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Biotechnology development with the assistance of ML experts

1.1 Introduction

It comes as no surprise that technology is developing rapidly and almost daily, providing humanity with new possibilities and opportunities. Yet another possibility technology provides us with is to be life-changing: biotechnology. 

Biotechnology is a field of biology, which, working in synergy with ML, technological studies, and other closely related industries, creates products using living biological systems and organisms. The industry is still pretty young, but it has already proven to be quite effective and has had a lot of investment over the past few years. 

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Still, biotechnology is leaking with all sorts of problems and risks that need to be taken into consideration and requests such new professions as AI software engineer, ML lawyer, robotic surgeon, etc. Check the list of top AI-related occupations here.
And now let me introduce you to some implications of biotech so we could understand the complications that the industry faces, provided with direct examples. 

But before you do that, you may want to know the very conception of biotechnology. To learn more about biotech and its implications, check out this short video.  

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1.2 Implications and Problems of Biotech 

1.2.1   Creating Artificial Body Parts

Artificial body parts are already a thing, created by means of bioengineering. With the help of bioengineering, such organs as the heart, hand, arm, etc., can be created artificially. Some organs, take skin, for example, may be “grown” in laboratories, but we wouldn’t call it a widely spread practice just yet. Multiple laboratories are now struggling at making better cells that could ultimately work the way natural ones do. Growing cells in a proper way is still quite a challenge, as cells require precise care to be suitable for integrating with a human body part.

Machine learning can be of great service in these struggles, as it may help scientists predict the possible outcomes and keep in mind all the factors that influence the overall process of assimilation with the body. With the help of ML and other closely related industries, biotech is looking forward to enhancing the bioengineering industry and becoming more successful at producing artificial body parts.

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However, it is not as easy as it may seem, as the risks are numerous. So what are the main problems of biotech in this particular section of development? 

1.2.1.1            Financial Risks

Quite often producing the industry experiments may be of great risk and difficulty.

Firstly, the experiments in biotech are mainly extremely expensive to conduct, which makes many people searching for new ways of achieving the results with less investment.
Some of the most expensive experiments are closely related to biotechnology, that is the study of the human genome (Human Genome Project). Overall, the cost of an experiment depends greatly on multiple factors but developing branches tend to be pretty expensive, which is why companies may rely on venture financing in such instances but still having no guaranties.

Apart from that, producing a biotech application may include a great deal of risk: all sorts of risks, actually. Not only does developing a new product imply huge financial risks (even considering the fact companies can get patent protection for their products, giving them some time to recover their expenses), but the whole process has to comply with the authorities as well. This may be a tough thing to deal with, as development may be an extremely long and tedious process. In the end, a long-awaited product might turn out inadequate and need to be modified several times before showing stable positive results. 

1.2.1.2            Assimilation Difficulties 

Every patient can have a different experience with their new body parts, and this experience can hardly be beneficial at times. Collecting biomaterial for assimilation procedures is hard on its own, as the material has to be of good quality, cause no harm and successfully reproduce cells. An artificial organ might not always be able to produce cells properly, but sometimes there’s just no way to know that beforehand. 

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