We provide end-to-end protocol development and validation to ensure clinical studies are scientifically rigorous, regulatory-compliant, and aligned with downstream analysis and data management. Our team drafts protocols in line with ICH-GCP guidelines, defines study objectives, endpoints, populations, randomization, and safety monitoring, and integrates them with SAP, CRF, SDTM/ADaM, and TLF planning. Protocols undergo thorough validation for logical consistency, completeness, and compliance, and are reviewed cross-functionally to ensure readiness for execution and submission. This approach reduces protocol amendments, prevents delays, and provides a strong foundation for high-quality, submission-ready data.
We develop comprehensive Statistical Analysis Plans aligned with the study protocol, datasets, and regulatory expectations. The SAP defines analysis populations, statistical methods, handling of missing data, and derivations, while ensuring alignment with ADaM datasets and TLF outputs. Independent review and cross-functional validation confirm statistical accuracy, traceability, and regulatory readiness. This ensures clear, executable analysis plans, reduces rework, and builds confidence in statistical results for regulatory submissions.
Our team creates submission-ready annotated CRFs (ACRFs) that ensure accurate, traceable, and regulatory-compliant data capture. CRF fields are mapped to SDTM variables and controlled terminology, with derivations, splits, and merges documented. All forms undergo cross-functional review and audit-ready documentation is maintained. This provides a strong foundation for SDTM and ADaM datasets, minimizes downstream mapping issues, and supports inspection readiness.
We design and implement ADaM datasets that are fully traceable, analysis-ready, and compliant with regulatory standards. Population and analysis flags, derived parameters, and metadata are defined to support efficacy(ADTTE, ADEFF, ADTR, ADRS, ADBOR), safety(ADSL, ADQS, ADLB, ADAE, ADEX, ADEXSUM, ADEG, ADVS, ADMH, ADCM), PK(ADPC, ADPP) , and exploratory analyses. Traceability from SDTM to ADaM to TLFs is verified, and independent validation is performed. Key checks include traceability confirmation, verification of derived parameters, and independent QC, ensuring high-quality, reliable analysis datasets.
Our SMEs develop accurate and consistent TLF outputs aligned with SAP and ADaM datasets. This includes interim, final, and ad-hoc analyses, with independent QC and reviewer-focused formatting. The outputs are designed to communicate study results clearly and effectively. Key quality checks include consistency validation across datasets and TLFs, adherence to SAP specifications, and ensuring interpretability for regulatory reviewers, facilitating smooth submissions.
We create detailed, validated Define.xml files capturing dataset, variable, and value-level metadata, derivation logic, and controlled terminology. Define.xml is validated using industry-standard tools and aligned with SDTM, ADaM, SDRG, and ADRG documentation. This ensures transparency and usability for reviewers, streamlines regulatory evaluation, and reduces queries, supporting faster approvals and high-quality submissions.
We provide Study Data Review Guides (SDRG) and Analysis Data Review Guides (ADRG) to clearly explain study datasets, derivations, assumptions, and analysis decisions. These guides are aligned with datasets and Define.xml and formatted for reviewer usability. Independent SME review ensures clarity and completeness. This simplifies regulatory review, reduces back-and-forth queries, and strengthens the overall submission package.
We offer global regulatory submission support for FDA (US), MHRA (UK), and PMDA (Japan). Our services include package preparation, CDISC compliance validation, SDRG/ADRG and Define.xml finalization, query resolution, and inspection readiness. Data quality checks ensure end-to-end traceability, regulatory compliance, and accuracy. This comprehensive approach reduces submission risk, accelerates approvals, and provides a single partner for multi-region regulatory submissions.
We generate comprehensive patient profiles to provide a clear, patient-level view of study data, ensuring traceability and transparency. Patient profiles summarize key information such as demographics, baseline characteristics, adverse events, concomitant medications, lab results, and clinical outcomes in a structured, standardized format. These profiles are derived from SDTM and ADaM datasets and validated for accuracy, consistency, and completeness. By applying quality checks for missing data, consistency across visits, and logical coherence, patient profiles allow sponsors, statisticians, and regulators to easily review individual patient journeys. They are instrumental for safety monitoring, regulatory inspections, and submission packages, helping highlight trends and support clinical interpretation.
We deliver end-to-end SDTM operations including dataset creation, mapping, and validation to generate submission-ready, reviewer-friendly datasets. SDTM specifications and datasets are developed across all domains, applying controlled terminology, TAUGs, and sponsor-specific standards. Multi-level QC and independent review ensure data accuracy and consistency. Key data checks include source-to-SDTM validation, controlled terminology compliance, and domain consistency checks, ensuring high-quality datasets ready for regulatory submission.
Reliability is built on experience. The CLINIZIG team possesses a rich history of over 20 years in a wide range of therapeutic areas, positioning us as a highly reliable partner for both small-to-medium enterprises and global pharmaceutical players.
+49 1575 7819 326
Reliability is built on experience. The CLINIZIG team possesses a rich history of over 20 years in a wide range of therapeutic areas, positioning us as a highly reliable partner for both small-to-medium enterprises and global pharmaceutical players.