Artificial Intelligence Infrastructure for Viral Vaccine Manufacturing

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This article was published as a part of the Data Science Blogathon.


Viruses are well-known etiological agents to cause a broad spectrum of diseases in humans, animals, and plants. In the last few decades, viral infections have emerged and have been responsible for life-threatening to humankind and the worldwide economy. As evident by historical records, vaccination has proven to be lifesaving for the world population against many viral diseases leading to disease eradication like smallpox and lowering the disease burden and mortality (COVID-19).

In the current scenario, the demand for viral vaccines is high. After that, the vaccine manufacturing industry has the fastest growing and leading company after considering the preventive measures, low disease burden, and mortality of human health worldwide.


Artificial Intelligence (AI) can have a transformative impact on viral vaccine manufacturing. There are many areas where viral vaccine manufacturing can leverage AI to enrich their processes, drive innovation and explore new business models. The current article may help start-ups and budding professionals by providing basic information about AI infrastructure requirements for viral vaccine manufacturing industries through questions and answers.

Virus and Viral Vaccine Manufacturing

A virus is an infectious microorganism that can only replicate inside the host organism and can infect through entry into plant and animal cells. Viruses can visualize through the electron microscope and have a simple structure. When a virus particle is independent of its host, it exists as a free particle known as a virion. The virions consist of a viral genome / genetic material within a protein shell called a capsid.

In some viruses, the protein shell is intact in an envelope. Classification of the virus is depending based on the diverse viral genome in nature (single- or double-stranded and linear or circular DNA or RNA), length of genetic material (nucleotide length of DNA or RNA), and number (nucleotide numbers of DNA or RNA) of the molecules.

Due to the requirement of Good Manufacturing Practices (GMP) approved manufacturing facility, Good Laboratory Practices (GLP) approved quality testing facility, dedicated equipment, skilled man-powers, and utility services, manufacturing and testing of the viral vaccine is a costly affair. It is also time-demanding from starting to end quality vaccine.

Artificial Intelligence and Its Levels

The vaccine industries are now leveraging Artificial Intelligence and Machine Learning techniques to develop and program autonomous robots that handle important agricultural tasks like harvesting crops much faster than humans. The definition of AI has changed. Previously, even a simple function like a calculator to perform calculations would demand an AI component. Now, it’s just computer software with various tiers of AI work. Predominantly, we can categorize the AI systems into three levels, as presented in table 1.

Table 1: Different Level of AI System

S. No. AI Level Description of the Level
1 Artificial Narrow
This is also known as weak or narrow AI because it’s
goal-oriented and designed to perform low-level simple tasks. Technologies such
as Siri, Alexa, etc., fall under this category. It’s carried out through machine
learning which specializes in only a particular area and solves that particular
2 Artificial General Intelligence Also
referred to as deep or strong AI, where machines can mimic human
intelligence. A few of its properties include recognition, hypothesis
testing, analogy, etc. Speech and facial recognition systems generally
fall under this category. However, this category is still under heavy
research and is not been completely developed yet.
3 Artificial Super
It is just a vague concept. It’s supposed to
develop in the coming future. It should be able to create and formulate its own
emotions and do tasks more efficiently than humans in fields such as
calculations, sports, art, etc.

Potential of Artificial Intelligence in Biotechnology Industries

Based on the available literature, Artificial Intelligence (AI) has already proven its potential application in different categories of the biotechnology industry, as given in table 2.

Table 2: Use of AI in different categories of the biotechnology industry

Category Artificial Intelligence used
1 Agriculture biotechnology To develop and program autonomous robots that handle important agricultural tasks like harvesting crops at a much faster pace than humans.
2 Medical biotechnology – Extensively used in drug discovery.
– Proving to be promising, including enhancing the EHRs with evidence-based medicines and clinical decision support systems.
– Widely used in gene editing, radiology, personalized medicine, medication management, etc.
3 Animal Biotechnology – Breeding of animals.
– Genetic characteristics among the animals are selected for breeding
4 Industrial biotechnology – To analyze the machines, predict outages, optimize equipment, etc, to provide efficient production and better product quality.
– To design desired drug molecule
5 Bioinformatics biotechnology Leveraging DNA sequencing from the huge data crunch involved, classification of protein along with protein’s catalytic role and biological function, analysis of gene expressions, genome annotation where a certain level of automation is required to identify the locations of genes, computer-aided drug design, etc.
6 Vaccine technology – To
design and develop a bacterial and viral vaccine

