SLAS Technology Vol. 36 Explores the Future of Intelligent Laboratory Automation

Oak Brook, IL – Volume 36 of SLAS Technology includes two editorials, one literature highlight, two original research articles, two reviews and two Special Issue (SI) features.

Editorials

• Mass Spectrometry Applications for High-Throughput Experimentation in Supporting Drug Discovery
  High-throughput experimentation paired with mass spectrometry (MS) is accelerating drug discovery by enabling rapid, parallel analysis of thousands of chemical reactions and biological assays. While challenges such as data management and matrix effects remain, advances in MS technology, direct-to-biology workflows and AI integration are driving end-to-end optimization of the drug discovery process.
• 2^nd EUOS/SLAS Joint Challenge: Prediction of Spectral Properties of Compounds
  The Second Joint Machine Learning Challenge, built on the success of the first EU-OPENSCREEN/SLAS challenge, demonstrates how open, well-curated experimental datasets can accelerate the development of advanced machine learning methods for drug discovery. The editorial outlines the challenge–the full technical descriptions of the winning solutions will be published in SLAS Technology later this year.

Reviews

• Guide to Liquid Volume Measurements: A Review of Methods and Technologies
  This review surveys liquid volume measurement methods and technologies for life science laboratories, covering volumes from picoliters to milliliters across applications in biopharmaceutical and clinical settings. Key attributes evaluated include volume range, precision, accuracy, workflow integration and regulatory compliance.
• Toward Full Automation in Synthetic Biology: A Progressive Conceptual Framework Integrating Robotics and Intelligent Agents
  This article examines the role of robotics and AI in automating synthetic biology workflows, covering progress of physical and cognitive automation in synthetic biology. The authors propose a dual framework for both total automation of the full Design-Build-Test-Learn cycle and progressive automation that can be adapted to diverse laboratory contexts, while addressing the ethical considerations of increasingly autonomous biological research.

Original Research

• Implementation of a Modular Digital Laboratory Infrastructure for SiLA₂ Based Devices
  This article presents a laboratory digitalization framework using open-source software and hardware, demonstrated through a SiLA-based continuous chromatography system for Green Fluorescent Protein (GFP) purification. The framework includes device control, data management, evaluation, and maintenance strategies for software and hardware.
• Low-Cost CNC-Based Media Dispensing System for Biotechnology Laboratories
  A custom Computer Numerical Control-based Automated Media Dispensing System was developed and validated over two years for a plant biotechnology lab, outperforming manual dispensing while maintaining efficiency At approximately one-fiftieth the cost of comparable commercial systems, the modular design offers an accessible and ergonomic automation solution for research laboratories.

Literature Highlight

• Life Sciences and Aging
  This entry in the Life Sciences and Society series by SLAS Technology Associate Editor Kerstin Thurow, PhD, centers on advances in genomics, AI, and senolytic therapies that are giving life sciences increased power to intervene in the aging process, shifting the focus toward extending healthy lifespan rather than longevity alone.

Special Issues

• Robotics in Laboratory Automation
  This editorial introduces the Special Issue (SI) Robotics in Laboratory Automation, which highlights advances in robotic systems that improve experimental precision, reproducibility and throughput. The SI addresses key developments in standardization and intelligent automation while acknowledging current limitations and emerging trends shaping the field.
• Revolutionizing Transcriptomics from Single-Cell Insights to RNA-Based Interventions
  This SI on systems genetics examines gene and molecular interaction networks, utilizing high-throughput sequencing and multi-omics technologies to understand how genetic networks influence phenotypes. It emphasizes the significance of personalized medicine, therapeutic target discovery and biomarker identification through integrated genomic and epigenomic approaches.

All active SLAS Discovery and SLAS Technology call for papers are available at:

This volume of SLAS Technology is available at

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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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