WASHINGTON, U.S.: Drug prices in the U.S. are the highest in any developed country in the world, with a particular increase over the past decade. This trend is something that people throughout the country, including President Donald Trump, want to see reversed. One influence that could result in the fall of prices is the use of artificial intelligence (AI), which can reduce development time, creating potential savings across the board.
According to reports, the majority of Americans believe that passing laws to lower drug prices should be a top priority for the government. Currently, Americans pay around $1,000 each year for prescription drugs. For those who may need ongoing prescriptions for more serious illnesses, prices can be in the tens of thousands of dollars, with new medicines for life-threatening diseases often launching with prices exceeding $100,000 per year.
Research and consulting solutions provider GlobalData reports that one of the major reasons for the high drug prices is that the cost of drug development has been rising significantly and pharmaceutical developers are struggling to achieve a return on their investments. The average timeline for a drug to be developed from discovery phase to market launch is about 15 years, and the total number of new molecular entities—a drug without precedent among regulated and approved medications—commercialized per year does not match the extraordinary research and development cost for the company.
One of the most time-consuming phases in the process of drug development is discovery, which takes four to five years on average. Identifying promising drug targets is one of the greatest challenges and this is the most crucial phase, where prudent decisions have to be made about whether to proceed to clinical trials.
This process is now being revolutionized with the development of AI and its ability to analyze big data and identify patterns and generate algorithms to explain them.
Dr. Valentina Gburcik, cardiovascular and metabolic disease director at GlobalData, said “These programs can help researchers generate more accurate hypotheses faster, making the drug discovery process less expensive and more effective. In addition, the database of electronic medical records and public health data can be analyzed to identify hidden patterns that can lead to a quick identification of potential molecular targets for a disease.”
Another move that could help in the reduction of prices is the use of blockchain. Gburcik believes that the technology could be appropriate for sharing electronic health records between various health organizations in a secure way, which would further facilitate research and speed up the drug development process.
“This significantly accelerates clinical trials and data management, further contributing to cuts in the timeline and cost of drug production,” said Gburcik.
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