It takes an average of 10 to 15 years and $2.6 billion for a drug to reach pharmacy shelves. While there are many steps in the process that contribute to this lengthy timeline and cost, no aspect of the process is more critical than proving the safety of a drug.
This guide analyzes how artificial intelligence – including machine learning – can be used by pharmaceutical and medical device companies to improve the clinical data review and cleansing process.
Since a patient’s health is at risk throughout the testing of a drug, as well as the life of a drug once it has been approved, companies must leverage the most advanced methodologies and industry tools to mitigate any risk to the public.
In an upcoming series of posts, I’ll discuss the importance of monitoring adverse events and safety signals to ensure patients are always kept safe, from research through post-approval. In the meantime, check out our latest guide on drug safety.