Why is artificial intelligence critical to biotech?

Biotechnology uses modern technology to harness biological processes, organisms, cells, molecules and systems to create new products that benefit people and the planet. Laboratory research and development through bioinformatics, exploration and extraction of biomass through biochemical engineering, and development of high-value products. Biotechnology operates silently in various fields such as agriculture, medical, animal, industrial and other fields.

White biotechnology refers to the technology that uses organisms to manufacture products through chemical processes. It is mainly used in the industrial field. It can solve the energy crisis by producing biofuels. For example, for vehicles or heating.

Every business organization working in the field of biotechnology maintains a large number of data. This data must also be filtered and analyzed to be valid and applicable. Operations such as drug manufacturing, chemical analysis, enzyme research, and other biological processes should be supported by computerized tools to achieve high performance and accuracy and help reduce manual errors.

Artificial intelligence (AI) is one of the most helpful technologies that helps biotech manage biological processes, drug production, supply chains, and data processing.

It interacts with data obtained through scientific literature and clinical data trials. AI can also manage difficult-to-compare clinical trial data sets and enable virtual screening and analysis of large amounts of data. Thus, it reduces clinical trial costs and leads to discoveries and insights into any field of biotech operations.

More predictable data makes it easier to establish workflows and operations, improves performance speed and program accuracy, and enables more effective decision-making. 79% of people believe that artificial intelligence technology will affect work processes and is crucial to productivity.

All of this results in a more cost-effective solution. Over the past three years, revenue generated with the help of artificial intelligence has grown by an estimated $1.2 trillion.

Advantages of using artificial intelligence in biotechnology

Artificial intelligence is used in various fields, although the capabilities of this technology, such as data classification And making predictive analytics is beneficial in any scientific field, but has particularly prominent applications in healthcare.

Manage and analyze data

Scientific data is constantly expanding and must be organized in a Arrange in a meaningful way. The process is complex and time-consuming: scientists must undergo repetitive and arduous tasks that must be performed with great concentration.

The data they use is an essential part of the research process, and failure can result in high costs and energy losses. Furthermore, many kinds of research do not lead to practical solutions because they cannot be translated into human language. Artificial intelligence programs help in the automation of data maintenance and analysis. The open source platform powered by artificial intelligence helps reduce the repetitive, manual and time-consuming tasks that lab workers must perform, allowing them to focus on innovation-driven operations.

Gene modification, chemical composition, pharmacological studies and other key informatics tasks are thoroughly examined to achieve more reliable results in less time. Effective data maintenance is critical to every scientific department. However, the most significant advantage of AI is its ability to organize and systematize data into predictable results.

Driving Innovation in Healthcare

Over the past decade, we have faced There is an urgent need for innovation in the manufacture and application of pharmaceuticals, industrial chemicals, food-grade chemicals and other biochemical-related raw materials.

Artificial intelligence in biotechnology is critical to facilitate innovation throughout the life cycle of a drug or compound, as well as in the laboratory.

It helps find the right combination of chemicals by calculating permutations and combinations of different compounds without the need for manual laboratory testing. Additionally, cloud computing enables more efficient distribution of raw materials used in biotechnology.

In 2021, research laboratory DeepMind used artificial intelligence to develop the most comprehensive human protein map (Extended reading:Artificial Intelligence Draws "Revolutionary" Human Protein Map). Proteins perform a variety of tasks in the human organism—from building tissue to fighting disease. Their molecular structure determines their purpose, which can be repeated thousands of times—knowing how proteins fold helps understand their function so scientists can figure out countless biological processes, such as how the human body works, or create new treatments and medications.

These platforms provide scientists around the world with access to data about discoveries.

Artificial intelligence tools help decode the data to reveal the mechanisms of specific diseases in different regions and help build analytical models that match their geographical locations. Before the use of artificial intelligence, time-consuming and expensive experiments were required to determine the structure of a protein. Now, through the Protein Data Bank, scientists have free access to some 180,000 protein structures produced by the program.

Machine learning helps diagnoses more accurately, using real-world findings to enhance diagnostic testing. The more tests you perform, the more precise the results you produce.

Artificial intelligence is a great tool to enhance electronic health records with evidence-based medicines and clinical decision support systems.

Artificial intelligence is also widely used in genetic manipulation, radiology, customized medical treatment, drug management and other fields. For example, according to current research, AI improves the accuracy and efficiency of breast cancer screening compared with standard breast radiologists. Additionally, another study claims that neural networks can detect lung cancer faster than trained radiologists. Another application of AI is the more accurate detection of diseases through X-rays, magnetic resonance imaging (MRI), and CT scans through AI-driven software.

Reduce research time

Due to global New diseases are spreading rapidly across countries. For example, with COVID-2019, biotechnology must accelerate the production of necessary drugs and vaccines to combat these diseases.

Artificial intelligence and machine learning sustain the process of detecting appropriate compounds, assist in their synthesis in laboratories, help analyze the validity of data and supply them to the market. The application of artificial intelligence in the field of biotechnology has shortened the operational performance time from 5-10 years to 2-3 years.

Improve agricultural yield

##Biotechnology is the method of genetically engineering crops to achieve greater harvests The essential. AI-based technologies are increasingly playing a role in studying crop characteristics, comparing quality and predicting actual yields. Agricultural biotechnology also uses robots (a branch of artificial intelligence) to complete manufacturing, collection and other critical tasks.

Artificial intelligence helps plan future patterns of material circulation by combining data such as weather forecasts, agricultural characteristics, and the availability of seeds, compost and chemicals.

Artificial Intelligence in Industrial Biotechnology

The Internet of Things and artificial intelligence are widely used Used in the production of vehicles, fuels, fibers and chemicals. Artificial intelligence analyzes the data collected by the Internet of Things and converts it into valuable data by predicting the results, which can be used to improve production processes and product quality.

Computer simulations and artificial intelligence suggested the intended molecular design. Strains are generated through robotics and machine learning to test the accuracy of developing the desired molecules.

Although it is only the beginning of the application of artificial intelligence in the field of biotechnology, many improvements can already be provided to various fields. Furthermore, the continued development of AI software in biotechnology demonstrates that it can be used across multiple processes, operations, and tactics to gain a competitive advantage.

Not only does it drive innovation, it is a valuable tool that allows for more accurate testing and prediction of results in the lab without the actual performance of the experiment, thus reducing costs. In addition to finding future human necessities in healthcare and agriculture, anticipating potential losses and making projections for companies, they should direct resources toward more efficient production and supply.

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