Our Biostatistics and Programming team delivers robust statistical design, analysis, and reporting to support clinical research across all phases of development. We provide statistical analysis plans (SAPs), sample size estimation, randomization, interim and final analyses, and validated statistical programming using industry-standard tools (SAS 9.4 version). Our experts generate high-quality clinical datasets, tables, listings, figures (TLFs), and regulatory-compliant outputs, ensuring accurate, reliable, and timely results for regulatory submissions and informed decision-making.
Expert statistical guidance throughout the clinical development lifecycle, from protocol design to regulatory submission, ensuring scientifically sound study outcomes.
Development of comprehensive Statistical Analysis Plans (SAPs) aligned with study objectives, regulatory requirements, and industry best practices.
Accurate sample size estimation and statistical power calculations to optimize study design while ensuring reliable and meaningful results.
Generation and validation of randomization schedules, allocation schemes, and treatment assignment strategies for unbiased clinical trials.
Statistical review of study protocols, objectives, endpoints, and methodologies to strengthen scientific validity and operational feasibility.
Selection of appropriate efficacy and safety endpoints with robust statistical methodologies tailored to study objectives.
Design and execution of interim analyses for early decision-making while maintaining study integrity and regulatory compliance.
Support for adaptive clinical trial methodologies, enabling protocol modifications based on predefined interim analyses.
Independent statistical reporting and analyses for Data Monitoring Committees (DMCs) and Data Safety Monitoring Boards (DSMBs).
Comprehensive statistical analysis of efficacy, safety, and tolerability endpoints using validated methodologies.
Advanced survival analyses including Kaplan-Meier estimation, Cox proportional hazards regression, and time-to-event modeling.
Analysis of repeated measures and longitudinal clinical data to accurately assess treatment effects over time.
Expertise in non-inferiority, superiority, and equivalence testing to support diverse clinical trial objectives.
Application of Bayesian statistical approaches for adaptive designs, evidence synthesis, and informed clinical decision-making.
Integrated statistical analyses combining data across multiple studies to strengthen scientific evidence.
Advanced missing data handling techniques and sensitivity analyses to ensure robust and reliable study conclusions.
Detailed subgroup evaluations and exploratory analyses to uncover additional clinical insights.
Specialized statistical evaluation of biomarker, pharmacodynamic, and translational research data.
Comprehensive Pharmacokinetic (PK) and Pharmacodynamic (PD) statistical modeling and analysis.
Statistical support for observational studies, registries, and Real-World Evidence (RWE) research.
Statistical design and analysis for medical device clinical investigations and performance evaluations.
Generation of publication-quality Tables, Listings, and Figures (TLFs) for regulatory submissions and scientific publications.
Preparation of statistically validated outputs and reporting for Clinical Study Reports (CSRs).
Development of CDISC-compliant SDTM datasets for standardized regulatory submissions.
Creation of analysis-ready ADaM datasets supporting efficient statistical analysis and reporting.
Programming of publication-quality Tables, Listings, and Figures (TLFs) using validated processes.
Validated SAS® 9.4 programming for clinical data analysis, reporting, and regulatory submissions.
Advanced statistical programming in R for customized analyses, visualization, and exploratory research.
Python-based statistical programming, automation, and data science solutions for clinical research.
Automated validation programs and quality control processes to ensure data accuracy and consistency.
Independent validation of SDTM and ADaM datasets to ensure CDISC compliance.
Execution and resolution of Pinnacle 21 validation checks supporting regulatory readiness.
Preparation of Define.xml metadata files compliant with regulatory submission standards.
Development of comprehensive SDTM and ADaM Reviewer Guides for regulatory authorities.
Programming Integrated Summaries of Safety (ISS) and Integrated Summaries of Efficacy (ISE) for NDA/BLA submissions.
Statistical programming supporting safety analyses, signal detection, and pharmacovigilance reporting.
Programming support for Pharmacokinetic and Pharmacodynamic analyses, including modeling datasets and outputs.
Development and validation of randomization schedules, treatment codes, and blinding procedures.
Custom programming solutions for automated data cleaning, discrepancy identification, and quality improvement.
Automation of recurring statistical reports, TLF generation, and submission-ready outputs.
Creation of interactive dashboards and advanced data visualizations for study monitoring and decision-making.
Preparation of regulatory-compliant datasets and outputs for eCTD submissions.
End-to-end programming support for global regulatory submissions including FDA, EMA, MHRA, CDSCO, and other health authorities.
Independent QC programming and double programming validation to ensure the highest level of accuracy and regulatory compliance.