The clinical research field has seen many developments and it has come a long way in using technology to ensure accuracy and speed of the analysis of research data. However, there are many challenges related to clinical trials and their data management that need to be addressed. Leon Surgeon talks about the challenges and solutions presented in the white paper Addressing the Challenges in Clinical Development with Data-Driven Strategies.
Any life saving drug or treatment that comes into the market, passes through many phases of research, experimentation, and analysis. Each phase requires a lot of data management – collection, verification, integration – and analysis in order to draw appropriate conclusions. Sounds pretty linear, right? It’s not. Any one from the life sciences industry will tell you that launching anything new in the market is a complex process, filled with delays and redundancies.
Of late, the challenges faced by all big pharmaceutical companies have multiplied. With technological advances and worldwide acceptance of clinically tested drugs and treatments, it should have been easy to get new treatments into the market. Instead, the life sciences industry faces many challenges related to clinical trials:
- Tighter regulation: Regulatory agencies across the world like the FDA and EMA have laid down stringent guidelines about how clinical trials need to be conducted. As compliance is essential for any drug or treatment to be approved for the mass market, the clinical trial process has become both complex and more expensive.
- Increasingly complex processes: A system of checks and balances is crucial to ensure patient safety; however it adds to the complexity of the process. It is no longer possible to manually manage data at any stage, as each aspect needs careful documentation and verification.
- Rise in costs: Not just regulation and complexity, other factors like finding willing participants, recording and verifying collected data, keeping track of all data sources, and pressure for commercial success – all contribute to the ever-increasing costs.
So how do we get past these challenges? We use technology in a manner that truly makes a difference.
- Centralized approach: One way to make clinical trials less expensive and to speed up the process is to use the centralized approach of managing data. Instead of recording data at different sites, we link the databases to collect and manage centrally. This saves time in collating data and of course eliminates redundant tasks like re-entry and re-verification of data.
- Reduce delays with strategic operations management: Even a day’s delay in a clinical trial can run up a bill of millions of dollars. To avoid this catastrophe, it makes sense to deploy strategies that are focused on keeping all players in the clinical trial process – sponsors, CROs, IRBs, regulatory bodies – invested in finishing the study in time.
- Choose the right data solution: All the steps that you will take to ensure a speedy and fruitful clinical trial will mean nothing if the data management and data analytics solution chosen by you is not equipped to handle your data requirements. Typically, organizations have existing data management solutions and they buy new solutions based on growing requirements. Eventually, they end up having many different and disparate data sources, making it almost impossible to integrate them on one platform. If the data from all sources does not merge properly, the analytics will not be accurate and will compromise the clinical trial results. Hence, it is important to find a solution that is truly flexible and customizable.
In the last decade or so, the clinical research field has seen many developments and it has come a long way in using technology to ensure accuracy and speed of the analysis of research data. With big data technologies in the picture, data-driven driven solutions have taken center stage. Does this mean we have found the road that will lead us to the market faster? Take a look at this white paper “Addressing the Challenges in Clinical Development with Data-Driven Strategies” and there’s a good chance you will find your answer.
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