Analytics for Contract Research Organizations
Features, Tools, Costs
Since 1989 in data analytics and since 2005 in healthcare IT, ScienceSoft overviews the core and advanced analytics features, essential integrations, key development steps, and costs of custom CRO analytics solutions.
Analytics solutions for contract research organizations consolidate data on clinical trials, laboratory tests, compliance consulting, and other services provided by CROs. They help to optimize trial efficiency, ensure regulatory compliance, enhance data accuracy, and enable informed decision-making.
- Implementation time: 2 – 6 months for an MVP.
- Costs: $30,000 – $1,000,000, depending on the solution's complexity. Use our free online calculator to get a ballpark estimate for your case.
- Core integrations: a clinical trial management system (CTMS) with electronic data capture (EDC), an EHR/EMR, a laboratory information management system (LIMS), an interactive response technology (IRT) or randomization and trial supply management (RTSM) system, a CRM, public clinical trial registries, trial patient recruitment software, patient-facing software.
Analytics for Contract Research Organizations: Features in Demand
Core Integrations for a CRO Analytics System
- Clinical trial management system (CTMS) + EDC — to enable informed study planning based on historical trial data; to monitor current study progress; to get resource and enrollment forecasts.
- EHR/EMR + PACS — to identify trial-eligible patients; to get RWE data; to enable longitudinal data analysis.
- Laboratory information management system (LIMS) — to monitor the operational performance of labs; to identify trends and correlations in test data; to perform pharmacokinetic and pharmacodynamics modeling.
- Interactive response technology (IRT) or Randomization and trial supply management (RTSM) — to optimize IP distribution and transportation; to enable more accurate longitudinal data analysis (due to the use of randomization data).
- Remote patient monitoring software (RPM) — to get more accurate insights into treatment influence and enable timely adverse event detection and alerting.
- CRM — to get insights into sponsor sentiment and prevent churn; to optimize patient recruitment and retention strategies.
- Financial management software — to get insights for efficient financial management, including budget planning and tax management.
- Public clinical trial registries — to get third-party trial data for building highly accurate forecasts (e.g., for enrollment, required resources, possible outcomes).
Development of an Analytics Solution for CROs: Key Steps & Best Practices
Development of analytics software for contract research organizations is focused on adapting to each CRO’s unique business processes to deliver analytics capabilities that enable informed decision-making for increased profitability and quality of provided research. With 19 years of experience in healthcare IT, ScienceSoft outlines the key steps and best practices we rely on to build analytics solutions for CROs.
1.
Business analysis and requirement engineering
At this step, business analysts conduct interviews with a CSO/COO, clinical research coordinators, clinical research associates, biostatisticians, and other stakeholders to translate business goals into software requirements.
During interview sessions, ScienceSoft also focuses on eliciting the compliance requirements for the software-to-be (e.g., HIPAA, FDA 21, CFR Part 11). If we see that the target system is highly complex, we recommend starting with a proof of concept (PoC) to verify solution feasibility. It can also be viable to go for an MVP, gather early user feedback, and develop a full-featured version with the relevant adjustments.
2.
Technical design
At this stage, the software engineering team decides on the integrations, architecture components (e.g., a data lake, a data warehouse), and techs to enable the required analytics capabilities.
The solution can be built using multiple suitable services, platforms, and tools (e.g., Azure Synapse Analytics and Amazon Redshift as a data warehouse, Apache Airflow and Informatica for data orchestration). We carefully compare the suitable options and pick the optimal tech stack that will be the easiest to integrate with the existing systems and offer the lowest TCO in the long run.
3.
UI/UX design
To tailor analytics dashboards to the needs of particular user roles, UI/UX designers build user personas and utilize them for mapping role-specific user journeys. E.g., clinical project managers and CRAs may need to be able to easily shift between trial- and site-specific graphs and charts for comprehensive monitoring (e.g., of resource allocation, enrollment dynamics). C-levels are likely to benefit from static dashboards that provide a clear and concise view of the organization’s operations and performance.
Following our best practices for UI/UX design, we often audit the software our clients already have in use (e.g., CTMS, CRM) and replicate the familiar tools and interface in the analytics solution. It helps users to adapt to new software more smoothly.
4.
Development, QA, and deployment
It is a good practice to conduct testing in parallel with development. This allows development and QA teams to establish smooth collaboration, prevent issues early on, and achieve zero critical defects in production.
ScienceSoft uses a combination of best practices for software cost optimization. For example, we create custom code only when there are no proven third-party components that can be used. This is often the case when there is a need to integrate custom or legacy systems or build ETL pipelines with complex data transformation rules. We also design CI/CD pipelines, follow our well-established DevOps practices, and utilize feasible QA automation, all of which allow us to reduce development costs by up to 78%.
What makes ScienceSoft different
We achieve project success no matter what
ScienceSoft does not pass off mere project administration for project management, which, unfortunately, often happens on the market. We practice real project management, achieving project success for our clients no matter what.
Costs of Developing an Analytics Solution for a CRO
The cost of developing an analytics solution for a CRO can vary from $30,000 to $1,000,000+. The exact figure largely depends on the number of service lines (e.g., each line requires a dedicated data model, unique analytics features, and integrations) and analytics complexity (e.g., ML/AI and big data analytics as higher-tier cost factors).
|
Basic solution |
Solution of medium complexity |
Advanced solution |
---|---|---|---|
The number of service lines the analytics solution should cover
?
Service lines may include early-phase development, clinical research, laboratory testing, data management, regulatory compliance consulting, and other services. |
One service line |
Two to three service lines |
A full suite of CRO service lines |
The number of simultaneous projects
?
More projects will require higher solution scalability. |
Up to 10 projects |
Up to 50 projects |
Up to 100 projects |
Geographic reach
?
Possible location-specific cost factors include the need to enable compliance with different regulations and data standardization efforts (e.g., for currencies and date formats). |
Single country/state |
Multiple countries/states |
Multiple countries/states |
Data complexity
|
Structured (e.g., relational databases, CSV, Parquet files) |
Structured and semi-structured (e.g., XML, JSON, ORC files) |
Structured, semi-structured, and unstructured (e.g., DICOM, PDF, HTML files) |
Data processing frequency
|
Batch (e.g., every 24 hours) |
Batch and real-time |
Batch and real-time |
Analytics complexity
|
Basic reporting and KPI calculation |
Root cause detection, trend identification, and forecasting (both rule-based and powered by machine learning) |
|
Reporting and visualization
|
Via market-available tools like Power BI, Tableau, Looker |
Via market-available tools like Power BI, Tableau, Looker |
Via market-available tools like Power BI, Tableau, Looker, and custom dashboards for complex visuals (e.g., Sankey diagrams for patient disposition tracking) |
Cost
|
$30,000 – $80,000 |
$80,000 – $300,000 |
$300,000 – $1,000,000+ |
Improve Service Delivery and Increase Profitability With Data-Driven Insights
Whether you want to improve your existing analytics system or want to build a new solution, we are ready to support you with our technical expertise. Holding ISO 9001- and ISO 27001 certifications, ScienceSoft can guarantee top software quality and complete security of your data. We also have mature project management practices to drive projects to their goals regardless of time and budget constraints.