AI at the forefront of medicines

AI at the forefront of medicines uses algorithms that can analyze large blocks of scientific and medical data that they can use in the development of new medicines for medical treatments and therapies.

AI at the forefront of medicines and medical research aims to generate new computer tools for the innovation of drugs and molecular targets, using computer engineering and artificial intelligence techniques.

Likewise, with new advances in computer science and informatics, artificial intelligence is quickly becoming an integral part of modern healthcare.

Currently, the pace of research has increased towards doctors, helping them make better decisions for the application of treatments.

That is why AI can provide personalized recommendations in real time to patients 24 hours a day.

All of this, through a healthcare system that could offer patients 24-hour access to an AI-powered virtual assistant that could answer questions based on the patient’s medical history and personal needs.

Drug discovery is often one of the most time-consuming and expensive processes in drug development.

That’s why AI at the forefront of medicines could help reduce development costs mainly in two ways: better drug designs and finding promising new drug combinations.

With AI, they could meet many of the big data challenges facing the pharmaceutical industry.

IBM’s new synthetic data generation method and phased training protocol enable companies to update their large language models with task-specific knowledge and skills. , eliminating some of the theory when training generative AI models.

AI in the field of new drug innovation has been influential in achieving a series of advantages such as the following:

– Accelerate research and search for new medications.

– Reduce the percentage of failures in clinical trials.

– Reduce research and development costs.

Consequently, AI is considered the main objective in the development of medicines, it is to be able to predict the way in which certain molecules may behave and study the probabilities that they can give rise to a new medicine.

Likewise, the aim is to speed up the discovery process of new drugs to reduce costs and ensure that they reach patients as soon as possible.