29 LIMS & Lab Automation
Inevitably, such work is conducted in disparate locations, especially with most countries under lockdown, and with the benefi ts of remote operation coupled with ease of protocol sharing and method transfer can only heighten the probability of success for such vital systems-level investigations.
Andrew Alliance’s cloud-native OneLab ecosystem ensures rapid, intuitive and precise protocol creation, with ease of method transfer to other labs, minimising intra- or inter-lab variability. As a consequence of it being ‘cloud-native’, it also means that these protocols can be executed, and monitored, remotely. This is especially important during periods of lockdown where the majority of research staff are required to work remotely, often from a home offi ce.
This same scenario also demands both fl exibility for assay development, often requiring the ability to switch in/out different ontologies, coupled with full traceability.
Lab 4.0 and the concept of the ‘connected lab’ very much comes into its own here.
Wireless execution of these protocols on its increasing range of connected devices, enabling fully automated liquid handling (Andrew+), guided pipetting (Pipette+), shaking (Shaker+)m rapid heating/cooling (Peltier+), magnetic bead separation (Magnet+), or micro-elution for SPE (Vacuum+) defi nes not only the blueprint for the connected lab of the future but also the capability necessary to realise the demanding sample prep requirements of multi-omics data integration, and therefore, pathway-based translational research.
In the drug discovery process, early in vitro ADME screening and in vivo PK profi ling provide a basis for choosing new molecular entities (NMEs) and lead compounds that have desirable drug metabolism, PK or safety profi les, necessary for drug candidate selection (CS) and latestage preclinical and clinical development. The ADME properties of a drug allow the drug developer to understand the safety and effi cacy data required for regulatory approval.
Toxicology tests are often a part of this process, yielding the acronym ADMET.
Today, such studies are performed both in vitro and in vivo, and have led to more standardised procedures across the pharmaceutical industry.
There has been understandable concern over the ways in which animals have been used and treated as part of this process. As such, the principles of the 3Rs (Replacement, Reduction and Refi nement) were developed over 50 years ago providing a framework for performing more humane animal research. Since then they have been embedded in national and international legislation and regulations on the use of animals in scientifi c procedures, as well as in the policies of organisations that fund or conduct animal research. Opinion polls of public attitudes consistently show that support for animal research is conditional on the 3Rs being put into practice.
Replacement refers to technologies or approaches which directly replace or avoid the use of animals in experiments where they would otherwise have been used, for example the use of methods employing human embryonic stem cells as alternative ways of conducting ADMET studies. Refi nement refers to methods that minimise the pain, suffering, distress or lasting harm that may be experienced by research animals, and which improve their welfare. Refi nement applies to all aspects of animal use, from their housing and husbandry to the scientifi c procedures performed on them.
By contrast, reduction refers to methods that minimise the number of animals used per experiment or study consistent with the scientifi c aims. It is essential for reduction that studies with animals are appropriately designed and analysed to ensure robust and reproducible fi ndings.
Reduction also includes methods which allow the information gathered per animal in an experiment to be maximised in order to reduce the use of additional animals. Examples of this include the micro-sampling of blood, where small volumes enable repeat sampling in the same animal. In these scenarios, it is important to ensure that reducing the number of animals used is balanced against any additional suffering that might be caused by their repeated use. Sharing data and resources (e.g. animals, tissues and equipment) between research groups and organisations can also contribute to reduction.
Figure 2. Andrew+ offers fully automated pipetting, as well as more complex manipulations, using a wide range of Domino Accessories and Andrew Alliance electronic pipettes. It executes OneLab protocols, enabling rapid transition from laborious manual procedures to error-free, robotic workfl ows.
If we now divert our gaze across to those critical teams involved in identifying off pathway effects and toxiological endpiints for both pre-clinical and clinical trials, we run into the area of ‘systems toxicology’, essentially the application of pathway-based approaches to a fi led that ahs chnaged little in over a century.
“Not responding is a response - we are equally responsible for what we don’t do.” (Jonathan Safran Foer, 2011).
Life-saving therapeutics and vaccines undergo a sophisticated array of both in-vitro, and later in the drug development process, in-vivo testing. Different animal models are used, with the aid of establishing drug safety, as well as parameters of use in human beings.
DMPK, or Drug Metabolism and Pharmacokinetics, is an important part of studies often referred to as ADME (Absorption, Distribution, Metabolism, and Elimination):
• Absorption (how much and how fast, often referred to as the absorbed fraction or bioavailability)
• Distribution (where the drug is distributed, how fast and how extensive)
• Metabolism (how fast, what mechanism/route, what metabolite is formed, and whether they are
• active or toxic) • Elimination (how fast, which route).
Regarding ‘reduction’ much emphasis is placed on the importance of minimising the number of animals used in a study. Over the past several years, it’s become increasingly apparent that many lab studies, especially in the life sciences, are not reproducible. As a result, many putative drug targets or diagnostic biomarkers can’t be validated. Some estimates suggest that more than 50% of all published life sciences research is irreproducible, and some indicate that the fi gure might be even higher. The problem fl ew below the radar for years. A 2012 comment in Nature by C. Glenn Begley, a former vice president at Amgen, and Lee M. Ellis, an oncologist at the University of Texas M. D. Anderson Cancer Center, drew attention to the problem. They described Amgen scientists’ attempts to replicate the key fi ndings in 53 ‘landmark’ fundamental cancer studies that claimed to identify potential new drug targets. They were able to replicate the fi ndings in only 11% of the cases.
This ‘concern’ has not dissipated but has triggered a number of subsequent studies aimed at identifying the reasons for such has high levels of irreproducibility. There a number of causes, which vary from the deliberate falsifi cation of research, with increased pressure being brought to bear on the peer review process, to the tools we use in the laboratory and the ways in which those can contribute to erroneous data. These include, but are not limited to, the means by which powders (e.g. precision weighing scale) and liquids (e.g. pipettes) are handled, mixed and transferred; as well as the way in which one research group might interpret and repeat the work of another. This latter point might seem odd when considered alongside tools but bear in mind that the way in which the tools are used depends upon an accurate description and interpretation of the protocol used, an important area of research and development in its own right.
In order to respect the 3Rs, researchers must constantly strive to ensure that the latest techniques tools are fully used, taking full advantage of lab automation in order to minimise unnecessary replication and use of animal models.
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