The use of artificial intelligence (AI) is growing in all sectors of society, and in the pharmaceutical industry, it represents a new revolution in the design and development of new drugs to speed up the process.
AI is a technological system that includes many networks and advanced tools that mimic human intelligence. It uses software that can interpret and learn from available data to make independent decisions to achieve specific goals. In its applications, AI is able to perceive and recognize patterns, remember, identify and optimize processes and controls.
In the field of healthcare, there are already some tools that have been developed based on artificial intelligence systems, for example, using the IBM Watson supercomputer, a tool has been developed to help in the analysis of patient data, resulting in treatment strategies. cancer. The system can also be used to quickly detect diseases, as evidenced by its ability to detect breast cancer in as little as 60 seconds.
You can imagine the involvement of AI in the development of a pharmaceutical product from the beginning of drug development to its use in a patient. This technological tool can determine the appropriate therapy for the patient; and manage the resulting clinical data and use it for future drug development. In addition, it helps in making marketing, sales and investment decisions for pharmaceutical products.
The drug discovery and development process can take more than a decade and cost an average of US$2.8 billion. AI can recognize lead compounds and those most likely to succeed, as well as enable faster target drug validation and drug design optimization. In fact, several biopharmaceutical companies such as Bayer, Roche and Pfizercollaborated with technology innovation (IT) companies to develop AI platforms for therapeutic discovery in areas such as immuno-oncology and cardiovascular disease.
AI applied to manufacturing processes in the pharmaceutical industry has also been shown to be effective in improving production efficiency and quality by automating certain processes and has been successfully applied in the synthesis and production of drugs used for various indications, such as: sildenafil (for erectile dysfunction), diphenhydramine (antiallergic) and rufinamide (anti-epileptic).
Despite the benefits, this technology faces some major information processing challenges such as scale, growth, diversity, and data uncertainty. There are currently no fully AI-based drugs on the market. Certain challenges remain regarding realizing this breakthrough, but it is highly likely that AI will become an indispensable tool in the pharmaceutical industry in the near future.