Data processing and preparation for clinical studies and biostatistics.
In the pharmaceutical industry, biostatistics and clinical data management have become indispensable. Comprehensive insights can be gained from a wide variety of studies through targeted statistical programming. In compliance with GCP guidelines, comprehensive data can be managed, and a study can be successfully evaluated. Biostatistics helps to analyse clinical studies with specific guidelines.
Clinical data management is the processing of data collected in a clinical study in a meaningful and efficient way. Well-thought-out data management ensures study projects are carried out correctly from the planning stage to conclusion. Some of the biggest challenges include creating and validating databases, ensuring data consistency, handling erroneous data, remote data entry and query management, and preparing data for statistical analysis.
Well-designed data management generates more data for your studies, providing a larger data pool and thus increasing the validity of the studies significantly.
Sophisticated database design and programming, including the corresponding documentation, make the user's work much easier; with a good Case Report Form (CRF) design, clear and precise questions and instructions can be created, eliminating the risk of misinterpretation.
With data review support (jReview, Spotfire, etc.), well thought-out query management, and the use of interfaces to EDC/RDE systems, your clinical data management is a guaranteed success.
Comprehensive data management in compliance with GCP guidelines is crucial for the successful evaluation of a study, and with our skilled data managers' extensive experience in the pharmaceutical sector, we can guarantee you the highest quality of valid, reliable data. We can also provide comprehensive support throughout the entire study process, from initial planning to the final evaluation and summary.
Data management is becoming increasingly important due to a growing awareness of quality control and quality assurance in clinical trials along with evolving regulatory demands. We are always updated, ready to assist you in meeting these legal requirements.
Quality assurance is ensured through the transparency and traceability of all the steps in a job, and our team of experts here at synvert is proficient in navigating these steps safely and securely.
As a consequence of our extensive experience in the pharmaceutical sector, we possess in-depth expertise in data management, including database design and programming, CRF design, query management, quality checks, error analysis, and more.
In recent years, biostatistics have gained increasing importance due to the emergence of various high-throughput methods. These methods allow millions of tests to be conducted on biochemical, genetic, or pharmacological substances, and consequently huge amounts of data are generated, which need to be processed.
There are several methods available to process these large datasets. However, as the amount of data increases, the methods used become more complex. Common techniques for analysing this data include neural networks, support vector machines, and principal component analysis, which involve dimension reduction techniques from the field of statistical machine learning.
Biostatistics are used in nutritional research to determine the health efficacy of certain foods, as well as in clinical trials to analyse the effectiveness of particular drugs and treatments.
Biostatistics are a critical component in various fields, including clinical trials, nutritional research, and preventive medicine, as well as playing a significant role in study planning, like the creation of study protocols, case number planning, CRF, DVP (Data Validation Plans), and other related activities, all in compliance with the relevant ICH (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use) and FDA (Food and Drug Administration) guidelines.
Clinical studies involve the use of SAP (Statistical Analysis Plans) and the creation of TLF (Tables, Listings, and Figures). Additionally, these studies require organising and participating in DSMB (Data Safety Monitoring Boards) and conducting PK/PD (Pharmacokinetic/Pharmacodynamic) analyses.
With extensive knowledge of pattern recognition and data mining methods, it is possible to discover new relationships in the data, and a clever selection of classification and clustering methods can accurately assign the data to the appropriate groups.
Our team of highly qualified statisticians can assist you in conducting your clinical study in compliance with ICH and FDA guidelines. Working closely with our statistical programmers, we ensure the highest quality in evaluating your study.
Our support is not limited to study planning, which includes developing study protocols, case numbers, creating case report forms (CRF), and preparing data validation plans (DVP). We can also help with report preparation, including study reports, safety and efficacy reports, interim reports, and other submission-relevant documents. Our expertise extends to Statistical Analysis Plan (SAP) and Tables, Listings, and Figures (TLF) creation, as well as organising and participating in Data and Safety Monitoring Board (DSMB) meetings. We also participate in the development of AMNOG (The German Pharmaceutical Market Restructuring Act) dossiers for the assessment of additional benefits. With our extensive experience, we can provide you with the support you need for a successful clinical study.
With our thoroughly trained statistical programmers, you’re guaranteed the highest quality study analysis.
