How AI is Reshaping the Biotechnology Sector

Medical biotechnology improves human health by producing drugs and antibiotics from living cells. It also studies DNA and genetically manipulates cells to increase the production of important and beneficial characteristics.

Fremont, CA: AI, or Artificial Intelligence, has the potential to transform biotechnology. There are numerous areas where biotech companies can use AI to improve their processes, drive innovation, and test new business models.

Agricultural biotechnology, animal biotechnology, medical biotechnology, industrial biotechnology, and bioinformatics are some of the subcategories of biotechnology. Let us take a look at how Artificial Intelligence is affecting these fields of biotechnology.

AI in Medical Biotechnology

Medical biotechnology improves human health by producing drugs and antibiotics from living cells. It also studies DNA and genetically manipulates cells to increase the production of important and beneficial characteristics.

In drug discovery, artificial intelligence and machine learning are widely used. Machine Learning aids in the discovery of small molecules with therapeutic potential based on known target structures. Machine Learning is widely used in disease diagnosis because it uses true results to improve diagnostic tests, i.e., the more diagnostic tests run, the more accurate the results.  

AI is also assisting in the reduction of the radiation therapy planning process, which saves time and improves patient care. Another promising application of Artificial Intelligence and Machine Learning is the enhancement of EHRs with evidence-based medicines and clinical decision support systems. Aside from the applications mentioned above, these technologies are widely used in gene editing, radiology, personalized medicine, medication management, and other fields.

AI in Agricultural Biotechnology

Agricultural biotechnology involves the creation of genetically modified plants in order to increase crop yields or to introduce new characteristics into existing plants. It includes traditional plant breeding, tissue culture, micropropagation, molecular breeding, and plant genetic engineering.

Biotechnology companies are now using Artificial Intelligence and Machine Learning techniques to create and program autonomous robots that can perform important agricultural tasks such as crop harvesting at a much faster rate than humans. Data captured by drones is processed and analyzed using computer vision and deep learning algorithms. This aids in crop and soil health monitoring. Machine Learning algorithms aid in the tracking and prediction of various environmental changes, such as weather changes, which affect crop yield.