• views: 99
• date: 6 June 2025
• posted by: 0nelove

What you'll learn
Distinguish the objectives, advantages, and limitations of Phase I–IV clinical trials, pragmatic trials, and observational studies.
Configure and utilize leading electronic data capture platforms and apply CDISC standards to structure, clean, and audit clinical datasets.
Identify, curate, and critically evaluate real-world data from electronic medical records, insurance claims, patient registries, and wearables.
Develop and execute retrospective and prospective RWE study protocols, including control cohort definition and endpoint selection.
Apply advanced methods such as propensity score matching, inverse probability weighting, and sensitivity analyses to minimize confounding.
Conduct univariate, multivariate, and survival analyses in SAS and R, and interpret hazard ratios, odds ratios, and confidence intervals.
Build interactive dashboards in Power BI or Tableau and craft clear reports tailored to regulatory agencies, payers, and academia.
Prepare RWE packages for label expansions, post-marketing safety updates, and health-economic value dossiers under FDA, EMA, and payer frameworks.
Implement HIPAA, GDPR, and global data-privacy best practices, including informed consent management and data de-identification.
Integrate pharmacovigilance processes with RWE by designing signal-detection algorithms and risk-minimization plans using tools like Argus Safety.
Coordinate cross-functional RWE projects by developing project plans, timelines, budgets, and deliverables across clinical, biostatistics, HEOR, regulatory .
Execute an end-to-end capstone RWE study—from protocol drafting and data extraction to analysis, visualization, and a defendable regulatory brief.
Requirements
A bachelor's degree in life sciences, pharmacy, medicine, public health, or a related field.
Basic understanding of clinical research principles and terminology.
Introductory knowledge of biostatistics and epidemiology.
Familiarity with spreadsheet software (e.g., Excel) and willingness to learn SAS or R.
Comfortable using web-based platforms and electronic data capture systems.
Proficiency in English for reading scientific literature and writing reports.
Reliable internet access and a computer capable of running statistical software.
Commitment to dedicating 5–7 hours per week over an 8-week blended schedule.
Description
Clinical Research & Real-World Evidence (RWE) ProfessionalUnlock the power of real-world data and revolutionize evidence-based healthcare decisions. This internationally benchmarked course blends the rigor of clinical research with the innovation of real-world evidence, offering in-depth mastery from study design to regulatory-grade analysis.Whether you're a healthcare professional, researcher, or data scientist, this course empowers you to navigate the complexities of global clinical trials and RWE generation with hands-on experience in SAS, R, CDISC standards, EDC systems, Power BI, and more.What You'll Learn inside This Course:Fundamentals of clinical research and the hierarchy of evidenceComprehensive understanding of clinical trial phases and adaptive designsGlobal regulatory frameworks: ICH-GCP, FDA, EMA, and Indian Schedule YClinical data management using CDASH, SDTM, and ADaM standardsConfiguring leading Electronic Data Capture (EDC) systemsReal-world data sourcing from EMRs, claims, registries, and wearablesDesigning robust RWE protocols with advanced confounding control methodsBiostatistical analysis using SAS and R (multivariate, survival, time-to-event)Communicating insights via professional dashboards and journal-style reportsPreparing RWE for regulatory submission, label expansion, and market accessEnsuring ethics, data privacy, and global compliance in RWE practicesIntegrating pharmacovigilance and signal detection into real-world studiesLeading cross-functional RWE projects with agile project management skillsCompleting a full-scale, peer-reviewed capstone project from protocol to presentationThis course offers applied theoretical real-world training aligned with global industry standards and regulatory expectations — ensuring you're equipped to deliver evidence that influences clinical, regulatory, and payer decision-making in today's dynamic healthcare environment.
Who this course is for
Life-sciences, pharmacy, medicine, and public-health graduates aiming to build specialized skills in RWE design, analysis, and regulatory applications.
Clinical research associates, coordinators, and project managers seeking to deepen their expertise in both traditional trials and real-world data studies.
Data analysts and biostatisticians who want to apply their quantitative abilities to healthcare datasets—EMRs, claims, registries, and wearables.
Pharmacovigilance and safety-monitoring professionals looking to integrate RWE methods into signal detection and post-marketing surveillance.
Market-access, HEOR, and health-economics specialists requiring hands-on experience with RWE for value dossiers and reimbursement strategies.
Regulatory-affairs and quality-assurance staff responsible for preparing real-world evidence packages for label expansions and safety updates.
Healthcare-IT and informatics professionals aiming to implement EDC systems, CDISC standards, and data-privacy protocols in clinical and RWE projects.
Early-career researchers, graduate students, and career changers who aspire to enter the rapidly growing field of real-world evidence and data-driven healthcare research.




   
   
   

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