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Anushree Mitra
Anushree Mitra

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How Does AI & ML Improve Vaccine Development & Rollout Process?

The exciting world of groundbreaking scientific advancements has already embraced different futuristic technologies, and AI/ML is no exception. The new-age researchers have tapped into the incredible potential of Artificial Intelligence (AI) and Machine Learning (ML) to introduce vaccine development into an entirely new era. This dynamic combo of this state-of-the-art technology and the science of immunity offers the exciting prospect of transforming how we find, create, and distribute vaccines.

Thanks to AI's knack for spotting patterns and ML's ability to extract valuable insights from data, scientists are speeding up the process of pinpointing the best vaccine ingredients, making clinical trials more efficient, and even tailoring immunization plans for individuals. Focusing on the pivotal role of AI/ML in vaccine development and rollout here.

Contribute of AI/ML in Vaccine Development

Identifies the Specific Target

Diseases are not the same, and so are the vaccines. To get the most effective results from them it is important to get an understanding of how our immune system reacts to it. And ML can identify it flawlessly by analyzing big sets of data to find the parts of the virus that are likely to trigger our immune system. Once we know these parts, scientists can design vaccines that match them.

But, we have to be careful when choosing these parts. We don't want them to be similar to our own body's proteins because that could lead to problems. So, we need to make sure the vaccine targets are unique to the virus.
One way AI identifies that unique need is it identifying the protein sequences of the vaccine. For instance, in the fight against COVID-19, scientists are using AI to find parts that both T-cells and B-cells in our immune system can recognize. They found 17 potential vaccine parts that work with both these types of immune cells.
Another type of vaccine involves using a piece of the virus's genetic code (RNA or DNA) to stimulate our immune system. Since viruses can change over time, the vaccine's genetic code must be stable. AI helps by analyzing large datasets of the virus's genetic information to find the stable parts that can be used in these vaccines.

Proper Antigen Selection

In the vaccine development landscape, selecting the suitable antigen plays a key role in triggering a strong immune response while avoiding harm. AI and ML algorithms have revolutionized this process.

These cutting-edge technologies dive into vast pools of genetic data, protein structures, and immunological insights. By sifting through this wealth of information, they excel in foreseeing potential antigens with remarkable precision, surpassing traditional methods.
This data-centric approach accelerates the antigen selection process and increases the chances of uncovering antigens capable of eliciting powerful and precisely targeted immune reactions. AI and ML are fast-tracking the early phases of vaccine development, simplifying the quest for the most promising antigen candidates.

Preclinical Testing and Trials

AI is important in advancing both preclinical testing and clinical trials for vaccines. Let's break down how it contributes to each phase:

Preclinical testing aims to assess a vaccine's safety and effectiveness before human trials. Traditionally, this step involves animal models, but in recent years, regulatory bodies have focused on trying out alternative approaches. AI steps in as one of these alternatives by using ML algorithms to predict the toxicity of compounds.

While AI doesn't entirely replace preclinical testing, it greatly aids in several ways. It assists in determining the right dosage, forecasting certain immune responses, and even selecting the most appropriate animal models.

Clinical trials, though not made virtual by AI, benefit substantially from its involvement. Artificial intelligence analyzes data from preclinical tests and predicts how the human immune system will react.

Besides, AI algorithms also assist researchers in pinpointing optimal trial locations. For example, the MIT School of Engineering devised an ML-powered COVID-19 model that offers real-time insights into the pandemic.
It captures data on people's behaviors and health statuses, predicts governmental responses, and even forecasts when and where COVID outbreaks might occur. This data-driven tool identifies ideal locations for clinical trials, not only across 120 countries but also within all 50 US states.

Tailored Vaccine Strategies

With the help of AI/ML, creating customized vaccine strategies gets super-easy. These futuristic technologies enabled the researchers to create personalized vaccine strategies, based on specific genetic profiles and immunological histories.
They also work on identifying the individual’s genetic susceptibility to specific diseases and their past immune responses to them, AI designs vaccines considering those facts, offering enhanced protection and minimizing probable and adverse side effects effectively.

Helps in Drug Discovery

AI and ML perform great when it comes to discovering the necessary drugs specifically finding boosters for vaccines called adjuvants. Instead of slogging through tedious experiment processes, AI-powered algorithms have the capacity to delve into the extensive libraries of chemicals to figure out which ones could supercharge vaccines. They speed up the hunt for adjuvants that make vaccines work better by ramping up the immune system's response.

Roles Played by AI/ML in the Vaccination Rollout Process

The effectiveness of AI/ML has expanded its wings going beyond vaccine development. Besides, it also has shown effectiveness in the rolling out process. Know about this role from the following lines.

Prioritizing the Vulnerable People

Vaccination campaigns are supposed to identify the most vulnerable population first, specifically during pandemics, and AI can make this happen with ease. During the COVID-19 pandemic, hospitals succeeded in giving priority to the most vulnerable ones ( for instance- people who are above 65) using these technologies.

Also, during that time of crisis, Sanford Health, a healthcare organization based in South Dakota, put AI to work in identifying those most at risk of experiencing severe COVID-19 outcomes. They utilized an algorithm to analyze their patients aged 65 and above, generating a prioritized list considering the several health factors like obesity, kidney issues, heart problems, diabetes, and more.

Resolved Issues Like Vaccine Hesitancy

Rapid spreading of wrong information regarding any vaccine is an issue the healthcare sector often faces, and here also, AI/ML came as a rescuer. Advanced AI-powered chatbots offer much-needed counseling and give relevant answers to sensitive queries related to vaccination. A recent study based in France even said that bots are capable enough to create a positive feeling about vaccination among people.

Supply Chain Management

AI-powered predictive models manage vaccine supply chains by forecasting demand, monitoring inventory levels, and predicting potential disruptions. This fact ensures a steady and timely supply of vaccines to vaccination sites, preventing bottlenecks in the distribution process.

Wrapping Up

Despite the great analytical power, AI/ML often fails to address the effectiveness of any vaccine in our body. Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence pointed out this fact rightly, focusing on the complex nature of the body. Hence, you may say that these next-gen technologies might go hand-in-hand with the traditional vaccine development and clinical trial proceedings. And there is almost no possibility of fully automating the vaccination process.

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