Tremendous Approach of Artificial Intelligence in Major Areas of Viral Vaccine Manufacturing

AI in vaccine technology has the potential to change the industry. While AI can apply to many aspects of viral vaccine technology, all applications of AI involve adjustment to IT infrastructure. The AI is acquainted with different infrastructure tools for developing novel viral vaccines, and these can be added value to the existing infrastructure. The vaccine industries can build new and exclusive AI tools-based facilities to develop novel viral vaccines against emerging and re-emerging viral pathogens. In both conditions, there is a need to integrate perfectly and also require monitoring responsibly.

Viral vaccine manufacturers need to understand what the umbrella term of AI includes and what to look for in different infrastructure tools of AI technology. There are so many tools of AI available, and few of them are working with various modes of AI methods to achieve task-specific goals.

Based on the available literature, AI can play a role in reducing the time and cost of vaccine manufacturing. The author identified areas of vaccine manufacturing where AI can apply and summarized them here in the given below in table 3.

Table 3: AI role in major areas of viral vaccine manufacturing

S. No. A major area of the viral vaccine
1 Designing new & novel candidates for viral vaccines
2 Development of new & novel candidates for viral vaccines
3 Improvement in up-stream processing steps for viral vaccine manufacturing
4 Improvement in down-stream processing steps for viral vaccine manufacturing
5 Documentation, data management, and data analysis of up- and down-stream processing steps for viral vaccine manufacturing
6 Monitoring of viral vaccine safety data of viral vaccines
7 Monitoring of viral vaccine potency data of viral vaccines
8 Documentation, data management, and data analysis of viral vaccine safety and potency data
9 Clinical
trials of viral vaccines
10 Documentation, data management, and data analysis of the clinical trails of viral vaccines
11 Supply chain management of viral vaccines
12 Data management and data analysis of the supply chain of viral vaccines

Need for Artificial Intelligence Infrastructure for Viral Vaccine Manufacturing

Based on available literature on AI, AI Infrastructure, and viral vaccine manufacturing, we will discuss here need for AI in the vaccine manufacturing industry through the following questions and answers. The following eight questions and answers can improve basic knowledge of AI infrastructure for viral vaccine manufacturing and also be helpful for start-ups and budding professionals.

Question 1- How is artificial intelligence used in the vaccine industry?

Answer 1- AI had created to emulate the human mind and working processes. AI can independently solve problems without needing to be the program so. AI is a systematic and independent tool for accepting new data and information and process without human involvement. Therefore AI can play a role in reducing the time, independently running the process, and cost of vaccine manufacturing.

Question 2- Is artificial intelligence better than humans in problem fixing and its conclusion?

Answer 2- The computing power behind AI allows it to process information exponentially faster than a human could, fixing problems or drawing conclusions that the human mind would never be capable of achieving the solution. AI software-based applications have been developed exclusively with highly significant features (execution speed, operational ability, and conclusion accuracy) compared to humans.

Question 3- Describe artificial intelligence as an application.

Answer 3- Based on available literature on the application of AI, It has a broad range of applications in different fields like E-commerce, Education, Finance, Robotics, Human Resources, Agriculture, Gaming, Automobiles, Social Media, Healthcare, vaccines, etc.

I want to mention AI applications with an example – Autonomous vehicles, automatic speech recognition and generation, and detection of novel concepts and abstractions.

Question 4- What is the use of detecting concepts and abstraction as an application of artificial intelligence?

Answer 4- Detecting concepts and abstractions used for detecting potential new risks and aiding humans to understand big bodies of ever-changing information.

AI can help detect the risk during the manufacturing, testing, storage, and vaccination stage of newly developed viral vaccines.

Question 5- Describe the potential for artificial intelligence in the vaccine industry.

Answer 5- Vaccine manufacturing is the most popular field because of its significance and remarkable application of AI. For example – The most practical and urgent application of Artificial Intelligence (AI) is to develop technologies that will help diagnose the acute and chronic stages of infectious and non-infectious diseases and develop vaccine candidature against various infection-causing agents.

– Diagnosis of cancers at an earlier stage of disease through mammograms and MRI scans.

– Design and development of new drugs for the treatment purpose of emerging and re-emerging infectious and non-infectious diseases.

