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Lab automation assisting in drug research

4th June 2019


Advances in artificial intelligence and machine learning are a few examples of automation technology. Automation offers scientists and researchers the ability to carry out research at an unprecedented pace. Many time-consuming and laborious tasks are no longer a major concern in the development process thanks to automation. 

Research in any field can be a long process that takes years or decades to come to full fruition. Any method that can speed up the process is a major advantage. The time required for FDA approval is also significantly reduced. 

Automation technology is very cost-efficient and can save industries billions of dollars on labour jobs. In fact, the use of smart technology is expected to dramatically increase over the next decade. 

Drug development requires skills and talents from a variety of disciplines. While automation technology cannot replace the necessary talents, they can perform labour-intensive tasks in a fraction of the time. 

Automation reduces human error. 

Machines are programmed to operate within certain parameters. The highly defined constraints ensure that the machines perform their function correctly nearly every time with less room for error than a human possesses. Machines are also designed to be more durable and shorten certain stages in the development process. 

It is estimated that the drug industry can save millions of dollars from human error through automation. As machines become more advanced and more widely used, the cost of the necessary machines decreases. 

Automation allows scientists and researchers to make further strides. 

Scientists and researchers do not have to spend as much time manually collecting samples and inspecting data sets. Automated devices can sequence samples at a much faster rate. Scientists and researchers have more flexibility to work on different assignments in parallel. 

There are many cures and vaccines that are dependent on drug research. Increased efficiency can allow scientists to find the necessary cure sooner. 

Scientists can worry less about contamination of samples due to human error. Mistakes are inevitable. However, too many mistakes due to human error can set back or hurt any progress. 

Automated machines increase replicability. 

Automation reduces the number of variables that must be considered in an experiment, reducing error and ensuring that results are much more consistent and scientists can draw a stronger conclusion. This creates a new standard for scientists to adhere to. The research community must come together to discuss their ideas on what is acceptable research and the possibilities that automation provides for them.

Researchers can invest in various devices to complete a wide range of tasks. Sometimes, a combination of automation and a creative approach is necessary to acquire the desired results. 

As automation develops, drugs become more affordable and accessible. One of the main goals of the research is to expand upon an existing idea and make it more accessible. Scientists and researchers aim to contribute to society in many ways, specifically drugs that are meant to help fight against extremely painful or dangerous diseases.

Automation assists scientists and researchers in their goal to make the results of research more accessible to the public. Scientists are often faced with the problem of finding methods and materials that are cost-effective. Automation will help with both reaching the public and keeping the costs affordable to them.

Robotic systems and liquid handling workstations are a few examples of technology that is commonly used in drug research. Many of the devices can work in parallel and produce results that prove to be more cost-effective. 

Automation solves challenging problems in drug research. 

The cost of the labour force, miniaturisation and genomic initiatives are a few challenges that scientists must overcome. Automation solves many of the problems in drug research through high precision techniques and advanced algorithms. The development time for drug enhancements and the production of new drugs may be much shorter in the future.





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