Don't miss our upcoming virtual workshop with John Snow Labs, Improve Drug Safety with NLP, to learn more about our joint NLP solution accelerator for adverse drug event detection. The World Health Organization defines pharmacovigilance as "the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine/vaccine-related problem." While all medicines and vaccines undergo rigorous testing for safety and efficacy in clinical trials, certain side effects may only emerge once these products are used by a larger and more diverse patient population, including people with other concurrent diseases. To support ongoing drug safety, biopharmaceutical manufacturers must report adverse drug events (ADEs) to regulatory agencies, such as the US Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) in the EU. Adverse drug reactions or events are medical problems that occur during treatment with a drug or therapy.

Safety, efficacy, speed and costs must all be prioritized and balanced in the delivery of life-changing therapies to patients. A drug that's quickly and cost-efficiently delivered to market, but isn't effective and safe is unacceptable. An effective, safe drug that doesn't get to patients in time to save lives has failed those who needed it most. When it comes to patient health and safety, there can be no compromises. Fortunately, in a world with abundant data and advanced analytics, we have more tools than ever before to optimize this balance for the betterment of patient safety and outcomes.

Over the past few years, the world has witnessed some of the greatest medical advancements and technological innovations. The human race is set on the path to development that will lead to brightest of the future. Scientists and innovators around the world are coming with breakthrough discoveries and innovations in every field of life, especially the healthcare industry, medical research, and hospitals management. The days of pain-staking surgeries, long treatment procedures, limited resources, and techniques are long gone. With the advents in artificial development and the machine learning algorithms, medical research and healthcare industry have reached the epitome of development, creating a path for humanity to counter every disease and health issue.

Big Blue has found yet another business application for its precocious cognitive computing system. IBM Watson Health is collaborating with the biopharmaceutical company Celgene to develop a new platform for evaluating the safety of drugs--both before and after they hit the market--the two companies are announcing this morning. The new offering, "Watson for Patient Safety," will gobble up anonymized medical records, claims data, and millions of electronic submissions to the FDA about potential drug side effects (known as individual case safety reports) to see if it can learn about the hidden dangers of medicines before they become too costly. The problem is one of the toughest in drug development. Many chemical agents (and maybe even most) interact with more than one "target"--meaning that if a drug has a molecular effect to begin with, it very likely will have one or more side effects.