– Design and development of novel vaccines for the preventive purpose of emerging and re-emerging infectious diseases.

The potential for AI in healthcare is broadly applicable. AI technology can apply from the infrastructure level through treating patients.

Question 6- How is artificial intelligence working as a tool; please describe it through examples.

Answer 6- AI is a popular, well-established, and effective data science tool in various industries. AI can help detect the risk during the manufacturing, testing, storage, and vaccination stage of newly developed viral vaccines.

For example, AI can use effectively for cyber security, finance, banking, healthcare, etc. Data security and integrity in IT infrastructure is the biggest issue in all applying industries.

Question 7- What are the infrastructure requirements to create artificial intelligence facilities in the vaccine industry?

Answer 7- Here, I would like to explain the answer to the question in two parts; Common AI infrastructure requirements and specific AI infrastructure requirements for the viral vaccine industry.

Part I – Common AI’s infrastructure requirements

AI functions on collected data: The more data AI solutions have access to, the more successful their implementation will be.

AI solutions with a wide range of data are independent. This data is capable of making more connections. Additionally, these solutions become increasingly accurate in detecting, recognizing, and flagging healthcare issues early.

Part 2 – Specific AI infrastructure requirements for the vaccine industry

The AI movement has connected to and implemented the Internet of Things (IoT). It will provide its services as AI machine learning for solving the problem and provide a solution after analyzing the data AI machine learning.

The massive amounts of data and the increase in connected devices call for a serious evaluation and plan for how an organization’s IT infrastructure can support the increases in activity.

Increased network security for Internet of Things (IoT) devices and advanced network security for organizations sending and receiving data with other organizations is necessary to ensure access to the devices. It shall protect the network from malware.

Storage is another concern for AI implementation. Organizations are needed to have at least a hybrid cloud environment to store data to increase data demands. The solution of AI needs access to cloud data constantly to implement machine learning.

The vaccine manufacturers are still several years away from fully realizing and benefiting from AI. At this stage, there is a need for official and regulatory authority-approved guidelines and regulations to ensure health security data. AI solutions are thoroughly checked and tested before implementation.

Question 8: What is the effect on a different area of vaccine designing and development after implementing artificial intelligence in the industry?

Answer 8- Artificial intelligence is implemented smartly in the vaccine industry, and it can deliver several tangible effects in different areas of the healthcare industry, such as informed decision-making, increased efficiency, competitive advantage, scaling organization, and Customer satisfaction.

(a) Informed decision making: It helps in the decision-making and leaner supply chain planning by providing operational information and insights about patterns and exceptions; support your employees with predictive analytics and forecasts to build new strategies and implement data-based decisions.

(b) Increased efficiency: This saves time and automates your employees’ mundane, repetitive tasks using AI and cognitive services, spotting malfunctions before they even occur. It also increases the efficiency of logistics operations and finding automation solutions.

(c) Competitive advantage: It helps leverage data and analytics to build resilience while staying one step ahead of your competitors: recognize new opportunities and emerging and new business models and optimize your supply chain systems and operations.

(d) Scaling organization: It enables company growth and scaling your business by automating operations used with AI. AI and machine learning applications make it possible to expand to global markets.

(e) Customer satisfaction: This may increase customer satisfaction by streamlining the delivery process and making your product accessible within 24 hours. Make the whole process transparent and status available & update at any time for your customers. You and AI can speed up your response time by empowering human-computer interaction with chatbots and natural language processing.


The article will provide a set of questions and answers related to require AI infrastructure in viral vaccine manufacturing. These are basic but useful to all new candidates, start-ups, and budding professionals in the field of vaccine manufacturing. The following points were concluded here by the author:

1. Artificial intelligence (AI) is acquainted with vast applications in various business fields of biotechnology.

2. AI is the most popular and significant data science tool for vaccine industries.

3. The above questions and answers are discussed here with understandable for candidates; who are interested in starting their carrier in the vaccine industry with data science.

4. The article may provide basic knowledge about AI infrastructure requirements for viral vaccine manufacturing.

5. Author has also encouraged professionals to contribute in the emerging field towards resolving public health issues related to disease diagnosis, treatment, and vaccines at the global level.

The author is always welcome to readers for discussing the article content on my e. mail ([email protected]).

The media shown in this article is not owned by Analytics Vidhya and is used at the Author’s discretion.

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