Volume 26 Issue 1, February 2021 Dave Pechter discusses the February SLAS Technology Special Collection AI in Process Automation with Guest Editor Cenk Undey (Amgen), which includes the following papers: Artificial Intelligence Effecting a Paradigm Shift in Drug Development by Masturah Bte Mohd Abdul Rashid Artificial Intelligence (AI) to the Rescue: Deploying Machine Learning to Bridge the Biorelevance Gap in Antioxidant Assaysby Sunday Olakunle Idowu and Amos Akintayo Fatokun Deep Learning and Computer Vision Strategies for Automated Gene Editing with a Single-Cell Electroporation Platform by Cesar Patino, Prithvijit Mukherjee, Vincent Lemaitre, et al. 

SAGE Life & Biomedical Sciences

SLAS Technology Author Talk Tech: Special Collection: AI in Process Automation

SLAS Discovery 25.10 December 2020Rob Howes discusses the paper "High-Throughput Screening for Drugs That Inhibit Papain-Like Protease in SARS-CoV-2" with authors Meredith Gardner (Scripps Research) and Michael Farzan (Scripps Research). This research is part of the December Special Issue, Drug Discovery Targeting COVID-19 with Associate Editor Tim Spicer.

SLAS Discovery Author Insights: High-Throughput Screening for Drugs That Inhibit Papain-Like Protease in SARS-CoV-2

SLAS Technology Author Talk Tech

Volume 25 Issue 5, June 2020 Dave Pechter discusses with Varun Bhaskar Kothamachu, Ph.D. (Head of Product, Digi.Bio) & Sabrina Zaini (Head of Operations, Digi.Bio) their featured research article, "Role of Digital Microfluidics in Enabling Access to Laboratory Automation and Making Biology Programmable."

SLAS Technology Authors Talk Tech: Role of Digital Microfluidics in Enabling Access to Laboratory Automation and Making Biology Programmable

SLAS Technology 25.4 August 2020 Dave Pechter discusses with Christian Heiss & Parastoo Azadi regarding the SLAS Technology Special Issue: Carbohydrate Structure Analysis: Methods and Applications.

SLAS Technology Authors Talk Tech: Special Issue: Carbohydrate Structure Analysis: Methods and Applications

Volume 25 Issue 6, July 2020 Podcast Editor Rob Howes discusses the SLAS Discovery 2020 July Special Issue with Guest Editors Davide Gianni and Stuart Farrow. This Special Issue of SLAS Discovery presents the topic “Functional Genomics for Target Identification” and is focused on three strategic pillars that form the foundation of the functional genomics discipline. Articles span a variety of relevant topics, from the development of more translatable models of diseases to the creation of validated screening libraries, technologies and computational pipelines to perturb gene function and enable quantitative interpretation of screening outputs. 

SLAS Discovery Author Insights: Functional Genomics for Target Identification

Volume 25 Issue 5, June 2020 Podcast Editor Rob Howes discusses the SLAS Discovery 2020 June Special Collection with SLAS Discovery Editorial Board Member Joseph G. McGivern. To read the editorial by Joseph G. McGivern and Mei Ding, click here. This Special Collection of SLAS Discovery presents a special collection reflecting recent advances and continuing challenges in the development and application of assay technologies that are applicable to drug discovery for ion channel targets.

Special Collection: Ion Channels and Relevant Drug Screening Approaches

Two articles are discussed: Traceable Impedance-Based Dispensing and Cloning of Living Single Cells: Single-cell cloning is essential in stem cell biology, cancer research, and biotechnology. Regulatory agencies now require an indisputable proof of clonality that current technologies do not readily provide. Here, we report a one-step cloning method using an engineered pipet combined with an impedance-based sensing tip. This technology permits the efficient and traceable isolation of living cells, stem cells, and cancer stem cells that can be individually expanded in culture and transplanted. Impedance-Based Single-Cell Pipetting: Many biological methods are based on single-cell isolation. In single-cell line development, the gold standard involves the dilution of cells by means of a pipet. This process is time-consuming as it is repeated over several weeks to ensure clonality. Here, we report the modeling, designing, and testing of a disposable pipet tip integrating a cell sensor based on the Coulter principle. We investigate, test, and discuss the effects of design parameters on the sensor performances with an analytical model. We also describe a system that enables the dispensing of single cells using an instrumented pipet coupled with the sensing tip. Most importantly, this system allows the recording of an impedance trace to be used as proof of single-cell isolation. We assess the performances of the system with beads and cells. Finally, we show that the electrical detection has no effect on cell viability. Link to journal articles: Muller G.; Bonzon D.; Claudinot S.; et al. Traceable Impedance-Based Dispensing and Cloning of Living Single Cells    Bonzon D.; Muller G.; Bureau J.; et al. Impedance-Based Single-Cell Pipetting  Link to issue: http://journals.sagepub.com/toc/jlad/25/3

