At present, artificial intelligence (AI) is a contribution in several industrial sectors and the pharmaceutical industry is not exempt from these technological procedures. Today, the doses of a medicine are standardized, essentially, based on the patient’s age range. As Bertrand Bodson CDO of Novartis explains, AI would help generate new drugs that are more effective and, in addition, suggest more precise and smarter doses so that patients have a better treatment. Bodson suggests that establishing an AI model using machine learning algorithms could help the generation of personalized treatments according to the characteristics of each patient, biology and genetics among others. Bodson exemplifies with eye diseases and proposes that some of these data could be deduced by introducing the result of a TCO (optical coherence tomography) scanner into an artificial intelligence system.
"What we are trying to prove is that a scan of your eyes, together with a database of patients, can better understand the stratification of patients and the evolution of diseases," explains Bertrand Bodson, referring to eye diseases.
Today according to Bodson, AI can already influence medical treatments, reducing both the methods (x-rays, ultrasound) and the years of disease evolution; notes in this regard: “Artificial intelligence can really have identified the patterns associated with diseases. Even more. You can study images globally, all available images, to understand what kind of shapes anticipate certain patterns, to be able to act earlier. ”
AI has another field in which it has excelled in the medical sector; This is the so-called generative chemistry, which applies AI models to the synthesis of new medications. Virtual molecules are simulated with the chemical properties desired by the researchers generating algorithms under the rules of chemistry, so that they can produce many of those potential molecules with the desired chemical properties, which are then passed to experts, to decide which ones to try.
Undoubtedly, AI is a great help in the medical area for the treatment of high-risk patients as well as for disease prevention.