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Time-to-market is critical to the success of many businesses. High throughput
technologies are laboratory methods that streamline the process of taking
a new product from discovery through to production. They are used in the
life sciences, chemical and manufacturing sectors, where they enable business
to screen, and experiment with, compounds and formulations for use in
healthcare products, household cleaning products, agrochemicals, paints
etc. The key components of high throughput technology are miniaturization,
automation and parallelization.
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High Throughput Screening (HTS)
solves the problem of how to screen thousands
of compounds for desirable pharmaceutical behaviour against a given target
by automating the assaying process.
The success of high throughput screening is built on advances in the batch
handling capability of laboratory instruments, and also in the development
of software to automate laboratory processes. HTS arose in the life sciences
sector, but is now also used the chemicals industry.
High Throughput Experimentation (HTE)
solves problems such as how to find
the best combination of dozens of smoothing agents, fillers, thickeners,
emollients and perfumes to make a good shampoo. HTE gives scientists a
more intelligent way of designing multiple experiments. It both replaces
and complements traditional research practices by incorporating advances
in data modelling, experimental design, automation and data management
into a single cohesive system.
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Generic HTE workflow
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High throughout techniques require integration of IT infrastructure and
automated laboratory equipment, and demand the support of scientists,
engineers, statisticians and modellers. There is a wide range of solutions,
from spreadsheet macros to full-blown LIMS/SCADA systems that are scaleable
and reliable but require commitment and capital.
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Virtual screening is a data-intensive technique that uses models, developed
from previous empirical data or from a theoretical standpoint, to screen
compounds from a database. This type of ‘thought experiment’
is an economical way of carrying out initial trials.
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Data management is an important part of the HTS/HTE approach. Large volumes
of data are produced that must be managed effectively. There may be regulatory
requirements dictating which data must be stored and for how long, and
there may be a need to share locally held data with a wider global audience.
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Tessella’s reference model for HTE deployment is designed to simplify
management by providing objective measures of the processes’ performance,
arming managers and technologists with insights into where HTE will provide
the most value. Read more about THERM™ here.
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Use the following icons to access further information: |
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| High Throughput Screening |
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| High Throughput Experimentation |
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For reasons of commercial confidentiality, we are not able
to reveal details of a significant proportion of our projects.
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