyping rapid innovation of microfluidics devices for experimentation
  The authors present PRIMDEx, an innovative hybrid manufacturing workflow combining 3D printing and rapid injection molding to address the cost, time, and flexibility limitations of traditional microfluidic device fabrication. By integrating both methods, PRIMDEx enables faster, cheaper and more adaptable prototyping, ideal for iterative R&D cycles in biotechnology and biomedical research.
• Magnetic nanoparticles-based targeted drug delivery system in tumor pain management
  This research developed a green-synthesized, pH-responsive transdermal system (catHEC·FA@SPIO) that delivers targeted analgesia via magnetic nanoparticles to nasopharyngeal carcinoma patients. The system demonstrated superior pain relief, reduced anxiety/depression, and minimal cytotoxicity compared to conventional analgesia, with 94% patient satisfaction.
• Explainable clinical diagnosis through unexploited yet optimized fine-tuned ConvNeXt Models for accurate monkeypox disease classification
  This study leverages fine-tuned ConvNeXt models with Adafactor optimization to achieve 99.9% accuracy and 94% accuracy in monkeypox classification, outperforming traditional conventional neural networks while reducing computational costs.
• Titanium surface functionalization with calcium-doped ZnO nanoparticles for hard tissue implant applications
  This study focuses on the development of calcium phosphate-based coatings enhanced with Ca-doped ZnO nanoparticles on titanium implants, demonstrating strong antibacterial activity against Staphylococcus aureus biofilms while promoting tissue integration. The dense, defect-free coatings offer a cost-effective solution to reduce implant failures, which currently incur USD 30,000–100,000 per infection case.
• Construction and validation of a nomogram model for predicting rebleeding in high-risk peptic ulcer bleeding patients based on lasso regression: A single center retrospective research
  The authors developed a Lasso regression-based Nomogram to predict rebleeding in high-risk PUB patients, identifying six key predictors: diastolic BP, hematocrit, blood transfusion volume, GBS score, endoscopic findings and mechanical hemostasis.
• Sample preparation using multiple microbial pattern recognition proteins and magnetic bead ratcheting
  This study demonstrates a semi-automated, flow-through platform using paramagnetic beads to isolate 18 bacteria and viruses from diverse samples in less than 30 minutes at low concentrations. The system enables downstream PCR analysis, addressing critical bottlenecks in infectious disease diagnostics.

Special Issues

• High-throughput mass spectrometry in drug discovery
  This SI features innovative research on high-throughput mass spectrometry technologies that overcome traditional LC-MS bottlenecks, enabling ultrafast, label-free screening for hit identification, covalent drug discovery and compound library validation.
• Bio-inspired computing and Machine learning analytics for a future-oriented mental well-being
  The SI proposes bio-inspired computing and machine learning analytics for mental well-being in the field of life sciences innovation. Featured research reinforces the goal of revolutionizing the delivery of biological services through a medical assistive environment and facilitating the independent living of patients.
• NexusXp: The Connected Lab
  SLAS Technology explores the Lab of the Future with the SI “NexusXp: The Connected Lab” in the field of lab automation. Research articles within this edition aim to explore cutting-edge advancements, innovative technologies and visionary concepts shaping the future of laboratories.
• Biomedical Imaging: New Frontiers in Molecular and Cellular Visualization
  This SI highlights emerging solutions, such as integrating AI and quantum imaging, which promise to enhance resolution, sensitivity and data processing capabilities significantly—bringing together contributions that showcase the transformative advancements in biomedical imaging technologies reshaping clinical practice and biomedical research.

 

This issue of SLAS Technology is available at https://www.slas-technology.org/issue/S2472-6303(25)X0004-2

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SLAS Technology reveals how scientists adapt technological advancements for life sciences exploration and experimentation in biomedical research and development. The journal emphasizes scientific and technical advances that enable and improve:

• Life sciences research and development
• Drug delivery
• Diagnostics
• Biomedical and molecular imaging
• Personalized and precision medicine

SLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.

SLAS Technology: Translating Life Sciences Innovation, 2024 Impact Factor 3.7. Editor-in-Chief Edward Kai-Hua Chow, PhD, KYAN Technologies, Los Angeles, CA (USA).

 

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