The increasing demand for speed-to-market requires that modern pharmaceutical laboratories work faster, more accurately and
efficiently than before. Unavoidably, this leads to a number of bottlenecks that threaten the overall laboratory operation
and efficiency.
The first step to be taken to address these issues is to look for instrumentation and software platforms that can automate
common laboratory processes. Automation often offers significant advantages, including:
- more efficient use of personnel
- decreased operating costs
- less human intervention (thus fewer laboratory errors)
- more rapid processing of samples
- greater accuracy and faster recording of results.
 Automation case study
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A significant number of procedures undertaken in pharmaceutical laboratories are less complex, but delicate, requiring extremely
careful handling while being highly repetitive. These procedures are suitable for automation, and many companies rightly opt
for bespoke technology, but only because the skills of humans can be truly imitated.
However, instruments can rarely multitask, which renders some actions more suitable for humans to perform. In some cases,
pharmaceutical laboratory processes often have high levels of variation, making the development of an automated, robust and
reliable process inherently difficult. This is further compounded with the high intrinsic value of the end product, making
it necessary for a laboratory to acknowledge and accommodate for a degree of risk during their sample management, R&D and
processes. It, therefore, seems that automation is not always the best solution for a laboratory to achieve optimum efficiency. Automation
will solve many of the efficiency and throughput issues in a modern pharma lab; however, it may not be suitable for overcoming
common workflow jams and bottlenecks in the overall process. Could the issues instead be resolved by critically reviewing
and changing the processes and methods of working?
Identifying the solution
Finding an appropriate solution that takes into account the pharmaceutical laboratory's future strategy can be a particularly
difficult and time-consuming process. The ownership of the problem can pass from person to person without the underlying issues
ever being resolved.
While universities teach scientists how to perform the various analytical tasks, scientists are infrequently taught how best
to address management issues such as workflow, efficiency and productivity. Furthermore, with scientists being occupied with
conducting the experiments and evaluating the results, it is very difficult and time consuming to step back and realize the
necessity to change a laboratory workflow or process to address efficiency issues. In most cases, change is initiated from
the bottom up, with the manager and staff placing pressure on the director.
 Key points
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Once the need for change has been identified, the most effective solution is to outsource the process analysis to a specialist
company. This removes the burden from the scientists and laboratory manager, and imports specialist external knowledge into
the company. The outsourced service provider can then impartially review the internal processes and decide whether automation
is the best approach to increase capacity in working methods by reducing common pinch points.
Where automation may not be the most viable solution to address workflow issues, specialists have started to use models from
the engineering and manufacturing industries.
To date, scientists have been reluctant to exploit these available process models. However, the laboratory industry can benefit
from employing the long-standing practices of productivity improvement and process automation employed by innovative process
engineering companies. Laboratory workflow can be improved by exploiting the available process models from the manufacturing
environment (for example, lean manufacturing or Kanban practices).
Broadly speaking, manufacturing and engineering processes involve following a logical step-by-step approach to set out a typical
workflow evaluation project.