Despite significant technical advances over the past several years, a few clinical data issues remain hard to solve. Pharma companies of all sizes grapple with fragmented data, operational inefficiencies, and cost overruns in clinical trials. And while AI holds promise for improving clinical trial efficiency, few clinical trials utilize tools with such technology.

Clinical data challenges affect small- to medium-sized (SMB) pharma companies more acutely than the average Big Pharma. For an emerging start-up, unexpected delays or budget overruns could make it harder to secure the next funding round. Without funding, a promising therapy may not make it to Phase 2.

Based on internal research, we’ve outlined the top three clinical data analytics challenges SMB pharma face at the moment. And while there are no quick fixes, we do share realistic solutions.

Third place: Unrealized expenses
Lack of control over clinical operations leads to unexpected expenses for SMB pharma. Lack of control, whether real or perceived, is associated with lack of visibility. Project managers don’t immediately know whether staff are performing tasks in a timely manner or whether sites are meeting their goals. Data managers don’t discover anomalies until weeks after the fact. When  clinical operations cannot detect issues right away, they become more difficult (and expensive) to correct.

Second place: Total cost of ownership (TCO)
SMB pharma struggles to reduce TCO given the rising costs of clinical trial supplies, staff, and technology. Without a unified platform for clinical data acquisition, management, and analysis, sponsors spend too much time and energy implementing solutions utilizing multiple vendors. Large enterprises may not blink at taking a “best of breed” approach, but for an SMB pharma operating on limited resources, that wasted time has a big impact on budget. 

First place: Fragmented and disparate data
Integrating diverse clinical data from EDCs, EMRs, lab results, and heterogenous architectures leads to system failures and delays. When integration problems occur, IT teams must create workarounds and staff must spend extra time managing and cleaning data. Labor required to complete these tasks increases TCO.

The Solution: A Unified Clinical Data Analytics Platform

A clinical data analytics platform with data management capabilities gives SMB pharma the tools needed to improve operational efficiency with little increase to technology costs. Here’s how the right platform solves SMB pharma’s top three data analytics problems: 

• Regain control with near real-time data access
  The ability to access and analyze data in near real-time improves decision-making processes. Managers gain a clear view of site and staff activities, which allows them to act in the moment. Data managers are notified of possible errors and anomalies right away, so they can rectify issues before they become complicated. Clinical operations become more efficient through improved visibility and control, which helps SMB pharma stay within budget.
• Reduce TCO with easy data integration
  A centralized data hub like the Clinical Data Repository (CDR) from MaxisIT automatically standardizes structured and unstructured data—no manual fixes required. With data integrated, powerful analytics deliver robust insights that drive decision making. With data automatically ingested, cleaned, and standardized for near-instant insights, IT and data management staff are free to engage in high-value activities. The reduction in labor costs, combined with faster insights, helps reduce TCO.
• Conduct trial activities on a unified clinical data analytics platform
  Moving from a fragmented approach to a unified clinical data analytics platform resolves most of the data integration and visibility issues that can drive up costs and drive down efficiency. Delays caused by manual workarounds are eliminated, while the overall data pipeline from data capture to regulatory submission simply moves faster and more easily. 

CTRenaissance, the leading clinical data analytics platform from MaxisIT, includes the Clinical Trials Oversight System and Data Management Workbench. Together, they deliver a comprehensive suite of features for managing clinical trials with greater efficiency and accuracy. Here’s what you can accomplish with CTRenaissance:

• Accelerate study cycle times by avoiding manual reconciliation and data review
• Enable risk-based quality management (RBQM) approaches 
• Simplify data management by delivering standardized data for simple to complex trials
• Enhance operational efficiency and collaboration with AI-powered automation 
• Perform real-time risk assessment and mitigation 
• Strengthen regulatory reporting 

SMB Pharma Challenges Bottom Line

Clinical operational efficiency, cost effectiveness, and technology ease-of-use are issues that have persisted in clinical trials for years. Advanced data analytics platforms like CTRenaissance enable SMB pharma to conduct their studies with more control and simplicity than before. 

To see how CTRenaissance can transform your clinical trials, request a demo today.