April 19, 2024


Epicurean computer & technology

Data-Driven Life Science Digital Solutions: Improving Your Strategies With Real-Time Insights

Digital technologies in the public-health response to COVID-19 | Nature  Medicine

The life sciences industry has been one of the most hesitant to embrace the digital revolution compared to other fields. This slow adoption can be attributed to a number of factors, one being that life-science businesses viewed technology more as something that merely provided fundamental capabilities rather than an advantage over their competitors. In this day and age, everything has gone digital, and life sciences must also follow suit. They can work with professionals such as Sciencia Consulting- experts in life science marketing.

But these days, especially after the COVID-19 pandemic, life sciences are now incorporating new digital technologies into almost all aspects of their work, even marketing operations. In fact, according to a report published by Deloitte, more than sixty percent of companies in the life sciences industry have already made significant investments in artificial intelligence (AI) technologies.

But how exactly is real-time analytics improving life science digital solutions and market development strategies?  Let’s find out!

  1. Making Way For Personalized Medical Treatments

The practice of personalized medicine, also known as precision medicine, includes classifying patients into subgroups determined by their genomic information. This ultimately results in more tailored treatment and improved health outcomes. But to make customized medicine a success and figure out the therapies that should be administered to patients, terabytes of clinical and user-generated data will need to be collected, analyzed, and integrated appropriately.

Using advanced real-time data analytics is one of the most effective ways to make sense of all of this data quickly. When it comes to precision medicine, data analytics can be utilized by concentrating on patient diagnosis, the discovery of biomarkers, prognosis, and disease subtyping. It is possible to incorporate data in real-time from wearable devices, implanted devices, electronic health records (EHRs), and multi-omics.

  1. More Effective Clinical Trials

Additionally, businesses operating in the life sciences sector are turning to technology to guarantee that clinical trials generate quality data that is devoid of mistakes, inconsistencies, outliers, and misreported occurrences. The procedure for the approval of drugs is going to be sped up. However, the most significant barrier has been the enormous amounts of data that have been collected during clinical studies, which are growing at an exponential rate.

Data analytics can be used to evaluate massive amounts of data from clinical trials, determine which information is important, and get insights from the vast amounts of data. It can also help control electronic patient hospital data coupled with a patient’s past medical records to locate the appropriate people for a particular trial, which can save time and increase the cost efficiency of the process.

  1. Improved Risk Management

In the field of life sciences, risk management is a procedure that is essential and non-negotiable at the same time. At least some businesses are issued warnings by various regulatory organizations around the world annually. Data analytics contributes to the establishment of risk management as a process that is ongoing and constant. Data analysis from product launch consulting enables one to get correct insights, forecast problems before they even materialize, and take preventative measures to avoid those risks.