How AI is Finding New Cures in Old Drugs
With an increase in diseases of a far more complex nature than previous decades, the dependence on Artificial Intelligence (AI) in medical treatment and pharma solutions is on the rise. With viable results, scientists are ecstatic about each new discovery they encounter with the help of AI.
Medicine is a multifaceted subject that requires years of training and experience for doctors to become qualified. With the rapid pace of changes in medicine and treatments, keeping up with these continuously evolving changes is often not possible. This is where AI steps in.
The speed at which AI can be used to recognize new knowledge in medical treatments and its corresponding use in developing drugs to counter diseases is tremendous. It surpasses the previously tested methods of clinical trials that take years and cost millions, before a drug is approved or disapproved.
For these reasons, among others, more and more pharmaceutical companies are looking to AI for solutions in the healthcare sector. Researching medical solutions is a job that is so very vast, with nearly 10,000 publications released on a daily basis; to make sense of all this information and analyze it quickly is humanly impossible. But AI has now made it easy to both gather and analyze data that is useful; sifting out unnecessary or unrelated information and narrowing it down to relevant material which can then be further studied by scientists.
In addition, AI can offer valuable insight into existing diseases and come up with new methods to overcome them. Equipped to find the genetic mutations that cause a disease, and further predicting the corresponding and effective treatments to treat the disease, AI utilizes its knowledge to deliver drugs in a shorter span of time, at a more economical cost. Most importantly, this is done by creating drugs from existing compounds to fight a range of diseases. In simple terms, existing drugs are used to create new cures by changing their molecular composition, and aligning them in accordance with a disease.
There is absolutely no surprise then that AI, in conjunction with the most recent research techniques, can aid in the development of drugs and medical therapies for a multitude of diseases.
With proven solutions and development in medical research, a number of big companies like Pharnext, Google and IBM, and smaller startups like Benevolent AI and Recursion Pharmaceuticals, are investing in the tools of AI to further their research and capture a market share for new discoveries.
These companies are using AI to examine drug and patient data, in an attempt to figure out new strains or patterns that can be used to treat a host of diseases. Just like old wine in a new bottle, AI is being used to figure out how existing drugs can be used in different compositions to treat new or existing diseases.
Another interesting aspect to the use of AI is repurposing. In medical terminology it refers to the 'application of already approved drugs and compounds to treat different diseases.'
AI is used to combine existing drugs and 'repurpose' them into compositions that provide healing powers for a range of diseases, which otherwise would have been ineffective on their own.
Diseases that have shown statistical improvements with the help of AI induced treatments are now being given fast-track status, as the drugs used have shown 'superior effectiveness' in treating the disease. This is a tremendous achievement for companies like Pharnext who have been working relentlessly to incorporate the use of AI into medical research and development and bring about medical solutions to fight rare illnesses.
The average time that a drug or treatment takes for approval is anywhere between 8 to 10 years. There are countless preclinical and clinical trials and tests conducted for a full proof approval before it can be rolled out. This will help avoid prescription errors in the long run. But by using existing drugs that have been approved and repurposing them, with the help of AI, the need for long drawn trials does not arise, and treatments and drugs can be fast-tracked.
With repurposing, there is no need to create or discover new drugs, bringing down the overall cost. With the success of Pharnext's foray into repurposing with the help of AI, other companies are following suit, and are also looking at possibilities of fast-tracking therapies that have been proven effective.
Such successes only reaffirm the importance of Artificial Intelligence in the medical industry. However, it is important to remember that AI can only succeed when it has access to huge amounts of high-quality data. While more common diseases like cancer and HIV have plenty of data to analyze, it's the more uncommon diseases that will take time to come up to speed for AI based medical solutions. With time though, AI will enable a more comprehensive approach to disease management and medication, turning it into an area of medical progress that scientists, clinicians and patients have much to be excited about.