Real-World Data Utilization in Clinical Research
Real-World Data Utilization and Real-World Evidence generation can and will reduce time and costs in clinical trials. Using real-world data for pre-study feasibility assessments, real-world data synthetic control arms, and follow-up patient monitoring is more and more becoming practice, although there are still many challenges to overcome and new processes to be established.
Whether you are considering to start with real-world data utilization or if you like to improve the current real-world data utilization process, we can help out. The corresponding services include (but are not limited to):
– Workshops and education
– Study set-up consulting
– Data vendor selection and evaluation
– Data reliability and robustness testing
– Data standardization
– Consulting in and/or execution of real-world data analysis
Workshop: Real-World Data Utilization in Regulatory Clinical Studies
The in-company workshop ‘Real-world Data Utilization in Regulatory Clinical Studies’ is intended to explore what requirements are applicable for real-world data utilization, how quality can be assured and assessed, and whether this data can be effectively leveraged for your specific research question.
In this unique interactive workshop, we will combine an intensive training on all aspects of real-world data utilization with the specific data requirement gathering for the research question at hand.
- Strengths and limitations of real-world data sources.
- Relevant data elements and constraints
- Availability of relevant data and corresponding data source selection.
- Regulatory requirements for real-world data usage.
The corresponding information can be downloaded via: Workshop information RWD
The team said that we could provide a very useful & comprehensive RWE overview and that it was great to address the topic from so many aspects, each participant found their relevant part in the 2-day agenda. They also found it very beneficial that the different groups (Biostatistics, Clinical Data Management, Medical Science and Post-Approval Study Management) had the opportunity to interact with each other around the topic and share insights.
The workshop exceeded our expectations in every aspect. Your speakers delivered outstanding presentations, providing valuable insights into the subject matter of RWE/D. The interactive sessions facilitated meaningful discussions and offered a platform for fruitful exchanges of ideas among the participants.
Mapping and Standardization of Real-World Data
ClinLine has cultivated strong relationships within the industry. These partnerships allow us to leverage each other’s strengths, enabling us to deliver optimal services to our clients. Among our esteemed partners is OCS Life Sciences, and we are thrilled to announce our latest collaborative endeavour: Real-World Data Mapping services. This initiative merges ClinLine’s Real-World data insights and OMOP experience with OCS Life Sciences’ mapping tools and programming proficiency. This collaboration functions as a cohesive team, without additional overhead or associated costs.
OMOP mapping services are offered in two directions:
– For standardization purposes: from registries or other sources to OMOP.
– For submission and analysis purposes: from OMOP to SDTM.
In addition, we also perform mapping and standardization of other Real-World Data origins like registry formats and FHIR formats.
Our comprehensive mapping services encompass a transparent and traceable process, accompanied by the necessary documentation to render data FAIR (Findable, Accessible, Interoperable, Reproduceable) for analysis, publications, and regulatory submissions. If you wish to delve deeper into this topic, please do not hesitate to contact us for further information.
Study feasibility assessments based on Real-World Data
The real-world eligibility tool
The Real-World Eligibility tool is designed and utilized at ClinLine to check the eligibility criteria of a study during the study design phase. By doing this, potential selection problems during the execution of the study can be detected and avoided. The tool is also used to get an impression of the patient population in different global areas. It is independent and interoperable with data standards such as CDISC, OMOP, and FHIR, but can also be filled with data adjusted to a basic defined import format. The tool is run at the included data centers, solving most privacy and governance issues. The tool contains automatic input definition generation and data validation algorithms to ensure that the analysis is performed correctly. Analysis is standardized, preventing the occurrence of analysis interpretation differences between data centers. Based on the results obtained from the different global data centers a uniform report is generated.
Would you like to know more or are you interested in a personal presentation of the tool? We are happy to share our ideas and thoughts with you. Go to our contact page or email us at email@example.com.