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Welcoming AI in the Clinical Research Industry

Artificial Intelligence (AI) has created a space for itself in nearly every industry. Due to its high precision levels and less error-making tendency, integration of AI has proved that, along with machine learning algorithms, it can take the product to its potential with great efficiency improvement. The healthcare industry, being one of the most sensitive and responsible industries, can make use of AI in the refinement of medical procedures.

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Welcoming AI in the Clinical Research Industry

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  1. Welcoming AI in the Clinical Research Industry Artificial Intelligence (AI) has created a space for itself in nearly every industry. Due to its high precision levels and less error-making tendency, integration of AI has proved that, along with machine learning algorithms, it can take the product to its potential with great efficiency improvement. The healthcare industry, being one of the most sensitive and responsible industries, can make use of AI in the refinement of medical procedures. Clinical trials using Artificial Intelligence technology Conventional methods of conducting clinical trials have reached their limits, which are observed through delays in clinical trial outputs, patient retention issues, and their expensive nature. Artificial Intelligence has the ability to add to the effectiveness and safety of clinical trials, with the goal of bringing optimizations to the processes, Drug testing: The drug would be developed using already available patient data collected through clinical trials over a period of time. Clinical trials have the ability to bring down the cost of clinical trials. Patients can relax knowing that they will have access to clinical trial healthcare even if they are not physically present at the trial site. This would accelerate the off-site monitoring, especially of weaker patients that require quarantined measures. Automations using data analytics: An automated improvement in clinical trials aids in patient care during clinical trials. All the raw data would be collected and transformed into insightful information for the purpose of better understanding diseases. A few resultant advancements would include: Corrections to recruitment design inefficiencies, resulting in large-scale recruitment Precision in evaluation and definition of data with an increased efficiency rate against existing information. Having accessible databases that would keep records of patient matches on the basis of their health status and treatment tolerance levels. Helps in bridging gaps between clinical trial sponsors and facilities by accelerating business reciprocal actions. Conclusion There is a wide scope for artificial intelligence in clinical trials. The clinical research and clinical trials industry has expanded beyond its current boundaries with artificial intelligence. Through the sharing of relevant information using decentralized clinical trials, AI could increase the efficiency of clinical trials while adhering to medical protocols.

  2. Pharmacovigilance courses Regulatory affairs in clinical research

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