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Role of AI in The Pharmaceutical Industry

Artificial Intelligence for Pharma

Pandemics and epidemics tend to bring the healthcare industry under the limelight, and the Covid-19 pandemic was no different. In addition to logistics and civic regulations, Pharma companies have taken centre-stage during the novel Coronavirus pandemic.

As a result, the pharmaceutical market has grown exponentially, and this is expected to continue in the years to come. Research indicates that the global pharmaceutical manufacturing market, valued at USD 405.52 billion in 2020, is expected to grow at a compound annual growth rate (CAGR) of 11.34% from 2021 through 2028.

Compounding the Covid-19 impact are factors like technological advancements, an increase in the number of elderly, focus on the healthcare needs of growing countries, a rise in chronic disorders, and higher spending by pharma companies on research and development.

Naturally, every player wants to make the most of the myriad opportunities present in the market. Consequently, competition among different pharmaceutical companies has been fierce. Numerous parameters are driving this intense competition within the sector:

If competition is going to be the bedrock of growth in the near future, then artificial intelligence will play a crucial role in determining which pharma brands stay ahead of the pack.

How AI is Helping Pharmaceutical Companies to Stay Competitive?

  1. Artificial Intelligence can improve the drug discovery process:

Pharma brands are leveraging the power of AI to aid the relatively expensive and competitive drug discovery process. AI solutions can successfully identify disease patterns in large datasets and help understand which drug compositions would be best suited for treating different diseases. For example, the MIT-industry consortium, ‘Machine Learning for Pharmaceutical Discovery and Synthesis‘, which comprises top pharmaceutical giants such as Bayer, Lilly, Novartis, Pfizer, etc., uses MIT’s robust machine learning solutions to improve the drug recovery process. This can:

More recently, GSK partnered with Vir Biotechnology to leverage artificial intelligence for identifying antiviral compounds that can treat coronaviruses, including Covid-19.

By embracing AI solutions, pharma companies are actively working on lowering R&D costs, preventing human errors, and accelerating the research timeline—leading to affordable-yet-profitable drugs.

  1. AI can help in the process of drug development and production by making it more effective:

Did you know that only 14% of all drugs in clinical trials win approval from the FDA, as per research by MIT? That is a poor outcome for clinical trials that can cost around $1 billion for each newly approved drug. This means the drug approval process can turn out to be a costly affair if the drug does not get approved. This is where AI can play an instrumental role in improving—and optimizing—the drug development process. Artificial intelligence tools can improve the success rate of new drugs by:

  1. AI can provide diagnostic assistance and empower physicians to deliver personalized treatment

At the heart of personalized treatment lies real-time patient data. AI-powered solutions and machine learning technology can empower healthcare brands to:

  1. Artificial Intelligence can help predict epidemic outbreaks

Machine learning models are being used to predict—and prevent—epidemics such as Malaria. According to a study conducted in Maharashtra, a data mining classification algorithm—Support Vector Machine (SVM)—was used to successfully predict the onset of malaria in the early stages with a lower error rate. This type of AI/ML tool can empower organizations to engage in early preventive care and put the right measures in place to combat it. Here’s how AI can assist in epidemic prevention:
Step 1: The AI/ML tools feed on real-time information that is gathered from disparate sources across the web.

Step 2: The predictive tool studies a multitude of environmental, biological, and other factors to make connections with previous epidemic outbreaks and provide relevant patterns, trends, and solutions.

Another excellent example of predictive forecasting is GlaxoSmithKline’s use of AI to promote its seasonal medicines in the Allergy Cold and Flu category. The brand leverages a predictive model that helps chart how the upcoming season for allergy or cold and flu will shape across varied geographical regions; including where it may peak and where it may lag. This empowers the brand to:

  1. AI can enable pharma companies to ‘sell and market’ better as well as smarter

Considering that the pharma industry is inherently sales-driven, pharma companies can leverage the power of Artificial Intelligence in driving a more targeted and personalized marketing campaign. AI tools can be used to:

AI tools can also be used to learn about in-store/online customer behavior. For instance, GlaxoSmithKline uses AI for tracking the eye movements of consumers and retailers (with their consent). The brand studies this data—collected using special eye-tracking glasses worn by shoppers in stores or online—in its dedicated shopper’s science lab, thus, enabling it to monitor how the end-user looks at the products. The AI-powered tool captures key images during the shopping process and provides analysis for Areas of Interest (AOI) metrics such as the time to first fixation, heatmaps, gaze plots, video replays, etc. This invaluable data can be used to engage in better product placement, improve the artwork and labeling of products, and discern consumer behavior from the inside out.

The writing is on the wall

It is the day and age of Artificial Intelligence. Almost no industry is untouched by AI, and the pharmaceutical industry is no different.

AI today finds application in nearly every aspect of the pharma product lifecycle. So naturally, the use of artificial intelligence in the pharma industry is not going to slow down any time soon. In fact, research suggests that 50% of global healthcare companies will actively execute AI strategies and adopt this futuristic technology by 2025.

This is hardly surprising as AI-powered solutions can bring down costs, enhance patient care, foster profitable innovation, and improve business outcomes across the value chain. Clearly, Artificial Intelligence is the future of pharma and the future is here.

 

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