The Power of AI in Biotechnology: Revolutionizing Innovation

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The Power of AI in Biotechnology: Revolutionizing Innovation

Artificial intelligence in biotechnology can speed up drug discovery, deliver analytics, accurately diagnose medical conditions, edit gene structures, develop personalized medicine, and do much more to help mankind. Here, we’ll discuss the role and importance of AI in biotech industries. 

The role of AI in biotechnology is gaining momentum in recent times. The biotech industry is redefining its processes using AL and ML technology to get better, faster, and more accurate results. Be it the pharma industry, healthcare, animal husbandry, or agriculture, AI and biotech are setting the stage for greater advancements and innovations. 

Biotech or biotechnology is the use of technology in biology. Pharmaceutical companies are the major players in this industry, though others are catching up quickly. Statistics show that the pharma industry will spend around $3 billion on AI in drug discovery by 2025. 82% of industry experts opine that the industry will continue with the digitalization of its operations during post Covid-19 pandemic. 

The power of big data and data analytics can revolutionize the biotech industry on various fronts. From using machine learning algorithms to natural language processing (NLP), neural networks, and advanced robotics, AI pushes the boundaries and creates more possibilities to improve the quality of life. New biotech companies are entering the global market, using artificial intelligence as an integral part of their business. Reports show that the biotech industry received $2.4 billion in venture funding by December 2022. Many rely on AI Biotech companies and solution providers to integrate the systems with advanced technology and use AI in all verticals. 

In this blog, we’ll read about the role of AI in biotechnology and how applied AI is helping biotech companies to drive innovation and be ready for future developments. 

Can AI and Biotech Save Lives?

Technically, yes, artificial intelligence and biotech can save lives. This is done by helping researchers create better quality drugs (with fewer or no side effects), correctly diagnose complex ailments in the healthcare industry, identify and change gene patterns to prevent life-altering diseases, etc. 

Most importantly, combining AI and biotech allows different players in the industry to share information and work together irrespective of geographical restrictions. They can create AI-based pharma (medical) tools and find solutions to save lives. 

How is Artificial Intelligence Transforming the Biotechnology Industry?

The advancement in the biotech industry now relies on big data, AI, and ML technologies. Many experts and top-level executives of leading biotech and pharma companies have said that 2023 is when AI in biotechnology will bring revolution and value and also fit for the purpose it is being used for. 

AI’s role in biotechnology is not limited to automating repetitive tasks or structuring data flow. Artificial intelligence can help in research, day-to-day work, data analytics, drug manufacturing, and much more. It speeds up the entire process by assisting human researchers to process large datasets accurately in a short time.

Diagnosing and Treating Mental Illness 

The growing cases of mental illness have been a cause of concern in the last few years. Mental illness affects around 13% of the world’s population. The Covid-19 pandemic has led to an alarming increase in depression and anxiety. People with depressive symptoms went from 193 million to 246 million (28% increase), while anxiety disorders showed a 25% increase (298 million to 374 million). 

Artificial intelligence can help doctors and scientists detect early signs of mental illness and use preventive medication or treatment to help patients feel better. Treating mental illness is hard because the symptoms exhibited by patients are varied and not universally applicable. However, advanced AI programs can observe the brain waves of patients to recommend the best antidepressant therapies for each patient. 

AI algorithms are being used to study and identify the behavioral loops in addicts to determine the chances of relapse so that physicians can take the necessary action. Furthermore, AI can help create personalized medicine that will be more effective in treating the patient. However, there is a lot more research to be done in this field to help people deal with mental illness and lead better lives. 

Creating 3D Protein Structures 

Proteins are one of the four most important macromolecules essential to building life. The scientific community has been using X-ray crystallography and nuclear magnetic resonance to identify protein structures. They have added 187,000 identified structures to the database. However, the process is slow and laborious. Many more proteins are yet to be identified. 

A UK-based team of AI researchers created AlphaFold, a machine-learning platform that uses the existing database to predict protein structures and build 3D models. The tool takes only a small fraction of the time takes originally to complete the job, that too with greater accuracy. This can help biotech companies identify more proteins quickly and use the vital ones in developing effective drugs. Diseases like cystic fibrosis and muscular dystrophy can be treated with the help of this technology. 

Gene Coding Identification 

Machine learning in Biotech can be researchers build powerful models to study and understand human genomics. The next-gen technology used by biotech companies helps sequence a gene in less time and creates an alternative method to homology-based sequence analysis. 

CRISPR (clustered regularly interspaced short palindromic repeats) can electively modify and edit the DNA or genes of living organisms. This allows scientists to identify and destroy the DNS from bacteriophages that cause infections and diseases. The technology can also help create personalized medicine based on the genome of the patient. This can be a game-changer in treating hereditary diseases and identifying the probability of a patient inheriting a family disease or illness. 

Lab Assistants 

AI in biotech is also being used to simplify tedious tasks. Artificial intelligence programs are acting as lab assistants and managing backend work as well as complex tasks like data analytics. is a fast, accurate, and open-source big data analytics platform that allows people to use its statistical models to identify patterns in datasets. Even though the company caters to many industries, many other AI platforms cater exclusively to the biotech, health, and pharma industries. 

