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Artificial Intelligence invaded the Bio Technology, the century began to re-born

AI invaded the Bio Technology

The year is 2020 AD, the sequencing of a complete human genome now costs less than a thousand dollars and the growth of transplantable human organs inside other animals is now gradually entering clinical trials. Advances such as this are the result of Biotechnology, which can be defined as technology based on biology. As we all know Information Technology has taken a paramount role in recent times and one major section of it which is Artificial Intelligence is rising rapidly. The combination of both these fields forms a novel topic called AI for Biotechnology.




Drug Discovery and Development

The current process of creating a drug is a long and time consuming one. It starts when scientists discover a biological target after which they begin testing different chemical mixtures in different dosages against it. Finally, they need to regulate the finished drug so that it is compatible with a wide range of people. Machine learning can be used to speed up lower the costs of this process. Primary stages in figuring out the drugs chemical structure and in the latter stage investigating the effect of a drug – both in basic preclinical research and clinical trials, in which a lot of biomedical data is produced.

 


Plant Biotechnology

Genetically modified Plants have become widely popular ranging from Golden Rice to the Flavr Savr Tomato. Biotechnology firms are now leveraging Artificial Intelligence and Machine Learning techniques to develop and program autonomous robots that handle important agricultural tasks like harvesting crops such as these at a much faster pace than humans. Computer Vision and Deep Learning algorithms are leveraged to process and analyze the data captured by the drones. Moreover, companies like Zymergen and Ginkgo Bioworks use vast metagenomic databases, machine learning, and robust automated laboratories to design microbes custom-suited to manufacture a desired good such as the cotton in your T-shirt.



Animal Biotechnology

Much like Molly the cloned sheep, molecular biology techniques are applied to genetically engineer/modify animals to bring about desirable characteristics such as higher muscle mass, and improved hardiness. Selective breeding is a very common practice where animals with good features are bred with each other so that their offspring will also result in the same traits. This is performed on the molecular level too where genetic characteristics among the animals are selected and such animals are bred. Machine Learning helps in understanding the genomics and making informed decisions and enhancing the capabilities of scientists in predicting the expression of those genes.


Human genomics

Each individual human has its own unique genetic footprint also known as their genome, by sequencing the genome of a human we can understand all minute details about him/her, from any allergies, to possible future medical conditions like cancer or heart disease, to even resistances and efficacies to drugs. After sequencing the size of a human genome is around 200 Gigabytes! This is only for a single person and is a lot of data to sift through manually. With advances in artificial intelligence and machine learning applications, researchers are better able to interpret and act on this genomic data.

With tools like Google’s DeepVariant, geneticists can now get an accurate picture of the full genome while being able to detect small mutations from random errors. This data could warn doctors of future diseases pertaining to this individual. AI & Deep learning was instrumental in effectively training DeepVariant.


Advantages of AI in Biotechnology

·  Time-saving - Since biotechnology is a field in which large amounts of data are constantly gathered, keeping track, and processing all this data would take tremendous amounts of time for humans alone. Computers have made this task quicker, and now the advent of Artificial Intelligence promises to shave off even more time.

·  Cost-effective – As mentioned above, crunching through piles and piles of data will use up a considerable amount of man-hours, If a neural network is trained to do such tasks the need for manual labor will be nullified. Furthermore, since errors are fewer, less money is wasted

            ·  Scalability – An AI-powered system will be able to adapt to new challenges better than a usual computerized system, furthermore neural networks can be trained for a wide range of functions and then adapt differently to specific ones. And many morethese are just the primary advantages of applying AI in  Biotechnology.


The FUTURE.....

The future of this marriage between these 2 titans of science is bright, from human genome sequencing being a cheap and mandatory procedure, scientists and doctors being able to halt a pandemic such as the recent Covid-19 in its tracks by the speedy development of a cure, no more waiting lists for organ donations therefore no more unnecessary deaths. And maybe humanity will finally have a chance at tackling the big fish like world hunger and overpopulation. We must not be afraid to venture on ahead and discover, for it is then that we truly support the human race.

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