Abstract:

The global pharmaceutical industry, especially in our country, which has traditionally taken a slow approach to adopting technology, is now undergoing rapid changes due to the development of several technologies. The prominent ideas in the pharmaceutical industry are accompanied by the use of artificial intelligence, blockchain, and 3D technology. The result of this research is data based on creativity and innovation that provides an overview of technologies and emerging knowledge-based companies in the pharmaceutical industry, improving strategic decision-making for the actors in this field. More than 90 percent of drugs that reach the clinical trial stage fail before entering the market. This failure rate discourages patients who are waiting for treatment and incurs significant costs that lead to increased drug prices. Artificial intelligence can put an end to all these problems and open a new window of science for pharmacists.

Designing and producing new drugs may take more than ten years, and the average research and development cost may reach up to 2 billion dollars in the early stages. Artificial Intelligence and the Pharmaceutical Industry

The use of artificial intelligence accelerates the drug discovery and development processes. Knowledge-based companies are exploring the use of these technologies to address various challenges in the pharmaceutical industry, such as automating and optimizing production processes, as well as designing effective marketing and post-launch strategies.

Patient identification is an important step in the drug discovery and development process, especially for conducting clinical trials. Artificial intelligence simplifies the identification of qualifying patient criteria and also makes the group identification process faster and cheaper.

Advantages of Artificial Intelligence in the Pharmaceutical Industry

Reviewing and predicting the effects and potential side effects of drugs: Using artificial intelligence algorithms, it is possible to predict how a manufactured drug will act in the human body and what impact it will have on pathogenic factors.

The use of artificial intelligence is not limited to drug interactions; it can also be used to identify potential side effects; it can predict which disease with what characteristics is more likely to experience which side effect.

Designing and producing based on data: For drug design, artificial intelligence uses machine learning to analyze data related to genetic information, drug production processes, chemical reactions, the effects of drugs on cells, side effects of drugs used by patients, medical histories, and laboratory results of studies on human tissues and cells. After analysis, the most suitable chemical compound and treatment method for the disease under study are proposed by artificial intelligence, and the drug manufacturing process begins.

Using artificial intelligence methods, the potential of thousands of chemical compounds for treating a specific disease can be evaluated.

For designing and producing new drugs, it may take more than ten years, and the average research and development cost may reach up to 2 billion dollars in the early stages.

Diagnosing diseases with artificial intelligence algorithms: The use of artificial intelligence in accurately diagnosing diseases is one of the most effective and innovative methods of disease diagnosis. With this method, the accuracy of disease diagnosis significantly increases and can lead to reduced costs and improved quality and efficiency of patient treatment. For example, deep learning algorithms can be used to detect cancer in X-ray images.

Currently, advancements in artificial intelligence, particularly the development of deep learning algorithms, have led the healthcare industry to adopt artificial intelligence methods in several areas from management to drug discovery.

Data analysis and improving production processes: By using artificial intelligence, a vast amount of information about the structure of drugs, their biological functions, and patient data can be analyzed, and pharmaceutical production processes can also be improved and optimized. For example, reinforcement learning algorithms can be used to optimize drug production processes.

Eliminating human error in the marketing and sales system of drugs with artificial intelligence algorithms

In the current state of the pharmaceutical industry in the country, the drug distribution system and their sale and delivery to customers, who are practically patients, heavily rely on manual processes and human expertise, which can lead to inefficiency, delays in service delivery, and increased human error in providing correct and practical services to patients. For example, in the pharmacy subprocess, filling a prescription involves several manual steps, such as interpreting the prescription, distributing the drug, and checking the dosage and frequency of use throughout the day. These manual processes are prone to errors and may be time-consuming.

Moreover, the traditional pharmacy system lacks the ability to customize medication regimens for each patient, which may limit the effectiveness of drug treatment. However, by using artificial intelligence-based tools, pharmacies can enhance their performance and overcome these limitations. Artificial intelligence can help automate various aspects of workflows in pharmacies, from reading and interpreting prescriptions to distributing drugs, reducing the risk and human error, and improving the efficiency of service delivery to the patient community.

By analyzing large amounts of patient data, artificial intelligence can help pharmacists develop personalized medication regimens tailored to the unique needs of the patient and their medical history. While the traditional pharmacy system has been effective in providing necessary medications to patients, it has been limited due to manual processes and lack of customization. The use of artificial intelligence-based tools can overcome these limitations and make the pharmacy system more efficient, accurate, and personalized, ultimately leading to better outcomes for patients.

Conclusion

Identifying new opportunities and emerging technologies for the early implementation of ideas in business leads to a competitive edge over other pharmacists.

Considering the daily advancements in technology in the pharmaceutical industry, artificial intelligence can create a new gateway to a brighter future for patients. This technology can be beneficial in reducing costs, saving time, producing new drugs, and improving clinical study conditions.

Artificial intelligence is the future of the pharmaceutical industry, and companies that invest in this technology will have a special competitive advantage in the future. In the near future, artificial intelligence will widely enter the pharmaceutical industry and lead to advancements in various fields, including biologics in the biotechnology sector.

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