How artificial intelligence is making a quantum leap in the field of gene editing
Medicine and biosciences are one of the fields that most benefit from artificial intelligence technologies, due to their dependence on large amounts of data and their need for accuracy and speed. Gene editing, or genome editing, is one of the medical fields where artificial intelligence will have a major impact in the future, as it can make revolutionary changes in improving the accuracy and speed of the process.
What is gene editing?
Gene editing is the making of subtle changes in the DNA sequence of any living organism with the aim of helping in the treatment of certain diseases. Over the past decades, this field has witnessed significant progress that has enabled scientists to achieve unprecedented medical achievements. However, there is still a lot to discover about the possibilities of gene editing, and artificial intelligence is expected to be the next big step in this area.
How artificial intelligence contributes to the development of gene editing
Researchers have already started using artificial intelligence in the field of gene editing, and this technology has provided a set of advantages, the most notable of which are:
Improve the accuracy of the gene editing process
One of the most important benefits of artificial intelligence in the field of gene editing is to improve accuracy; determining the relationships between genes and physical changes is complex and prone to errors. And here comes the role of artificial intelligence in analysing these relationships with high accuracy.
For example, in 2023, scientists developed a machine-learning-based model that was able to determine whether gene mutations are harmful or harmless with an accuracy of up to 90%, helping doctors figure out which genes need to be modified to prevent the development of serious diseases.
In addition, the success of gene editing depends on understanding the complex relationships between DNA and proteins, as the correct structure of proteins is essential in modifying genetic sequences. Recent research has shown that artificial intelligence can analyse 49 billion interactions between proteins and DNA, which contributes to the development of more accurate editing mechanisms for certain gene groups.
Accelerating research in genomics
In addition to improving accuracy, AI is also helping to speed up genetic research; predictive analysis models can simulate interactions between different genetic materials faster than traditional tests, saving scientists considerable time and effort.
The impact of this use has been clearly seen in the development of COVID-19 vaccines; artificial intelligence has helped pharmaceutical companies accelerate research. For example, Moderna was able to produce and test more than 1,000 RNA strips per month, although traditional manual methods would have produced only 30 strips during the same period. If it weren't for the speed of machine learning, the development of vaccines would have taken much longer.
Personalized medicine (personalized treatment for each individual)
One of the most promising applications of artificial intelligence in the field of gene editing is personalised medicine; it can analyse the genome of each individual with high accuracy, allowing the possibility of designing personalised treatments for each patient to achieve the best possible results.
For example, doctors began using artificial intelligence to analyse protein changes in cancer cells, which helps them choose the right treatments for each individual case. Predictive data analysis can also determine how different patients respond to treatments based on their unique genetic make-up, which contributes to improving effectiveness and reducing side effects.
When healthcare systems are able to offer tailor-made treatments to each patient, this leads to reduced risks and better treatment outcomes, enhancing the chances of success of gene therapies.
Potential challenges of using artificial intelligence in the field of gene editing
Even with the great benefits that artificial intelligence offers in this area, there are some challenges that need to be taken into account, most notably:
The high cost
Gene therapies are very expensive; some treatments can cost up to 3.5 million dollars per treatment. Adding artificial intelligence to these technologies may increase the cost, making these treatments unavailable to many people.
This financial barrier raises ethical concerns, as gene therapies may become restricted to the wealthy, increasing the gap in the quality of health care between different social groups. However, artificial intelligence is expected to help reduce costs as well, as it can speed up research and reduce errors, which can lead to increased efficiency and reduced costs over time.
Safety and accuracy concerns
The reliability of artificial intelligence is a concern; even with its high accuracy, it is prone to error, and excessive reliance on it can sometimes lead to critical errors, causing serious health consequences.
In addition, some AI models may suffer the problem of bias due to the data on which they were trained. For example, some systems for detecting skin cancer have shown 50% less accuracy in diagnosing dark-skinned patients than light-skinned ones, which can lead to diagnostic errors that affect gene editing decisions.
Artificial intelligence is revolutionising the field of gene editing; it contributes to improving accuracy, accelerating research, and developing personalised medicine, which may lead to the development of more effective treatments for incurable diseases. However, cost and safety challenges and biases remain obstacles that must be carefully addressed to ensure that this technology is used in a fair and safe manner.
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