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Digital Transformation AI Dominates Today’s Research Labs

From Ahlam Rais |

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Laboratories across the globe are making use of smart technologies such as Artificial Intelligence (AI)—in line with the ‘Industry 4.0’ concept—due to its numerous advantages as well as to keep up with today’s changing and demanding market requirements. One of the most crucial aspects of the AI technology for laboratories is its ability to analyze large sets of data and also recommend the best possible solutions for developing innovative and at times revolutionary products.

When AI is applied to chemical and pharmaceutical laboratories, it creates innovative and quality products or solutions in a much shorter period of time as compared to the more traditional methods.
When AI is applied to chemical and pharmaceutical laboratories, it creates innovative and quality products or solutions in a much shorter period of time as compared to the more traditional methods.

Artificial Intelligence can be considered as the champion in the lab space. Be it the chemicals or pharmaceuticals industry, most of the industrial segments are already impressed by this so called ‘next-gen’ technology. So, what’s so special and unique about this technology that is transforming laboratories like never before? Let’s find out.

What is AI?


Artificial Intelligence is all about smart machines or systems that are capable of carrying out tasks which are usually done by human intelligence. There is another subsection under the umbrella of AI i.e. Machine Learning (ML) which helps software applications automatically learn by making use of historical data and algorithms. This process enables the system to improve from experience based on the data fed into it, detect patterns, spot trends and also predict outcomes with high accuracy.

When this technology is applied to chemical and pharmaceutical laboratories, it creates innovative and quality products or solutions in a much shorter period of time as compared to the more traditional methods which may even take years to achieve. This shows us the importance of data and is also the reason why companies have started to collect and preserve more and more of their data. Thus, industry leaders are correct in terming ‘data’ as the new oil as it’s only data that will help companies to think and develop solutions that have never been executed earlier.

Examples from the industry

For instance, during the recent global pandemic, pharma manufacturers were rushing to find a cure for Covid-19 by pooling all their available resources together. The pharmaceutical major Pfizer in partnership with Biontech developed the Pfizer-Biontech Covid-19 vaccine in record time. Artificial intelligence along with machine learning played a vital role in this project as researchers were able to fast-track the development of the life-saving vaccine.

Pfizer is also making use of AI along with digital technology to enable dynamic and remote monitoring of human behaviors to develop meaningful novel quantitative digital endpoints. “AI and machine learning allow us to collect data from wearables and compare against ground truth in order for us to develop algorithms to quantify behaviors like walking, standing from sitting or stair climbing. This allows us to innovate based on key questions emerging from assets in the portfolio and our desire to develop novel, patient centric endpoints that can be measured continuously in the home environment,” states the company.

The company is also leveraging this technology for patients suffering from nonalcoholic steatohepatitis (NASH), a serious form of liver disease that is not associated with alcohol abuse. “Currently, the only way to diagnose NASH is through a liver biopsy, which can be painful. At Pfizer, we are in the process of devising a digital upgrade, leveraging 3D imaging techniques that send sound waves through the body, which helps to estimate key drivers of the disease, including liver stiffness and inflammation,” adds the firm.

In 2019, the Switzerland-based company Novartis established the ‘Novartis AI innovation lab’ and collaborated with tech giant Microsoft for AI. The company’s aim behind this: to completely change and accelerate the process of discovering as well as developing breakthrough medicines. Machine Learning can scan through huge experiment data sets of the past and also analyze them to recommend the best available options for the development of innovative medicines, thus, saving time and money. Overall, this specialized lab makes use of AI to overcome numerous computational challenges such as generative chemistry, image segmentation & analysis for smart and personalized delivery of therapies, and optimization of cell and gene therapies at scale.

In the chemical industry, Dow is constantly working towards developing new catalysts, polymers, and formulations with the help of AI, ML and many other smart technologies. Creating novel polyurethane formulations in a shorter period of time and at the same time reducing the R&D team’s experiments by analyzing previous data sets and results with AI has convinced the firm to use this expert technology across its product, process, and application development. The company also intends to automate its lab workflows so that researchers can focus on more productive operations such as executing the suggestions made by the smart AI system.

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With the above examples, it is clear that Artificial Intelligence along with Machine Learning has gone on to achieve many successes and is truly a boon for laboratories not just with respect to data analysis but it also has the ability to automate workflows, ensure quality checks and validate results. In conclusion, this technology may be explored even further for diverse applications but for now it’s doing more than enough.