Industry
Life Sciences
Patient-centered Care Models Taking Center Stage in Life Sciences
Highlights
- Success in the pharma industry hinges on adopting unified platforms, real-world evidence (RWE), health economics and outcomes research (HEOR), genomics, and AI-enabled analytics.
- Next-generation delivery models and AI-driven automation accelerate study start-up, data review, reconciliation, and query management, enabling more efficient clinical trial execution.
- Our scalable, flexible, and cost-effective services support fit-for-purpose AI adoption aligned with regulatory expectations.
- We uphold compliance with the Clinical Data Interchange Standards Consortium (CDISC) and customer standards through responsible AI and human oversight.
On this page
Overview
Investments in infrastructure, software, AI-enabled capabilities, data foundations, and talent upskilling are essential to keep pace with technology transformations.
The pharmaceutical industry must transform CDM to address the challenges of integrating multiple data sources by adopting unified platforms and AI-ready data architectures. As the role of the data manager evolves to that of a data scientist, more pharma companies emphasize data integrity and the use of next-gen electronic data capture (EDC) tools, data warehouses, and non-CRF data integration in clinical trials.
A complete suite of systems (seamless with limited or no integration) in one CDMS integrating multiple data sources (e-source, HEOR, electronic medical records, digital data, electronic patient-reported outcomes) is crucial for companies today.
Keeping pace with these expectations, TCS’ data managers elevate into clinical data scientists by performing trend analysis with increased scientific rigor and real-time data reviews using advanced analytics.
Solution
TCS’ CDM services focus on delivering high-quality clinical trial data.
Given the evolving needs of the pharma industry, we offer standards-driven CDM services, incorporate smart study build, ensure direct data transfer to EDC, and embed intelligent queries with risk-based data management. AI-enabled capabilities augment these services through protocol intelligence, risk-based query prioritization, and proactive data-quality insights.
Our study start-up services include the development of a data management plan, eCRF specifications, edit check specifications, database design, edit check programming, external checks or listing programming, case report form (CRF) completion guidelines, quality control management, and user acceptance testing. AI-assisted authoring can accelerate eCRF and validation specifications and other study build deliverables, with data managers reviewing and refining every output. TCS adheres to coding guidelines for WHODrug Dictionary (WHODD) and MedDRA, undertaking essential dictionary set-up tasks to ensure compliance in our processes.
Our study conduct services suite covers data review and query management, data entry and verification, third-party data transfer and reconciliation, ePRO data handling, medical coding, serious adverse events (SAE) reconciliation, medical data review, study data transfers, archival, and the like.
As part of the study closeout phase, we collaborate closely with customers and offer support for database and regulatory audits, interim database closure and lock, project closure documentation, study data transfer, archival, and decommissioning.
Additionally, TCS offers specialty services, such as automation consulting, digital clinical trials (DCT) technology-led services, smart questionnaires (ePRO, e-diaries), smart devices and wearables, and proficiency in medical device data management. These services are complemented by AI-enabled insights, predictive analytics, and intelligent multi-source data reconciliation.
Tailoring our approach to a study's unique needs, customers can opt for either of the operating models, such as the end-to-end study-based model, milestone-based model, or FTE (full-time equivalent) model. Collaborative synergy across domains like clinical operations, biostatistics programming, and medical writing has delivered superior data outcomes.
Benefits
We offer a holistic approach to quality and compliance with an inspection readiness team.
First-time right (FTR) approach - TCS uses an agile methodology, with practices such as collective work management, transparency, real-time interventions, and collective wisdom, and embraces change to drive quality and efficiency. AI-assisted quality checks and predictive insights can further reinforce the FTR approach by helping identify potential issues earlier and focus attention on high-risk data.
In-house training team – Pharma Academy of Learning and Sharing (PALS) has created industry-benchmarked modules on therapeutic areas, diseases, and molecules. This enhances the scientific understanding of CDM project teams before they are assigned the studies.
TCS’ CDM projects have delivered upper quartile performance by significantly reducing median cycle times (for the final protocol to go live and last-patient-last-visit to database lock). We offer multiple cost-effective models to manage life sciences companies’ clinical development portfolios.
The TCS Advantage
TCS is committed to driving transformation through technology innovation, responsible AI adoption, and industry-standard solution accelerators.
We have demonstrated deep domain expertise in CDM for the past two decades across all our engagements, including projects for multiple top global pharmaceutical companies.
TCS’ experienced talent pool reflects knowledge depth across phase I to phase IV, expertise in 20 therapeutic areas, and has handled clinical studies with complex disease indications.
Our agile, lean, experienced, and adequately resourced teams assure delivery excellence commitments by mitigating risks and challenges. Our leadership position in capability and experience in the life sciences domain, IT, and R&D brings unique transformative solutions to the CDM landscape. We combine deep domain expertise with AI-enabled analytics and automation so that technology augments, not replaces, expert clinical judgment.
We have developed over 25 process automations within CDM by deploying AI, machine learning, and RPA technologies, and have partnered with leading technology providers to stay at the forefront of CDMS innovation.
We have rich technical expertise with unified platforms, reporting tools, electronic clinical outcome assessments (eCOAs), and DCT platforms. These complement our proprietary solutions to provide end-to-end CDM services, supporting predictive insights, proactive risk management, and informed decision-making across the study lifecycle.
Case in point: Driving operational excellence
The model provides more accountability to improve upper quartile (UQ) performance for a global top UK-based pharma customer.
The adoption of agile methodology by the CDM project team helped our customer achieve and exceed upper quartile performance of data management milestones.
The customer required a transparent approach to enhance cycle times for priority studies and to elevate operational excellence by redefining accountabilities.
Our CDM project team successfully deployed the agile methodology to comprehend role inter-dependencies and establish clear ownership, facilitating on-the-go recalibration and ensuring FTR delivery.
Notably, the customer was able to experience a significantly reduced cycle time from eleven weeks to five weeks from last subject last visit (LSLV) to database lock (DBL). TCS was instrumental in helping the customer improve UQ performance from 59% to 82% within a short period.