Traceable Impedance-Based Dispensing and Cloning of Living Single Cells and Impedance-Based Single-Cell Pipetting

Robert M. Campbell, Ph.D., is Senior Research Advisor at Eli Lilly and Company in Indianapolis, IN, where he heads the Cancer Cell Growth and Epigenetics Group. Dr. Campbell has served as Editor-in-Chief of SLAS Discovery for the past 12 years, where he has been a vital leader to grow the journal and share its important content. In this podcast, Dr. Campbell talks with our SLAS Discovery Podcast Editor Rob Howes, Ph.D. (AstraZeneca Gothenburg, Sweden) to discuss his work with the journal, as well as a little history about SLAS and the journal, and to make a call to authors and readers about upcoming content and his interest to work with listeners to publish and share their work. For more about Dr. Bob Campbell, read his ELN member profile article, Drum Roll Please! For more information about the journal, visit the SLAS Discovery website or contact Dr. Campbell directly at editorcampbell@slas.org.

Meet Editor-in-Chief Bob Campbell and SLAS Discovery!

The clinical team attending to a patient upon a diagnosis is faced with two main questions: what treatment, and at what dose? Clinical trials’ results provide the basis for guidance and support for official protocols that clinicians use to base their decisions upon. However, individuals rarely demonstrate the reported response from relevant clinical trials, often the average from a group representing a population or subpopulation. The decision complexity increases with combination treatments where drugs administered together can interact with each other, which is often the case. Additionally, the individual’s response to the treatment varies over time with the changes in his or her condition, whether via the indication or physiology. In practice, the drug and the dose selection depend greatly on the medical protocol of the healthcare provider and the medical team’s experience. As such, the results are inherently varied and often suboptimal. Big data approaches have emerged as an excellent decision-making support tool, but their application is limited by multiple challenges, the main one being the availability of sufficiently big datasets with good quality, representative information. An alternative approach—phenotypic personalized medicine (PPM)—finds an appropriate drug combination (quadratic phenotypic optimization platform [QPOP]) and an appropriate dosing strategy over time (CURATE.AI) based on small data collected exclusively from the treated individual. PPM-based approaches have demonstrated superior results over the current standard of care. The side effects are limited while the desired output is maximized, which directly translates into improving the length and quality of individuals’ lives. Link to journal article: https://journals.sagepub.com/doi/full/10.1177/2472630319890316 Link to issue: http://journals.sagepub.com/toc/jlad/25/2

CURATE.AI: Optimizing Personalized Medicine with Artificial Intelligence

Podcast Editor Rob Howes discusses the SLAS Discovery 2020 February Special Issue with Martin Main and Andrew Zhang. To read their article, click here. 

Special Issue: Advances in Cellular Target Engagement and Target Deconvolution

Over the last decade, flexible analytical devices have received considerable attention in both academia and industry. Compared to conventional analytical devices which are generally made from rigid materials, such as silicon, glass, and plastics, flexible devices offer several unique advantages, such as simplified fabrication, lower costs, enhanced portability and disposability, and compliance to curved or deforming surfaces. For these reasons, flexible analytical devices are well suited for many diagnostic applications, including wearable and in vivo sensing, and point-of-care testing for disease detection and health monitoring. This special issue showcases a comprehensive review and exciting original research on topics ranging from wearable sensors for human motion monitoring and disease diagnosis, flexible electrochemical sensor arrays for human cell culture monitoring, paper-based sensors and immunoassays for diagnostic testing, a paper-based biological solar cell for power generation and storage, and a 3D printing strategy for rapid prototyping of flexible microfluidic devices.  Link to journal articles: http://journals.sagepub.com/toc/jlad/25/1 

Special Issue: Flexible Analytical Devices for Point-of-Care Testing

Dave Pechter discusses with Chao Li the article, "Automated System for Small-Population Single-Particle Processing Enabled by Exclusive Liquid Repellency."

Automated System for Small-Population Single-Particle Processing Enabled by Exclusive Liquid Repellency

Professors at Johns Hopkins University, Claire Hur and Deok-Ho Kim, discuss their paper, "Engineering Innovations for Fundamental Biology and Translational Medicine".  

Engineering Innovations for Fundamental Biology and Translational Medicine

UCLA Professor, Dino Di Carlo, discusses his review paper, "Technologies for the Directed Evolution of Cell Therapies".  

Technologies for the Directed Evolution of Cell Therapies

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