Issues

Browse our previous issues below, or browse and search for specific features or analysis & opinion.

All our articles, news, product announcements and more are available from the navigation at the top of the site (accessible via the menu button for smartphone or tablet).

Access is free when subscribed and logged in.

Fattening up FEA

Gemma Church discusses advances to FEA software as it is now used to simulate a wide range of physical phenomena

Regulating scientific discovery

Sophia Ktori explores the use of informatics software in the first of two articles covering the use of laboratory informatics software in regulated industries

HPC maintenance

Robert Roe explores the role of maintenance in ensuring HPC systems run at optimal performance

Twenty years of the OpenMP API

Michael Klemm, CEO, and Matthijs van Waveren, marketing coordinator for the OpenMP ARB, along with Jim Cownie, principal engineer, Intel Corporation (UK), consider the development of OpenMP over the last 20 years

Electronics everywhere

Gemma Church explains the background behind explosive growth in the simulation and modelling of low- and high-frequency electronics

Cool runnings

With innovation in cooling technology increasingly more important to ensure energy, performance and cost efficiency of HPC, Keely Portway speaks to experts to find out what is driving the latest innovations

The smart laboratory

This chapter discusses what we mean by a ‘smart laboratory’ and its role in an integrated business. We also look at the development of computerised laboratory data and information management; the relationships between laboratory instruments and automation (data acquisition); laboratory informatics systems (information management); and higher-level enterprise systems and how they align with knowledge management initiatives.

Information: Laboratory informatics tools

This chapter will look at the four major laboratory informatics tools – laboratory information management systems (LIMS), electronic laboratory notebooks (ELNs), laboratory execution systems (LES) and scientific data management systems (SDMS) – their differences and how they relate to each other. Each of these systems functions at or around the ‘Information’ layer (see Figure 1) and typically serves to collate data and information about the laboratory’s operations

Beyond the laboratory

This chapter considers who cares about how smart the laboratory is, and why? It also looks at the broader business requirements and their impact on the laboratory, with an emphasis on productivity and business efficiency, integration with manufacturing and business systems, patent evidence creation, regulatory compliance, and data integrity and authenticity

Practical considerations: Specifying and building the smart laboratory

This chapter looks at how to build a smart laboratory; what approaches to take; and how to deal with potential problems. Inevitably, becoming ‘smart’ takes time, not only due to the level of investment required, but also because of the impact of change and the need to consider legacy requirements.

Summary

In this guide we have attempted to coalesce much of the information required in order to design and implement as smart laboratory or, at the very least, to begin the process of laboratory automation. While it may seem like a challenging prospect, the underlying principles are simple and focused on crafting a strategy that will enable more productivity and insight to be generated from scientific research

References

Source references from throughout Building a Smart Laboratory 2018

Dealing with data

Informatics experts share their experiences on the implementing new technologies and manging change in the modern laboratory

Data: Instrumentation

This chapter will consider the different classes of instruments and computerised instrument systems to be found in laboratories and the role they play in computerised experiments and sample processing – and the steady progress towards all-electronic laboratories.

Knowledge: Document management

This chapter considers how the smart laboratory contributes to the requirements of a knowledge eco-system, and the practical consequences of joined-up science. Knowledge management describes the processes that bring people and information together to address the acquisition, processing, storage, use, and re-use of knowledge to develop understanding and to create value

Knowledge: Data analytics

This chapter takes the theme of knowledge management beyond document handling into the analysis and mining of data. Technology by itself is not enough – laboratory staff need to understand the output from the data analysis tools – and so data analytics must be considered holistically, starting with the design of the experiment

Ensuring data integrity

Darren Barrington-Light, senior manager product marketing for Thermo Fisher Scientific, explains the importance of integrating LIMS into the pharmaceutical data chain

Paperless Lab Academy 2018

This year the Paperless Lab Academy (#PLA2018) conference will move to a new location overlooking Lake Maggiore on the southern side of the Alps, near Milan, Italy. The central theme will focus on how to ‘Empower your eData Life Cycle.’

Synergy between man and machine

The failure of a candidate drug can cost millions – so many chemists are turning to software that provides modelling capabilities and multi-parameter optimisation

The future of laboratory informatics

Robert Roe interviews laboratory informatics software providers who discuss potentially disruptive technologies and their impact on the laboratory informatics market

Drowning in data?

David Wang gives his view on how modern laboratories can leverage data to provide maximum value

An artificial future

Elsevier’s Jabe Wilson predicts radical changes in the ways AI will be used in scholarly communications

Racing ahead

Gemma Church finds out how electric vehicles can make performance and user experience improvements

The Path to Exascale

Robert Roe reports on the potentially far-reaching benefits of exascale computing for European research

Simulate and innovate

Robert Roe reports from the European Altair Technology Conference and finds that simulation-driven design is taking centre stage for the CAE industry.

HPC unearths glacial flow

Robert Roe looks at research from the University of Alaska that is using HPC to change the way we look at the movement of ice sheets

Deep learning dominates ISC

At ISC High Performance 2017, held in Frankfurt, Germany, deep learning is driving new computing innovation as the HPC industry sets its sights on AI hardware and applications

Storage ambitions

Robert Roe finds that commoditisation of flash and SSD technology and the uptake of machine learning and AI applications are driving new paradigms in storage technology.

Accelerating demand

Robert Roe reviews the latest in accelerator technology and finds that GPUs and coprocessors will be key fixtures in the future of deep learning

Whatever the weather

Gemma Church explores the use of modelling and simulation to predict weather and climate patterns

Predicting the future of the laboratory

The first in series of articles covering the Paperless Lab Academy conference – in this article Robert Roe looks at the importance of adopting digital technologies - the benefits and pitfalls that laboratories face when on the road to digital convergence.

Pages