ARTIFICIAL INTELLIGENCE AND

The Future of Computational Biochemistry

Perhaps the most fundamental shift in how medicine is made could come from computational biochemistry. Virtually all major drug-makers have computational chemistry labs and are using the processes to make drugs better and faster.


The process of developing drugs generally begins with an attempt to find a chemical compound that will inhibit a certain protein that causes or is associated with a disease. Traditionally, the beginning of this process involves randomly testing millions of compounds in test tubes in the hopes of identifying a protein inhibitor.


Computational biochemistry allows drug-makers to cut out a significant portion of the test tube experiments. Instead, a computer simulates the protein and tests all of its atomic interactions. That analysis will yield a far narrower list of “leads” that researchers can take to the next stage of testing.


Advanced computer analytics is already allowing pharma companies to develop better products for less money - and it’s only beginning. Computers are diving deeper into data by the day. Their insights are becoming even clearer. It may not be long before their ability to simulate chemical interactions will be so accurate that clinical trials on human beings will no longer be necessary. That development could reduce the time it takes to develop drugs by years and the cost of R&D by billions.