Today’s laboratories have come far along in terms of technology and advancement of research approaches. With the integration of various technologies, such as robotics, machine learning (ML), artificial intelligence (AI), and automation, the research procedure has been revolutionized, which in turn has transformed manual testing processes into automated handling systems.

Microfluidics and lab-on-a-chip technologies, based on the concept of AI, made the adoption of paperless workflows, influencing procedure efficiency, reproducibility, data collection, analysis and sharing, and cloud computing easy with instrumental factors in the transformation of the laboratory.

This article will outline the advancement of AI in laboratory informatics.

What is laboratory informatics?

A specially designed application that enhances scientific processes comprises a variety of technology tools specialized in its own data collection and analysis strategies to enable the storage and delivery of information in laboratories termed laboratory informatics.

In order to fulfill quality standards, eliminate transcribing mistakes, shorten the test result time, and improve patient outcomes, laboratory informatics plays an essential role in laboratories.

Laboratory informatics has enabled end customers to prompt suppliers to design more appealing, practical, and feasible laboratory products, with a significant increase in the usage of such products. These advancements led various technologies to enter the laboratory informatics market to meet the growing needs and dependence on laboratory data to support clinical and public health demands.

Increased efficiency of laboratories due to their usage and better data management is among the major growth factor in the global laboratory informatics market.

As per a report by BIS Research, the global laboratory informatics market was valued at $4.34 billion in 2021 and is anticipated to reach $12.67 billion by 2032, witnessing a CAGR of 10.27% during the forecast period 2022-2032.

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What is the role of AI in laboratory informatics?

Artificial intelligence (AI) has become one of the most challenging terms to understand because of its increasing application across numerous arrays of varied approaches. AI is employed in laboratory testing to accelerate data-driven processes affecting the testing process to receive accurate results without any human errors.

AI has been a part of laboratories for a while. Various sectors have proven to be benefited from AI, including scientific research, data analysis, medical diagnosis, and process automation. Working robots based on AI technology are built apparently to think like humans and encounter accelerating laboratory testing in healthcare and several other sectors like finance.

Moreover, with the wide use of technological advancements, AI labs are considered to be the lab of the future.

Applications of AI in Laboratory Informatics

AI enables machines to persuade powers such as thinking and decision-making like humans. AI provides endless virtual possibilities in laboratory informatics by improving efficiency and extending the capabilities of laboratory tools.

Some applications of AI in laboratory informatics are as follows:

Medical Laboratories: Medicinal science has always relied on artificially intelligent systems such as algorithms that can identify health problems based on patients’ lab samples and compare them to thousands of other databases in the AI.

These AI-based advanced laboratory systems used in pathology to assist in diagnosis are able to test hundreds of samples each day with accurate results reducing the possibility of medical errors.

Pharmaceutical Laboratories: Pharma companies have been using AI technology for years to improve the drug manufacturing process. AI helps in assisting the development of new drugs by collecting and analyzing clinical data during tests, thus reducing the time people have to spend on it. With the acceleration provided by AI systems in drug development, it has the potential to transform the whole pharma industry and the method of drug development.

Environmental Testing: AI-based testing methods are used in the process of detection of water pollutants and air quality. These methods analyze animal blood drank by mosquitoes and aim to identify harmful pathogens before the potentially dangerous strain of a virus can spread.

Additionally, AI holds the potential to process hundreds of soil samples to check the soil quality and find out any harmful chemicals in it, benefiting the environment.

Chemical Laboratories: AI robots can convert organic and inorganic chemical synthesis procedures into simple instructions and store them in a precise format that is accessible only to chemists. Chemical assessments such as molecule design, toxicity tests, environmental impact research, and many more in chemical laboratories are mostly based on AI system algorithms that give accurate results and information on the molecular properties of specimens.

Conclusion

With the rapid growth in the advancement of various technologies in the field of laboratory testing, more and more processes can be automated. AI-based laboratory procedures have made laboratories work more efficiently, conducting quicker research and providing faster results.

The global laboratory informatics market is well-established, and with the continuous increase in the demand for data management systems and laboratory efficiency, it is expected to grow further.

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