Take advantage of our statistical analysis and consulting services: we can assist you in selecting the best statistical methods to handle outliers correctly, ensuring that your regression methods yield accurate results and that meaningful clustering is performed.
To comply with the AMNOG regulations in Germany, extensive dossiers must be submitted for the assessment of additional benefits before launching new pharmaceutical products on the market. Our team can help you to manage the significant data submission requirements involved in this process.
Medical writing is a crucial aspect of the pharmaceutical and medical industry. With the increasing complexity of clinical trials and approval procedures, newly developed medical products must undergo a rigorous process before they can be marketed, and well-structured documents play a vital role in this process. Medical professionals need to be able to read and understand the newly written documents quickly and easily, and a consulting company can support you with the preparation of study-related documents and the processing of regulatory inquiries, amongst other things.
In medical writing, the preparation of study-related documents, like protocols and reports, is very important, and in addition, regulatory requests require prompt and diligent handling to accurately represent your company.
For medical writing, a knowledge of local regulations is of great importance.
In addition to preparing study-related documents, creating effective presentations is also crucial.
Our team of medical writers can prepare study reports and help you throughout the entire study process, including regulatory submissions and presenting study results.
We support you in the preparation of study-related documents (protocols, reports, etc.).
Our team can provide expert support with regulatory inquiries.
Our team has a great deal of experience preparing these types of presentation.
Statistical programming involves the development and validation of lists, tables, and graphics for statistical analysis. A central aspect of statistical programming is the merging and integration of new internal and external study data. Data extraction, transformation, and mining are also integral components of statistical programming, typically automated.
Companies may have their own sets of standard programs or tools for statistical analysis; we employ statistical programming with specific applications to enable the analysis of research and study data in a company-specific manner.
Our team of programmers, with years of accumulated experience, can support you with your study evaluations with their comprehensive understanding of the CDISC (Clinical Data Interchange Standards Consortium), SDTM (Study Data Tabulation Model), and ADaM ( Analysis Data Model) standards, essential for efficient study analysis.
Tools for statistical programming, for example in SAS and R, are constantly evolving, so it is important to stay on the ball with the latest developments, just as our experts do.
For more than 15 years synvert has been working with biostatistics and clinical data management. Our extensive experience in this field has led to many international pharmaceutical businesses making long-term contracts with us.
Thanks to regular in-house and third-party training courses in, for example, SAS or GCO, our employees can keep up with the latest changes and developments.
Our synvert experts have ample experience implementing the CDISC, SDTM and ADaM standards.
Data mining is a methodical application of statistical techniques to large datasets, aimed at identifying relationships and trends within the data.
Clinical trials are conducted in multiple stages. The initial phase involves testing a new substance on healthy individuals to investigate its safety and tolerability. In phase two, a small group of people who are already sick are given the substance to test its effectiveness and tolerability. Phase three involves administering the substance to a larger group of sick individuals to obtain the necessary data for regulatory approval of the new drug. The final phase focuses on monitoring the therapeutic use of the drug after it has been approved for market, specifically for detecting rare and usually unwanted side effects; this phase also involves identifying any potential long-term effects.
synvert will accompany you through all these phases as well as supporting you in the collection and evaluation of your data.
Pharmacovigilance is the systematic process of monitoring finished drug products for humans or animals, aimed at detecting and evaluating any adverse effects or potential risks associated with their use, thus enabling appropriate risk minimisation measures to be taken, ensuring the safety and efficacy of these products.
Randomly assigning study participants to either control or experimental groups creates a more level playing field, allowing for a higher degree of statistical certainty in the results.
Coding standards adhere to international norms such as MedDRA (Medical Dictionary for Regulatory Activities), ICD (International Classification of Diseases), and WHO-DD (World Health Organization Drug Dictionary), guaranteeing accurate and consistent documentation and reporting.
To provide comprehensive support for a clinical study, various tasks need to be performed throughout different phases of the study, including data collection, evaluation, and reporting. Our team of highly specialised professionals are well-equipped to assist you with these tasks, ensuring the successful performance of your study.
Thanks to our experience in the field of biostatistics and clinical data management, we can provide you with comprehensive support for your clinical study and our experts will be there with you at every stage of the study.
Our programmers are proficient in the MedDRA, ICD and WHO-DD international standards.
Regular training of our employees keeps us up to date with medical services, including randomisation, pharmacovigilance and medical reviews.