Home / Research Areas / Rare & Undiagnosed Disease

When the Whole World's Patient Population Fits in One Room

Some conditions affect only a few hundred — or even a few dozen — people worldwide. Standard statistical methods, built for large sample sizes, often simply don't work. This pathway trains you in the specialized methods rare disease research actually depends on: small-sample statistics, patient registries, and natural history study design.

What Researchers in This Area Do

Research Designed for When You Only Have a Handful of Patients

Network and systems approaches are especially valuable here because they let researchers "borrow strength" from biological context — using known pathway relationships to make the most of limited patient data, rather than relying on statistical power from sample size alone.

Apply statistical methods designed for very small sample sizes (exact tests, Bayesian methods) instead of standard large-cohort statistics

Navigate and analyze data from rare disease patient registries, often working with patient advocacy organizations

Design natural history studies documenting how a poorly understood disease actually progresses

Use network and pathway context to generate hypotheses when there isn't enough data for a purely statistical approach

Why It Matters

The First Real Step Toward a Medically Invisible Condition

There are thousands of recognized rare diseases, and the majority still have no approved treatment and, in many cases, no clear understanding of their underlying biology. Patients and families affected by rare disease often spend years pursuing a diagnosis. Research in this area — even a single well-designed registry analysis — can be the first real step toward understanding a condition that has otherwise been medically invisible.

Doctor of Latin ethnicity between 25-35 years old is examining a pregnant woman in the company of a nurse
Sample Research Project

What a Summer Project Looks Like

Rare & Undiagnosed Disease

Characterizing Disease Progression: A Natural History Analysis Using Registry Data

Working with de-identified data from a rare disease patient registry, a student analyzes how a specific rare condition presents and progresses across the patients represented — looking for patterns in symptom onset, disease course, and commonly co-occurring conditions. Because the sample size is small, the student applies statistical methods specifically suited to small cohorts, and considers how known biological pathway information can support conclusions the sample size alone couldn't statistically confirm. Closely mentored by a rare disease clinician-researcher, the project produces a written natural history summary intended to be genuinely useful to the patient community and to researchers designing future studies.

Small-sample statistics
Patient registry navigation
Natural history study design
Research ethics for small cohorts

Course by Track

How Each Level Gets There

Every track takes a shared Fall foundations course, then this area-specific Spring course, then a live mentored summer project.

High School

HS-S-RD

Undergraduate

UG-S-RD

Medical Student

MS-S-RD

Clinician

CL-S-RD