In the world of medicine, there is always the quest for the next cure for one of the many diseases that affect mankind. This quest often centers around the discovery of new drugs that will be the cure. There are always advancements being made in this field of medicine but never enough or fast enough to deal with the diseases and afflictions that mankind can be stricken with.

Drug Discovery

Drug discovery is part of medicine, as well as is included in the fields of biotechnology and pharmacology. 

In The Past

There have been a lot of drug discoveries, many of which that have turned life threatening illnesses into ones that can be fully treated or in some cases controlled. The process in which these discoveries are made are long and arduous. The discoveries were made by taking remedies that were currently being used and then identifying the active ingredient in them that worked. Or in some cases discoveries were made by accident. A good example of this was penicillin. 

In The Now

Advancements have been made in drug discovery partially because of new technology. However, the methods being relied on are very expensive. It takes a lot of money to start projects in the quest for new drugs to deal with a specific disease. An example of this is cancer research when it comes to developing new chemotherapy treatments or other drugs used in the treatment of cancer. With all the modern technology that is available today the advancement in drug discovery is slow, challenging, frustrating and expensive. In the meantime millions of lives depend on drug discovery advancement.

AI and Drug Discovery

The drug discovery industries are constantly in search of new technology to assist them, and they are now showing great interest in artificial intelligence. 

Machine learning and dynamics simulation, which can fall within the realm of AI, can be useful tools for drug discovery. Many believe that AI can be effectively used in the many steps that the process of drug discovery takes. These steps include:

  • First, identifying the targets that may respond to drugs is critical. Such as protein receptors that are found in some of the diseases.
  • Target binding may be the next process, which requires intense screening of the compounds that can be used to see which ones have the capability of binding to the target.
  • Then there is a whole gambit of testing both biologically and chemically that has to be carried out. 

How Could AI Help?

AI is currently available that is able to identify certain patterns in accumulated data. Based on this, it may assist with predictions as to which of the compounds would be the most beneficial to be turned into medicines. 

How Is AI Being Currently Used?

There are many biopharmaceutical companies that are using AI to further their efforts. Some examples are:

Pfizer:

This company is relying on the IBM Watson to help find new immune-oncology drugs. Watson is a machine learning system which AI. 

Sanofi:

This is a UK based company that has just completed negotiations with Exscientia, who has a AI system that can be used in the research for metabolic diseases.

Roche:

This company is heavily involved in discovering new cancer treatments. They are relying on AI from GNS Healthcare. 

These are just a few of many that are now entering into the world of AI.

The Potential Benefits

There are numerous benefits that come with the use of AI, such as being able to make the process of drug discovery less time consuming, more effective and less costly. Already to date there has been some significant benefits with the use of AI in the medical industry.

A Critical Discovery

Sometimes new drugs are released for use where later in years, it is discovered that there are some major and serious side effects. One such case was with a drug called Lamisil. This was a drug developed for the treatment of fungal skin infections and thrush. Three years after its release for use multiple reports of side effects arose. Some so serious, they led to death as a result of the drug doing irreparable damage to the liver of some that had used it. 

Canadian researchers were able to identify the compound that was causing the problem. What they could not determine is how the compound was being formed in the liver.

Then a graduate student using AI was able to solve the problem. The AI was able to determine the pathways that the compound was taking when it was metabolizing the liver. It was a two step process that was taking place, which is extremely difficult for scientists to determine but did not prove difficult for the AI.

The Potential Uses of AI

Artificial intelligence has the ability to handle complex problems. It has the ability to decipher patterns which is critical in drug discovery. Patterns are comprised of huge amounts of data, which is very complex for the human mind but doesn’t seem to be as such for AI.

This discovery not only solved a very serious problem, but it opened up new opinions on how AI could be beneficial in other areas of this type of medicine. 

Drug Enhancement

Not only could AI be used for the discovery of new drugs, it could also take on a role of enhancing drugs that are already discovered. A good example of that is the use it was put to for the fungal drug. There have been several cases where drugs have had to be pulled off the market because of new discoveries of side effects. Rather than have to shelf these drugs possibly AI could be used to identify the flaws so they could be corrected.

The Challenges To Be Faced

Although AI may be a potential resource that comes with many benefits, it creates extra challenges that are current. Researchers and scientists have to become familiar with the AI and learn its capabilities. It is necessary if they want to be able to capitalize on its capabilities. It takes time and resources to do this and puts an extra burden on those who are involved.