Analyzing and Using Technology in Managing Data in Clinical Trials

¶ … Technology Aid in the Process of Clinical Trials

Capstone Project title: Using technology in managing data in clinical trials

We will start our paper by discussing "Clinical Data Management" or CDM, which is an important phase in clinical research. It is a process through which reliable, high-quality and statistically accurate data is generated from clinical trials. This drastically reduces the time taken by the process, from when drugs are developed to the time they are marketed. The CDM team members play an active role throughout the process, from the beginning to the end. They are required to have sufficient knowledge about the maintenance of CDM processes quality standards. There are several procedures in the process such as Case Report Form (CRF) and its annotation, data entry, designing a database, validation of data, management of discrepancies, medical coding, extraction of data and data locking. During a trial, these procedures are assessed regularly to ensure that they meet high standards. Currently, there is increasing pressure to improve the standards of CDM so that they can meet the requirements of the regulatory body and beat the competition through faster commercialization of the products (Krishnankutty et al., 2012).

Body

Industry Preparedness

We will argue that the industry seems ready to embrace the drivers of technological change. For instance, a recent webinar by FDA described it, the biopharmaceutical industry is very slow to the adoption of electronic solutions which have the possibility to change the way clinical trials are conducted. However, Contract Research Organizations (CROs), some of the sponsors as well as investigative sites are convinced that a tipping point for the industry is close. To support this, a research carried out in the eClinical solutions market shows that a 13.8% annual growth rate is expected in the projects from 2014 to the year 2020, surpassing the 2014 estimate of $3 billion by 3.52 billion. Cloud-based solutions were included in this study (Morrison, 2015). The industry seems ready to embrace what many consider to be the drivers of change.

Big Data and Accessibility

Another argument we will put forward is that technology or cloud computing eases access and allows bid data analysis. Access is very important as far as effective data management in clinical trials is concerned. Accessing information fast and with ease allows those in charge of administration of the clinical trial to get what they require so that they can produce analysis and results that are accurate and concise. Particularly in clinical trials that are large, the large amounts of data used can make the process of data collection more stressful. The best part of big data use is cost reduction and optimization. Big data use provides the best data collection and analysis methods to those conducting clinical trials.

Enhanced Information Management

Another key argument we plan to put forward is that online disease management programs lead to key technological advancement. They ensure there is convenience for the medical practitioner as well as the patient and can be represented in another format easily for the purpose of clinical trials. A study conducted in 2013 showed how positive results are achieved through online disease management programs. Led by a nurse, a health team including different disciplines can manage a group of patients with diabetes through an online disease management program. The study stated that in a six-month period, there were greater reductions in AIC in INT patients. However, the differences did not hold for one year (Tang et al., 2013, p. 526). The management of symptoms is a very important part of clinical trials as well as distinguishing the effective medications and those that are not. This is important in the production of a clinical trial that is successful. It cuts the cost incurred and paves way to better information management through online access, which is easy and convenient.

New Solutions

Our last point will be the introduction of novel solutions to problems. Technologies such as eSource, ETMF, clinical analytic interfaces that use next generation technology and RBM which are supported by the cloud are gaining acceptance with the increased use of the cloud. These technologies are important and can help advance clinical trials (Morrison, 2015).

Conclusion

TECHNOLOGY USE IN CLINICAL TRIALS 1