Discovering new drugs and treatment methods are the two fundamental factors driving the pharmaceutical and healthcare industry. The development of new drugs has historically been a very challenging task, and still, the efficacy of new drugs is questionable. Traditionally, pharma companies rely on clinical trials to test the effectiveness of new drugs, but this method is expensive, time-consuming, and questionable. With the advent of data analytics, the healthcare industry is betting on real world evidence to test drug efficacy during the drug development process. Real world evidence eliminates the limitations of randomized clinical trials (RCT) by providing insights into the performance of various drugs and its usage in real-world setup.
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Benefits of Real World Evidence
Derive Results from a Larger Dataset
It has generally been noted that a tiny percentage of patients with a certain disease enroll in traditional clinical trials. For instance, only 3% of potential patients volunteer to participate in oncology clinical trials. Real world evidence gathers claims, medical, HER, and pharmacy data from thousands of patients in real-time. This provides pharmaceutical companies with a significant data set to base their decisions on in order to come to an accurate conclusion.
Reduce Costs and Time of Clinical Trials
Conclusions based on findings from smaller data sets of clinical trials can be unreliable and misleading. Also tracking each patient can be costly and time-consuming. Many times, clinical trials get excessively challenging or face ethical issues, which can be tackled with real world evidence as it provides similar information with a comparable dataset.
Reduce Time to Market
Researchers and medical professionals can collect post-trial information in real-time to identify side-effects, adverse reactions, and medication errors. As a result, researchers can make the necessary changes to the drug in order to improve its efficacy. Such a process saves a lot of time which would otherwise be wasted in the data collection stage itself; thereby, reducing the time to market.
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Drug Personalization
Drugs and medicines affect each person differently due to variations in genome and genetics and external environmental factors. By gathering a multitude of patient-related data, real-world evidence can make it possible to sequence genomes and help pharma companies to decide the best medication for the target population.
Develop Cost-Effective Medicines
Insurance companies and government Medicaid programs spend vast sums of money on medicines. Real world evidence can help cut down such costs, which can then be used for other purposes. It can do so by analyzing large datasets to support evidence that a low-cost drug performs similarly with its high-cost counterpart.