Services

Our expert biostatisticians collaborate with investigators during protocol development to:

• Identify optimal trial designs, such as adaptive designs, Bayesian designs, enrichment strategies, and cluster-randomized designs etc.
• Define study hypotheses and endpoints.
• Perform sample size and power calculations.
• Draft statistical analysis plans (SAPs).
• Serve as a liaison between WCM PIs and external trial networks and sponsors.

We offer a full suite of data management services, ensuring high-quality and regulatory-compliant data collection and processing:

• Electronic Case Report Form (eCRF) design.
• Development of Data Management and Sharing (DMS) plans.
• Comprehensive electronic data capture (EDC) programming: Our dedicated team builds EDC infrastructure using platforms such as REDCap, REDCap Cloud, and Clinvestigator etc.
• Implementation of data standards (CDISC, SDTM, ADaM) and validation checks.
• Quality control, audit trails, and documentation.
• Site training for EDC and data management systems.
• Medical coding for adverse events (AEs), severe AEs and concomitant medications.
• Full data linkage and integration, including eCRFs, imaging, laboratory data, and Electronic Health Records (EHRs).

Our team provides end-to-end clinical trial monitoring (CTM), ensuring data integrity and protocol adherence:

• Randomization scheme development and implementation (stratified, block, cluster randomization etc).
• Enrollment and follow-up tracking.
• Monitoring and reporting of safety events and protocol deviations.
• Identification and resolution of data quality issues via Source Data Verification (SDV), query management and risk-based monitoring (RBM).
• Site coordination, training, and investigator meetings.
• Preparation of Data and Safety Monitoring Board (DSMB) charters, reports, and meeting coordination.
• Execution of interim analyses to support decision-making.

We execute interim and final analyses as outlined in the SAP, generating regulatory and publication-ready reports:

• Creation and validation of analysis datasets.
• Planning, analysis, and writing of manuscripts, clinical study reports (CSRs), and regulatory submissions.
• High-quality figure and table generation for publications.
• Management and execution of secondary analyses for completed trials.

We ensure full compliance with regulatory requirements across all stages of the clinical trial process:

• Facilitation of Institutional Review Board (IRB) applications.
• Preparation for regulatory submissions, including CSRs and data packages for FDA, EMA, and other regulatory agencies.
• Adherence to Good Clinical Practice (GCP), International Council for Harmonization (ICH) guidelines.
• Management of electronic records and signatures in accordance with 21 CFR Part 11.
• Assurance of compliance with HIPAA for patient data protection.

Coming soon.  Please contact dcc@med.cornell.edu for assistance.

We ensure seamless access to diverse RWD sources, integrating them into standardized formats for analysis:

• Identification of RWD datasets (EHRs, claims, registries, wearables, imaging, genomics).
• Facilitation of Data Use Agreements (DUAs) applications.
• Extraction, harmonization, and mapping to common data models (OMOP, PCORnet, Sentinel).
• Secure data linkage using privacy-preserving methods.

We enhance data quality and readiness for analysis through:

• Computable phenotyping using structured/unstructured data.
• Standardization, normalization, and feature engineering.
• Imputation, anomaly detection, and bias mitigation.
• Longitudinal data processing for temporal analyses.
• Advanced Analytics: We apply cutting-edge analytical methods including:

We apply cutting-edge analytical methods including:

• Supervised, unsupervised, and reinforcement learning for predictive modeling, disease subtyping and clinical decision support.
• Representation learning and embedding for multimodal data (EHRs, text, images, temporal signals, genomics).
• Causal inference for effectiveness and safety analyses.
• Dimensionality reduction and visualization (PCA, t-SNE, UMAP).
• AI-powered analytic tool development with user-friendly interfaces.

We translate data-driven findings into clinically and regulatory meaningful evidence:

• Target trial emulation and synthetic control arms.
• Model evaluation and monitoring (technical performance, clinical impact, fairness assessment).
• Model interpretation and explanation (SHAP, LIME).
• Knowledge extraction from biomedical literature and knowledge graphs (e.g., iBKH).
• High-quality reporting for manuscripts, regulatory submissions, and visual summaries.