Newswise — Oak Brook, IL – The December edition of SLAS Technology is a Special Collection entitled, “Assay Guidance Manual for Drug Discovery: Technologies that Matter” by Guest Editors Sarine Markossian, Ph.D., G. Sitta Sittampalam, Ph.D., Jayme L. Dahlin, M.D., Ph.D., (National Center for Advancing Translational Sciences, NIH, Bethesda, MD, USA) and Nathan P. Coussens, Ph.D. (Frederick National Laboratory for Cancer Research, Frederick, MD, USA).

This SLAS Technology Special Collection serves as a complimentary issue to the December special issue of SLAS Discovery. Both journal issues highlight the Assay Guidance Workshop for High-Throughput Screening and Lead Discovery series conducted by the National Center for Advancing Translational Sciences (NCATS) Assay Guidance Manual (AGM) program.

This special collection of SLAS Technology contains the research article by Gonzales et al which provides recommended best practices in compound management and handling for researchers performing biological assays. The authors emphasize the importance of a close collaboration and an open dialogue between screening and sample handling groups for successful drug discovery campaigns. Other articles in this collection describe emerging technologies related to high-throughput screening (HTS) and lead optimization.

An original research article by Elder et al was contributed by NCATS scientists in collaboration with an industrial partner, Kebotix, and is focused on remote-controlled autonomous bioassay optimization using Bayesian statistical approaches. Morato et al describes new applications of desorption electrospray ionization (DESI) mass spectrometry (MS) for high-throughput synthetic chemistry, chemical reaction screening, and label-free biological assays amenable to HTS. These two articles highlight major areas of technological development such as optimization using machine learning as well as the power of evolving mass spectrometry methodologies to advance both chemistry and biological applications.

This issue of SLAS Technology also includes five articles of original research:

  • Optimization of Automated Sample Preparation for Vitamin D Determination on a Biomek i7 Workstation
  • Traceability Methods for Cell Line Authentication and Mycoplasma Detection
  • Summit: Automated Analysis of Arrayed Single-Cell Gel Electrophoresis
  • Optimal Scheduling for Laboratory Automation of Life Science Experiments with Time Constraints
  • Enhanced Drug Permeation into Human Keloid Tissues by Sonophoresis-Assisted Micro-needling


Other articles in this issue include:

  • Assay Guidance Manual for Drug Discovery: Technologies That Matter
  • Automated High-Throughput System Combining Small-Scale Synthesis with Bioassays and Reaction Screening
  • Busting Myths in Compound Handling Practices for Assay Developers
  • Cross-Platform Bayesian Optimization System for Autonomous Biological Assay Development
  • Coprocytobiology: A Technical Review of Cytological Colorectal Cancer Screening in Fecal Samples
  • Higher Tumor Mutation Burden Was a Predictor for Better Outcome for NSCLC Patients Treated with PD-1 Antibodies: A Systematic Review and Meta-analysis
  • Diffuse Reflectance Parameters of Treated Leishmaniasis Cutaneous Ulcers and Association with Histopathologies in an Animal Model: A Proof of Concept
  • Life Sciences Discovery and Technology Highlights


Access to this issue of SLAS Technology is available at 

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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 Discovery: Advancing the Science of Drug Discovery, 2019 Impact Factor 2.918. Editor-in-Chief Robert M. Campbell, Ph.D., Twentyeight-Seven Therapeutics, Boston, MA (USA)

SLAS Technology: Translating Life Sciences Innovation, 2019 Impact Factor 3.047. Editor-in-Chief Edward Kai-Hua Chow, Ph.D., National University of Singapore (Singapore).




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