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The Future of Artificial Intelligence and Pharmaceuticals

In the field of pharmaceutical research, artificial intelligence is used to perform tasks previously performed by humans. This technology has revolutionized how scientists develop new and innovative medicines. In 2017, Verdict AI surveyed businesses about the importance of artificial intelligence in their industries. Over 70% of the respondents said that it would be very important for their organizations to adopt it. According to a study conducted by Narrative Science, over 60% of organizations are using AI tools to identify opportunities for their innovation. This is very important for pharmaceutical businesses as it allows them to capitalize on new opportunities.

Creating New Drugs Fasters

A study conducted by MIT revealed that only 13.8% of the drugs that are submitted for clinical trials are successful. Furthermore, a pharmaceutical company can expect to spend up to $2 billion on the entire process to get approval. Due to the increasing importance of artificial intelligence in the pharmaceutical industry, many companies are now using it to improve the efficiency of their operations.

Through the use of AI, pharmaceutical businesses can now tackle difficult-to-treat diseases. In addition to finding new treatments for certain diseases, such as Alzheimer’s and Parkinson’s, AI can also be utilized to discover new remedies for rare illnesses. Unfortunately, pharmaceutical businesses typically do not focus on developing new treatments for rare diseases. This is due to the high cost and time involved in developing new medicines. Due to the increasing number of AI-based innovations in the field of medicine, interest in developing new treatment methods for rare diseases has also increased.

Improving Drug Adherence and Dosage

One of the most important factors that pharmaceutical businesses consider when developing new medicines is their patients’ adherence. This is because if patients do not follow the trial rules, their participation in the study will be removed. Another critical aspect of a successful clinical trial is the adherence of the patients to the treatment regimen. According to studies, machine learning could help reduce incorrect drug dosage by up to 50%.

Analyzing Data More Efficiently

Despite the increasing importance of electronic systems, clinical trials still rely on paper diaries. This method allows patients to record their medication usage and provide detailed reports about their adverse reactions. Aside from this, many companies still rely on fax machines to collect information about the patients in their clinical trials. A study by Cognizant revealed that about 80% of clinical trials could not meet enrollment deadlines. Also, one-third of the studies are terminated due to issues related to enrollment. Being able to extract and analyze the data collected from medical records is a top priority for the pharmaceutical and medical industries.