Another role of AI as a lab assistant is the use of robotic devices in research centers, healthcare units, and hospitals. Though this area is still being explored by the biotech industry, we can soon expect robotic assistants to have a prominent role. 

How can Biotech Companies Leverage AI to Drive Innovation?

Speed Up Innovation and Analytics 

Artificial intelligence is now a part of research and development in the biotech industry. AI tools can process large datasets in a quick time and deliver faster analytics. The initial stages, where scientists have to repeatedly conduct lab experiments and record their findings, can be hastened using AI. AI tools can make the recordings and come up with possible variations to the experiments and the subsequent results. 

The process of discovering and analyzing extensive information doesn’t have to take years. Artificial intelligence and machine learning can accurately analyze the data and deliver insights in days or hours. From identifying patterns to detecting errors in datasets, all repetitive tasks can be automated with AI technology. Scientists and researchers can directly use the insights in their experiments. 

New Vaccines and Drugs 

With new viruses and their mutant versions affecting people around the world, it has become important to speed up the process of developing vaccines. The biotech industry had to race against time to create vaccines for the Covid-19 pandemic. The entire process can be hastened by relying on advanced AI and ML algorithms to study molecular data and identify the right composition as an antidote to the virus. 

Earlier, scientists had to manually perform most processes, and it took around five to ten years to create a vaccine or new drug for a virus. However, by using AI in biopharma research, companies can develop new vaccines in two or three years. 

Advancement in Industrial Biotech 

AI is used in the field of biopolymer replacements, molecular designing, and robotics. For example, AI tools can create 3D images of molecules and edit the structures to create new chemical compositions. This makes it easier for laboratories to develop new and better chemicals for industrial use. AI, ML, and IoT are already a part of industries and help with day-to-day operations. 

Many companies that deal with textiles, fuels, car components, chemicals, and biotech manufacturing gain an advantage by streamlining their processes using artificial intelligence. Automated robots can replace humans in hazardous zones to minimize the risk of accidents. 

Agricultural Biotech 

AI and biotech have a great role in the agricultural industry. Genetically modified and hybrid plants are not new. Researchers say that genetically modified plants provide better and greater yields while consuming fewer resources. However, successfully creating such a seed or plan takes years of work. Scientists work with many procedures like tissue culture, molecular breeding, and micropropagation to get the results. 

Biotech companies in the agriculture sector use AI and ML tools to speed up genetic engineering. Computer vision and deep learning technologies are used to monitor soil and crop health in farmlands. The tools can also be used to track environmental changes and predict rainfall, storms, and weather conditions to help farmers decide the best crop to plant for the season. Furthermore, robots can help farmers with hard jobs like harvesting crops through automated machines. 

Animal Biotech 

Artificial intelligence in the animal biotech industry can help companies use molecular biology to modify the genes and traits of animals and create mixed or cross-breed versions for agricultural and pharmacological applications. AI is also useful in selective breeding, where animals of specific qualities are bred to give birth to offspring with similar attributes. 

Machine learning algorithms can be used to process large datasets with genomic data about different animal species and ways to choose animals for selective breeding. This helps the animal industry breed healthier and stronger offspring that are less prone to diseases or illness. 

Personalized Medicines 

Biopharma companies take personalization one step ahead by developing medicines based on a patient’s condition or symptoms. While the actual process is a lot more complex and involves the use of several AI tools, it is quite possible to find medication for lesser-known or hereditary diseases that affect only a small portion of the community. 

Here, Artificial Intelligence and Machine Learning are not only used in discovering new drugs but play a crucial role in understanding how diseases develop in humans, the various stages of disease development, the corresponding symptoms, and ways to effectively treat the conditions based on the parameters of each case. 

Are AI and ML the Future of Biotech?

Research and development are the backbone of biotechnology but are also expensive, laborious, and time-consuming. By adopting artificial intelligence, machine learning, deep learning, neural networks, big data analytics, etc., the biotech industry is gaining momentum and enhancing productivity. 

Given the impact of biotechnology on our world and the role of AI in biotechnology, there’s no denying the need for advanced technology to improve the quality of human life on multiple fronts. AI-driven drug discovery process is now a part of many biopharma companies and will continue to speed up the development of new and effective drugs. 

Similarly, there is an increase in third-party and offshore AI solution providers who provide the necessary IT infrastructure and integration services to help biotech companies adopt advanced technology. AI and ML will continue to be the future of biotech as more companies around the world use the technology all various stages. 


AI in biotechnology is expanding the possibilities of its role in various industries like pharma, agriculture, and industrial. From automating recurring tasks to speeding up the discovery phase, AI can be used in several ways in the biotech field. 

It’s time for biotech companies to become proactive and adopt AI technologies to boost efficiency. Many biotech firms are partnering with AI service providers to initiate digital transformation quickly and effectively. Talk to our expert team to know how customized AI tools can revamp biotech processes. 

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