Clinical trials saw massive changes during the pandemic-triggered lockdowns, as life science companies were forced to adopt automated data monitoring and shift to decentralized trials. Virtual clinical trial solutions are helping them prevent trial disruptions and cancellations by enabling seamless data extraction and monitoring, identifying inconsistencies, and building evidence-based decision making.
With the industry moving toward a patient-centric and decentralized approach to clinical trials, data capture, reporting, and monitoring will stay relevant and continue to grow in the new normal.
The industry’s rapid adoption of new clinical trial methods threw up varied challenges – especially in emerging markets like China, India, Africa and the Middle East - as the rules of data capturing and analyzing changed dramatically.
The current state of clinical trials
The success of any new drug that hits the market depends on its clinical trials, and seamless clinical data management is a cornerstone for informed decision making at every stage of the trial.
Data management enables companies to generate high quality, reliable, and statistically sound clinical data.
Clinical trials saw massive changes in the last year, as a need for automated data monitoring through software solutions was reinforced during the pandemic. The COVID-triggered lockdowns also forced biotech companies to shift to decentralized trials.
Decentralized clinical trial models have existed for many years, but were not widely adopted in emerging markets till the pandemic changed the dynamics of the industry and made it necessary for the method to be implemented at scale. Virtual clinical trial solutions became a prerequisite for drug developers to prevent trial interruptions and cancellations and to enable clinical trials to adapt and continue.
The pandemic also hastened the industry’s move towards digital innovation and automation, with organizations exploring the impact of AI, machine learning and other advanced technology on clinical trials. These technologies are emerging as new ways to extract data, monitor this data as it is generated, identify issues and inconsistencies in ongoing trials, and help generate evidence-based decision making.
Challenge of adapting to the new normal
The industry’s rapid adoption of a completely new way of conducting trials has created new challenges for researchers. The new processes, which are different from the traditional clinical trial models, capture and analyze data differently - data managers must adapt to these new methods rapidly.
Several questions come up for sponsors and CROs (contract research organizations):
- How do you recruit volunteers for virtual clinical trials?
- How do you ensure they take their medication?
- How do you ensure that the side effects they discuss during calls are accurate?
- How appropriate and suited are these clinical data services in emerging markets like China, Japan, India, Africa, and the Middle Eastern nations?
- How is the data getting monitored, and what are the industry directions that have to be implemented?
- What are the other competing trials in the same therapeutic area?
Clinical trial delays and failures have significant time and cost implications and can also negatively impact the sponsors and CROs. With increasing complexity and delays in study start-up, it is evident that an overhaul in management methods is necessary.
Digital clinical trial management
Wipro’s cost-effective SaaS-based Clinical Trial Management System (CTMS) is an effective way for companies to focus on data privacy and security. The system supports multi-center and multi-protocol studies, is highly customizable, fast to implement, intuitive to use, reduces the time to onboard new studies to 8-10 weeks, and brings down the total cost of ownership by 40%.
The feature-rich platform generates actionable reports and metrics in pre-configured templates for companies and CROs, is 21 CFR Part 11-compliant, and integrates with electronic data capture, interactive voice response, and randomization processes.
Wipro’s cloud-enabled SaaS solution automatically brings together various publicly available industry-defined data sources along with the internal databases, providing sponsors and CROs with insightful and interactive visualizations, which help them expedite clinical trial planning and feasibility assessments.
The solution plugs data-driven insights to provide a right start and a strong foundation, which has significant impact on clinical trial successes.
Some of the other features that the Clinical Trial Management Solution provides include:
Subject Matter Support: SMEs assigned for clinical studies resolve issues on operational systems and product usage.
Testing: Clients can author, review, and execute business document, technical test cases, and UAT scripts.
Business Access Management: The solution enables security management for systems to access, transfer or create operational data, including clinical trial management systems, project management systems, SharePoint, and EDC.
Reporting: It generates, reviews, and supports efforts to provide summary reports to end users.
Process Streamlining: Develops streamlined processes for user access, lab and site administration, core configuration, and URL management.
Analytics: Provides systematic statistics for the discovery, interpretation, and patterns for tracking different stages of the trial, helping clients in effective decision making.
Streamlining clinical trial processes
Wipro’s clinical trial management solution streamlines clinical trial processes.
The solution selects the best performing countries and sites
It builds complete site profiles, with therapeutic areas and indication experiences. It provides a detailed success/failure analysis and performance level insights.
It creates a consolidated knowledge repository
The system builds an integrated study of industry benchmark open data sources like trial registries, pubmed etc., and integrates easily with internal proprietary databases like CTMS, CDM, and eTMF.
Identifies and selects suitable investigators
The CTMS provides a 360-degree view of an investigator profile, performance analytics, and ranking based on prior experience.
Provides accurate patient enrolment forecast and trial match
The solution gives clients match incidence and prevalence data across geographic area vis-a-vis a specific therapeutic area, along with detailed drill down analytics of patient demographics across geographic areas.
Helps clients gain competitor intelligence
Once the system is deployed, it provides an objective analysis of previous trial failures and successes of competitors, a deep view and analysis of their previous, ongoing, and upcoming trials, as well as a list of associated sites and sponsors.
Toward a digital future
In a post-pandemic world, high quality of data management requires a huge effort in collating data, and many biotech companies do not have the capacity to do it on their own. Working with an experienced partner is emerging as an ideal and cost-effective solution.
Going forward, data capture, trial reporting, and monitoring will continue to evolve as the pharmaceutical industry looks to embrace the latest technologies and make clinical trial management seamless for all stakeholders.
Data management in clinical trials is also emerging as a perfect example of how AI and machine learning can transform processes, cut costs, and automate tasks that were done manually so far.
The industry is also witnessing a seismic shift towards a more patient-centric approach as well as a decentralized approach to clinical trials. In the long run, this will impact the industry in positive ways. The pandemic can only be considered a catalyst that hastened this change.
There are plenty of ways that your enterprise can benefit from adopting Wipro’s SaaS-based Clinical Trial Management System. To learn more about how Wipro can help in your transformation journey to seamless clinical trials, connect with us.
About the Author
Subhrajit Ghose has over 18 years of industry experience in Contract Research Organization/ Pharmaceutical and Biotech organization with expertise in clinical data management, operations and service management, operations improvement, and risk analysis and mitigation. He has been in several leadership roles across geographies and led many initiatives to drive improved operational efficiency and profitability for global clients.