Program Structure (Humanized)

Module 1: The Clinical Research Big Picture (How Biomedical Science Fits In)

• What clinical research really is: evidence generation, patient impact, and decision-making.
• How biomedical science supports trials: from understanding disease to measuring outcomes.
• Key vocabulary you’ll use throughout: endpoints, biomarkers, cohorts, arms, and outcomes.

Module 2: Cells, Tissues, and the Language of the Human Body

• Core cell biology: membranes, signaling, growth, apoptosis (why it matters in disease).
• Basic tissue types and how organs maintain function.
• Inflammation and immune response as a “common thread” in many conditions.

Module 3: Disease Mechanisms (From Normal Function to Pathology)

• How diseases start and progress: infection, degeneration, metabolic disorders, cancer concepts.
• Pathophysiology made practical: symptoms, lab values, and clinical significance.
• How researchers define disease severity and progression for trials.

Module 4: Biomarkers, Diagnostics, and Clinical Measurements

• What biomarkers are and how they’re used: diagnostic, prognostic, predictive, pharmacodynamic.
• Understanding common clinical tests and what they indicate (workflow-level interpretation).
• Basics of sensitivity, specificity, ROC thinking, and false positives/negatives.

Module 5: Therapeutic Principles (How Treatments Are Designed)

• How drugs interact with targets: receptors, enzymes, pathways (intro level).
• Pharmacology essentials: ADME, dose-response, therapeutic index (conceptual).
• Therapy categories: small molecules, biologics, vaccines, gene/cell therapy (overview).

Module 6: Clinical Research Study Designs (Choosing the Right Approach)

• Observational vs interventional studies, RCT basics, and why randomization matters.
• Phase I–IV logic (high-level): safety → efficacy → comparison → real-world evidence.
• Endpoints and outcomes: primary vs secondary, surrogate endpoints, and clinical relevance.

Module 7: Data, Statistics, and How to Read Clinical Results

• Understanding study results: effect size, p-values vs confidence intervals (practical meaning).
• Bias and confounding: what can break a study and how researchers reduce it.
• Reading tables and figures: baseline characteristics, adverse events, outcome comparisons.

Module 8: Ethics, Patient Safety, and GCP Mindset

• Informed consent: what it means in practice and why it matters.
• Ethics committees/IRB role and participant protection principles.
• Adverse events vs serious adverse events (SAE), reporting mindset (high-level).
• Data privacy and confidentiality basics.

Module 9: Clinical Research Operations (How Trials Actually Run)

• Key roles: PI, CRC, CRA, sponsor, CRO (who does what).
• Protocol basics: inclusion/exclusion criteria, visits, procedures, and deviations.
• Source data, CRFs/eCRFs, monitoring concepts, and audit readiness (overview).

Module 10: Translating Biomedical Knowledge into a Research Career

• How to convert biomedical concepts into research questions and hypotheses.
• Basics of writing: background, objectives, methodology, and outcome interpretation.
• Career pathways: clinical research, biomedical research support, regulatory/quality, healthcare analytics.

Final Project

• Develop a mini clinical research concept note for a biomedical topic of your choice.
• Define disease background, biomarker/endpoint plan, study design, and ethical considerations.
• Example projects: biomarker-driven study outline for diabetes risk, observational study plan for asthma triggers, trial concept for a novel therapy (non-clinical framing).