The importance of data analytics for enhanced clinical research

The modern pharmaceutical landscape boasts an abundance of high-quality data, which went years without being used for greater advantage to businesses and the people they serve. Data and analytics, however, have started to transform this space, turning extensive, comprehensive datasets into useful intelligence, thanks to a plethora of new technologies and the ease with which modern personal medical devices, social media, and electronic medical records are accessible. 

Businesses in the pharmaceutical and life sciences sector can use this data to demonstrate the effectiveness and value of novel medications and medical devices, as well as to guide strategic decisions, encourage further product innovation, and strengthen ties with important stakeholders and clients.  

The challenge here lies not in collecting this data, but ensuring it is harnessed and curated effectively, and strategically used to create competitive advantage. 

Increasing value – and not just monetarily 

NWEH has been a consistent proponent of data analytics and made significant investments in the establishment of cutting-edge analytical tools and internal expertise. The top 20 pharmaceutical companies are benefiting increasingly from improvements in analytical techniques that rely heavily on machine learning and artificial intelligence. 

In addition, modern data analytics techniques have proven crucial for improving real-time insights, recruitment and safety monitoring of patients within clinical trials, and the development of more individualised medicines. 

Many in the industry are implementing innovative data analytics techniques that will be used to analyse clinical trial data in real-time. Provided compliance with any required ethical approvals, trial stakeholders will be able to near-spontaneously inform trial design changes in order to maintain overall efficiency and safety. Additionally, the industry will witness the development of more individualised medicines as advanced data analytics improves our capacity to recognise patient subgroups that react differently to treatment. As a result, it is possible to design clinical trials specifically for subgroups and greatly optimise and customise treatments to benefit a more diverse population. 

Furthermore, it is possible to identify potential patients who will benefit from a particular treatment by using key data analytics techniques. These findings can then be used to quickly locate hotspot areas and the communities that are most impacted, as well as efficiently engage with these patients for recruitment into clinical trials. 

Rapid, unrestricted data sharing 

The COVID-19 pandemic was a major factor in the rapid surge of enhanced data analytics, in which several companies were able to develop the fastest vaccine ever created. Relevant data in the studies required quick analysis and free exchange between pharmaceutical companies, governmental organisations, and data analytics firms. Free-flowing data sharing, as seen during the pandemic response, makes the development of drugs easier by streamlining industrial R&D processes. And with the available information, researchers have a better understanding of the recipients of the product. This makes it possible for trials to perform more safely, with greater accuracy, lower expenses, and in less time. 

A strengthened offering 

Pharmaceutical firms today are eschewing conventional methods and adopting digital transformation and pharmaceutical data analysis on a much larger scale. This decision enables them to comprehend and meet the needs of both their stakeholders and customers. By employing key data analytics, you can not only improve your understanding of trial results, but vastly enhance your supply chain efficiency by easily validating data, detecting anomalies, benchmarking operations, and rapidly accessing reports. 

Moreover, data analytics for pharma development offers the crucial capability of real-time optimisation and improved inventory management, freeing up man-hours which otherwise would have been spent tracking and monitoring business operations. 

The use of data in developing pharmaceutical products is paramount, and it helps to prevent health issues and strengthen the patient care sector. As we enter the era of post-pandemic clinical trials, ensuring collaboration between the pharmaceutical industry and data analytics partners will prove to be a key facilitator to the development of quality treatments and happy, healthy and safe patients.