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**Artificial intelligence (AI) and machine learning** are also playing an increasingly important role in drug development. These technologies can be used to analyze large datasets and identify potential drug targets, predict the effectiveness of new therapies, and personalize treatment plans. AI and machine learning are helping to accelerate the drug development process and improve the outcomes for cancer patients. This is another area that has a lot of promise, and can help improve the rate of new drug approvals.
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Before administering antibiotics, it's crucial to **obtain blood cultures**. This helps identify the specific type of bacteria causing the infection. Blood cultures help to guide antibiotic choice. This is important because the antibiotic will be tailored to target the bacteria that caused the infection. This helps to prevent the overuse of broad-spectrum antibiotics, and also reduces the risk of antibiotic resistance. If the cultures are positive, this can help guide the course of treatment, so the doctors can narrow the antibiotics and better address the root cause of the sepsis. Time is of the essence in sepsis, so it's a balancing act. The medical team has to start antibiotics quickly to combat the infection, but they also want to identify the specific pathogen to choose the most effective antibiotic. Blood cultures also help to prevent unnecessary medications.
