HALVING DRUG DISCOVERY TIME, THE AI WAY?
ChatGPT has transformed the world or so do we believe. It has cut down our time considerably to reach our destination of Artificial General Intelligence, AGI, the first and most important threshold to reach / cross / outperform human brain capabilities. To err is human, and few humans have the human threshold which we boast off. Rest is all hit and trial. The journey will take some time for sure, but the precision which it promises to provide, would be out of the world. Predicting your knowledge output in no uncertain terms, would be giant leap. You can be christened as the New Intelligence.
While this tectonic movement goes on, there are innumerable areas which are being impacted in a manner, we could have never imagined. The tools were not there. DeepMind which predates OpenAI has been a leading AI research and product company, which has given us milestone after milestone in its onward AI march. It was acquired by Google, but its founder, Demis Hassabis, still leads the way from one technological breakthrough to the other. Demis Hassabis cofounded Google AI unit and also heads the drugs offshoot Isomorphic Labs. He said, “the goal was to reduce the discovery stage – when potential drugs are identified before clinical trials – from the average of five years to two.”
Shortening the process is critical given the fact that pharmaceutical companies are under pressure to fill their pipelines with new potential medicines, while the existing one’s face patent cliffs. Under pressure to bring down drug prices, they are looking for way and means to cut cost on R&D. Currently, it takes a decade to discover and develop a new drug. The average cost of the drug is $2.7 billion based on one reliable research. Where is the AI ray of light to pull it off? The Isomorphic Labs uses an AI platform to predict biochemical structures, which aids in the creation of new drugs.
The hastening of the process can be done by “recommending which potential compounds will have the desired impact on the body.” Given the potential of this platform / technology many drugmakers want to partner with Isomorphic Labs. Hassabis says, that the “company wanted to focus on collaborations that could improve its technology.” This makes immense technology and business sense. He said that they could probably sign up with a dozen of companies but that would mean “to make more bespoke solutions for the individual programmes.” Following, it’s thought process, Isomorphic Labs has gone ahead to sign deals with just two pharmaceutical companies; Lilly and Novartis. Good luck to pathbreaking venture. The caution is that even drugs discovered by AI can fail in clinical trials. But that is what R&D is all about!
WITH AI FACILITATION, WE ARE ENTERING INTO A NEW ERA OF DRUG DISCOVERY.