Biostatistics

Clinical Design

Special approaches like Adaptive Design

• Pre-Defined Statistical Approach: Our team ensures statistical methods are pre-defined in the protocol to maintain integrity and consistency
• Statistical Complexities: Adaptive designs introduce challenges such as balancing adaptation with statistical validity, managing variability, and avoiding biases. These complexities are managed by experts
• Multiplicity and Alpha Error: Multiple interim analyses can affect the overall alpha error rate. We make necessary adjustments to control type I error and ensure valid results

Sample Size Calculations

Key Considerations for Sample Size Calculation:

• Study Design Factors: Assessing all relevant aspects of the study to ensure comprehensive analysis
• Patient Burden Reduction: Minimizing patient burden to achieve significant cost savings while maintaining the required statistical power and regulatory compliance
• Balancing Risks and Costs: Finding the right balance between the risk of trial failure, costs, and recruitment time to streamline the trial process
• Expert Analysis: Leveraging the expertise of COD specialists who evaluate impacting factors, complexities, bio-statistical nuances, and associated risks in proposed statistical possibilities

Protocol Development

• Interim Analysis and DSMB: Interim analyses and Data Safety Monitoring Board (DSMB) activities are pre-defined in the Statistical Analysis Plan (SAP) to maintain protocol adherence
• Blinding Strategy: Ensuring a robust blinding strategy during interim analyses to prevent bias and maintain study credibility
• Post-DMC Decisions: Outlining and implementing decisions post-DMC meetings based on predefined criteria for systematic and transparent execution
• Pre-Planned Analysis: To support the DSMB quorum in making timely and informed safety decisions, pre-planned analyses are essential. These analyses provide the necessary elements and data, allowing the DSMB to evaluate the trial’s progress and make safety calls effectively

Statistical Analysis

• Comprehensive Statistical Analysis Plan (SAP) Preparation: We specialize in creating detailed Statistical Analysis Plans (SAP) to outline the statistical methodologies and procedures to be followed throughout your clinical trial
• SAS Programming: Our team of expert SAS programmers meticulously programs and analyses clinical trial data to ensure accuracy and compliance with regulatory standards
• TLF Generation: We generate Tables, Listings, and Figures (TLFs) that provide a clear and comprehensive presentation of your clinical trial data, facilitating easy interpretation and decision-making
• PK/PD Analysis: Our pharmacokinetic (PK) and pharmacodynamic (PD) analysis services offer in-depth insights into the drug’s behavior within the body and its biological effects, helping to ensure the safety and efficacy of your clinical trials

Comprehensive CDISC Conversion Services

• SDTM (Study Data Tabulation Model): Structured datasets are defined for regulatory submission and review, ensuring clarity and compliance
• ADaM (Analysis Data Model): Efficient datasets for accurate statistical analysis, aligned with study needs and supported by detailed Define.xml metadata files for SDTM and ADaM, ensuring transparency and smooth regulatory reviews