How does artificial intelligence lead a new revolution in the pharmaceutical industry?

While the rate of digital transformation accelerates in different sectors, the pharmaceutical industry stands on the threshold of a historic turning point led by algorithms and smart systems. Artificial intelligence is no longer just an instrument in laboratories, but rather a driving force that draws the characteristics of the process of developing medicine of their roots, from the discovery of vehicles to the patient’s treatment of the patient. In recent years, the role of artificial intelligence has increased to become the most prominent candidate to revolutionize the design and testing of medicine, to the extent that some experts do not exclude that we will see the first medicine completely developed by algorithms without direct human intervention. But this technical mutation is not limited to speeding up time tables, but rather defines how we develop the medicine and those who develop it. Thanks to these modern techniques, the drug industry can become more effective and can address their incurable diseases at an unprecedented velocity at a lower cost, which opens the door for a new era in medicine in which artificial intelligence is saved, as traditional contracts could not. 1) How does the digital revolution start in the drug industry? The development of medicine is traditionally based on determining what is known as the ‘molecular purpose’, that is, protein or biological future associated with the disease, and then scientists begin to test thousands of chemical compounds that can deal with this purpose in the hope of achieving an effective treatment. But this model, based on experience and errors, is a retreat before the rise of artificial intelligence that has changed the rules of the game. The pharmaceutical industry is today in a real digital revolution led by the capabilities of artificial intelligence, which are able to quickly and accurately analyze large amounts of genetic, chemical and clinical data, enabling people to determine new therapeutic goals and develop promising pharmaceutical vehicles with a much lower cost of traditional methods. This revolution depends on advanced algorithms, the most prominent techniques of machine learning and deep learning, which enable smart systems to predict how vehicles interact with high precision biological goals. Instead of performing thousands of experiments in laboratories, these digital models can shorten the initial siphtheria by simulating interactions within the computer, reducing the need for expensive experiences and time consumption. Artificial intelligence skills are not limited to the acceleration of the discovery, but rather extend to the ability to detect hidden ties between biological paths and the development of disease. These links, which can miss even the most experienced scientists, help design medicines that target the disease at an unprecedented molecular level, which increase access to effective and adapted treatments. 2) Is artificial intelligence in shortening the years of the development of the middle to a few months? The development of new medicines has always been associated with a long and difficult path that usually extends for long years of research and experimentation, but artificial intelligence instruments have radically changed this comparison. Advanced algorithms provide an unprecedented ability to analyze large amounts of chemical, biological and gender data, which enables the detection of promising therapeutic compounds effectively and quickly exceeds traditional means. The experience of the “Excientia” enterprise is a tangible example of this transformation, as it could develop a new medicine connection within 12 months, instead of the traditional average of 4.5 years, through artificial intelligence -algorithms specialized in the design of medicine and expect its effectiveness. It also indicates that artificial intelligence can reduce the time needed to produce new medicines and can investigate it by 40% to 50%, leading to a reduction in costs at these stages by up to $ 26 billion annually. Artificial intelligence can also reduce the duration of clinical research to half or more, reducing its cost by approximately 28 billion, by automating manual tasks and analyzing statistical data faster and more accurately. 3) What are the other benefits that artificial intelligence offers to the drug industry? The benefits of artificial intelligence are not limited to the discovery of new medicines, but also extend to the action of old medicine for new therapeutic purposes. Ozmpic, originally developed for Type 2 diabetes, was approved as an effective treatment for obesity, in a step that represents one of the direct applications for analyzing algorithms of disease paths and vehicle effects. Experts confirm that this expansion of the use of artificial intelligence will not be limited to reducing costs or accelerating the performance, but that it will allow more effective medicine, and will reach it in the record time to the market, increasing innovation in the pharmaceutical industries and causes a qualitative shift in the global health care system. 5) How do regulatory authorities handle medicine that people did not create? The most important regulatory bodies such as the American Food and Drug Administration and the European Pharmaceutical Agency handle medicines developed by artificial intelligence within the same traditional legal frameworks, as there is still a separate license path for this category of medicine. However, the accelerated developments have urged these bodies to issue documents and draft guides to explain how artificial intelligence techniques in the pharmaceutical development phases, while maintaining strict safety and efficacy standards. These bodies require the commitment of companies developed to the valid scientific and organizational practices, regardless of the use of artificial intelligence in design or manufacturing. It also emphasizes the need to provide audible and transparent data and outputs and can be trusted. In Europe, the European Pharmaceutical Agency has issued an organizational article confirming that any artificial intelligence system used in the license files should be subject to a risk -based evaluation, including its function and its use, with the full commitment to the rules of data quality and safety. Technically, the regulators are asked to provide accurate information on the used algorithms, including the structure of the model, the training methods and the sources of data used. The focus is on evaluating transparency and the ability to explain, especially in cases where mysterious artificial intelligence algorithms are used, where the organizational bodies need clear justifications to no longer use explanatory models, and an extensive documentation of how to develop algorithm and deal with data. The regulators also attach very important to the issue of potential prejudices in data and ensure that algorithms do not reflect or improve prejudices against certain groups. It is also necessary to document the detection capacity for each step in the development of the model, including the dates of training and versions used and to verify performance by independent data. The US Food and Medicine Administration and the European Pharmaceutical Agency do accurate overviews of any use of artificial intelligence during clinical trials or results, and companies are required to deliver clear protocols that show how the algorithms influenced the course of the study or its results. The use of artificial intelligence in manufacturing or pharmaceutical vigilance is also subject to strict requirements related to quality and accountability. In short, the regulators are not opposed to the use of artificial intelligence in the development of medicine, but they need complete commitment to safety, transparency and accountability standards, without providing special facilities just because the drug was created by algorithm.