TCS ADD™ Risk-Based Quality Management
Transform your clinical trials with our AI-driven RBQM platform. Enhance efficiency, ensure compliance and drive quality.
Industry
Life Sciences
Patient-centered Care Models Taking Center Stage in Life Sciences
Products and Platforms
TCS ADD™
TCS ADD™: A Suite of Modern and Open Technology Platforms
Highlights
- The clinical trial industry is facing unique challenges today due to high data volume and complexity, making clinical trial oversight inefficient and costly.
- Companies need data science-led solutions that spell greater market success. Our integrated, AI-driven platform modeled on the good clinical practice (GCP) guidelines is transforming clinical trials by implementing comprehensive risk assessment, monitoring, issue identification, and mitigation across operational and clinical data domains.
- TCS ADD™ Risk-Based Quality Management improves quality and oversight, reduces workload, enhances patient safety, increases compliance, and accelerates the product market submission process.
On this page
Overview
TCS ADD™ Risk-Based Quality Management (RBQM) is an end to end integrated, AI- driven platform modelled on FDA and ICH guidelines on ‘Quality by Design’ and managing ‘Critical to Quality’ factors for transforming clinical trials by implementing comprehensive risk assessment, monitoring, issue identification and mitigation across operational and clinical data.
Our RBQM platform significantly accelerates time to market by improving data quality, study/site oversight, reducing workload by predictive analytics, enhancing patient safety and regulatory compliance.
Highlights
Challenge
Clinical trial monitoring is facing challenges due to the increased complexity of trials and an increasing number of data sources.
This has resulted in operational inefficiency and difficulties in signal detection. Siloed systems, time-consuming study onboarding activities, lack of required skill sets, and limited AI/ML capabilities are hampering conducting clinical trials efficiently, impacting costs and quality adversely. Manual review processes, absence of end-to-end workflows, and difficulties in bringing in cross-functional collaboration are delaying the adoption of risk-based monitoring strategies.
Solution
TCS ADD™ Risk-Based Quality Management is a platform, catering to diverse needs of risk based strategies in R&D.
The platform provides the products and technology to enhance risk assessment, monitoring, quality control, compliance, site performance, and clinical and operational data analytics capabilities. Our unique platform approach allows flexibility, enabling organizations to adapt the tools that best meet their immediate needs while gradually integrating a comprehensive risk-based quality management (RBQM) solution.
TCS ADD™ Risk-Based Quality Management platform is powered by four cutting-edge components encompassing end-to-end risk assessment, statistical monitoring, and mitigation of risk.
Solution features
Real-time risk assessment, monitoring and mitigation
Scalable, modular, and flexible
Encompasses over 40 out-of-the-box KRIs and critical data points and site/patient risk scores
System generated alerts and end to end user driven workflows
Enables efficient study onboarding in a near-touchless manner
Extensive KRI/KPI/ QTL/CDP library for user-driven study configuration
Our Modules
The Risk Assessment and Categorization Tool (RACT) is a highly intuitive component that aligns with the industry–standard approach for risk identification and mitigation of critical data and critical processes of clinical trials. The platform facilitates early identification and planning for potential risks that could negatively impact the safety, efficacy, and integrity of the study and study data.
Key features:
- Efficient risk assessment at program and protocol levels on an ongoing basis
- Smart workflows ensuring documentation and approvals
- Categorized risk assessment and risk score assignment
- Quantification of risks and mitigation plan allocation
- Integrated with downstream monitoring tools for easy configuration of operational and clinical analytics tools
- Aligned to TransCelerate standards
Clinical Trial Analytics leverages data-driven insights to optimize the planning, execution, and oversight of clinical trials with a focus on improving trial efficiency, ensuring compliance, and enhancing overall trial quality through robust analytics. The offering facilitates user-driven configuration and centralizes statistical monitoring of over 40 key risk indicators such as patient recruitment rates, protocol deviations, and data entry lags, enabling timely interventions. In addition, it enables patient-specific analytics to detect anomalies in patient data and monitor patient adherence to treatment protocols, and identify patterns that may indicate non-compliance.
Key features:
- Automated and intelligent data intake from various structured and unstructured sources, resulting in novel insights through the enablement of AI/ML methods
- Integrated with RACT (Risk Assessment and Categorization Tool) and has user-driven configuration of KRIs and KPIs from an extensive master library of more than 40 out-of-the-box KRIs
- Nine levels of drill down providing data analysis at therapeutic area, indication, compound, protocol, region, country, site, subject, and so on.
- Risk scores at all levels and CRA (Clinical Research Associate) workload predictions facilitating dynamic site monitoring
- Comprehensive communication module
- GenAI-enabled clinical trial insights
- Targeted data reviews and site monitoring visits, enabling reduced source data verification models
The QTL module allows the study team to proactively monitor systemic issues that could negatively impact the safety and efficacy of clinical trials.
Key features:
- Comprehensive and extensible QTL (Quality Tolerance Limit) library with more than 20 out-of-the-box QTLs across multiple aspects of a clinical trial
- AI-driven statistical tolerance limit calculations fit for your study
- Automated QTL monitoring tailored with notifications of breaches, drill-down features for RCA, and mitigation actions
- QTL reporting for CSR (Clinical Study Report)
- Powered by smart data ingestion
An advanced and integrated AI/ML-based solution that enables the seamless monitoring of patients’ medical data for timely decision-making. It facilitates patient profiling with risk scores, outlier detection, and alerts and notifications to easily identify safety risks and trends.
Key features:
- Patient profiles and risk scores
- Configurable critical data points and metrics library for subject data with the study-specific configuration of ‘priority alerts’ and ‘data of interest’
- Interactive study-, site-, and subject-level data trends across more than 50 clinical parameters
- End-to-end review workflow and query management system. Integrations with multiple EDCs (Electronic Data Capture)
- Anomaly-detection algorithms and GenAI-enabled insights
- Unique review processes for multiple stakeholders, such as data management, centralized monitoring, medical monitors, etc.
Benefits
The TCS ADD™ Risk-Based Quality Management platform commands global usage covering several therapeutic areas.
The key benefits include:
Increased efficiency and reduced workload
- Up to 30% reduction in site monitoring costs by dynamic site monitoring facilitated by workload predictions and risk trends
- 100% elimination of manual allocation
- Targeted site monitoring with reduced source data verification (SDV)/ Source data review (SDR)
Improved data quality and oversight
- Up to 20% increase in data quality and integrity with the detection of duplication and missing data collection and early identification of trends and signals
- End-to-end integrated risk assessment, monitoring, and mitigation workflows
Meaningful insight and prevention of issues
- Automated and intelligent data intake from over 15 diverse data sources resulting in novel insights
- Fast and easy insight and decision-making with use case-specific algorithms and visualizations; TA (Therapeutic Area)-compound-program-region-country-site-patient level aggregation
- GenAI-enabled clinical trial insights
