Artificial intelligence in biotechnology

Original article was published on Artificial Intelligence on Medium

Artificial Intelligence in biotechnology

One of the main tools that biotechnology uses in its processes is Machine Learning.

The ability to establish data analysis algorithms, prediction, and probability models establishes research guidelines that would otherwise take years.

Artificial intelligence technologies, such as machine learning and big data, are combined to generate prediction models.

Big Data helps in massive data analysis and even neural networks to be able to reach conclusions more efficiently and effectively in terms of time and cost.

Immediate impact

Currently, benefits have already been seen in agriculture with improved food or in the creation of biodegradable products, however, the most significant impact is expected in the field of health and environment.

For the following examples, it establishes that artificial intelligence tools are implemented in biotechnology processes:

The cost for research and processing of the human genome has been reduced from $ 3 Billion dollars in 2001 to almost $ 1 thousand dollars in 2019.

In order to sequence the human genome used to take between 2 to 4 months, but currently with the right knowledge, it can be done in a couple of hours.


Taking the same need for organ donation as an example, there is a branch of biotechnology that seeks to create organs outside of a human body.

A few years ago this would have seemed impossible, but with the research processes of the functioning of the human body and the physical and chemical elements that come into play, you can imagine having a result by 2024.


A challenge that is currently facing the integration of artificial intelligence in biotechnology is the pandemic that we are currently experiencing.

Part of biotechnology is the development of drugs and vaccines for certain diseases.

Given that today we are seeing how a new disease can collapse various normal processes in the world, we are as spectators measuring success in variables of time and effectiveness.

By this, I mean that several laboratories in the world with artificial intelligence capabilities applied to biotechnology are looking for effective treatment and especially a vaccine.

This is undoubtedly a test that highlights the current state of this alliance between two super sciences.

Risks and precautions

Like any revolutionary idea, it is accompanied by certain aspects that we must be careful with.

In itself, biotechnology has always been a highly regulated aspect by government entities due to the risks to humanity that it can bring.

Likewise, it poses risks in the creation of viruses or diseases that can get out of control.

Adding artificial intelligence to biotechnology is like adding fuel to a science that must be regulated to avoid unwanted goals.

As in any field of application, artificial intelligence in biotechnology must always be oriented to the continuous benefit of the current situation of humanity.

Goals must be established in common agreement that leads to solutions to problems that we face today.

The union of these sciences has an obligation to improve the quality of life of people and the planet in general.