AstraZeneca & Johns Hopkins National Healthcare Case Competition
Prompt Develop a go-to-market strategy for a novel oncology treatment requiring routine ctDNA monitoring, shifting physician behaviour toward regular molecular testing.
Core Contributions
Stakeholder Research
Led discovery with oncologists, patient advocacy leaders, and potential diagnostic partners to map friction between clinical innovation, reimbursement, and everyday workflow.
Landscape & Workflow Analysis
Synthesized clinical, operational, and legal constraints to design a GTM approach that could plug into existing hospital pathways without adding cognitive load or admin burden.
Advanced through initial screening (essay + application) as 1 of 12 teams from 72 → delivered GTM recommendations to AstraZeneca leadership panel.
University of Pennsylvania Healthcare Case Competition
Prompt Recommend a new indication for an inhaled drug delivery platform that offers the strongest combined scientific and commercial rationale.
Core Contributions
Competitive & Indication Landscape
Led analysis of target diseases and competitors to identify spaces where inhaled delivery could create meaningful clinical differentiation.
Cross-Functional Synthesis
Worked closely with scientists, business students, and legal experts to balance efficacy data, IP risks, and market access considerations.
Co-developed and pitched a focused indication strategy to the sponsoring company, highlighting a clear path from mechanism of action → clinical value → payer story.
Gilead Clinical Trials Case Competition
Prompt Recommend an initial set of clinical trial sites in Africa for a tuberculosis study, balancing feasibility, data quality, and equity.
Core Contributions
Site Selection Criteria Design
Defined and weighted criteria such as historical enrollment, lab capacity, data quality, and regional TB burden to move beyond "convenience" site selection.
Decision-Support Dashboard
Built an interactive dashboard enabling clinical operations teams to compare candidate sites and simulate different weighting scenarios.
Delivered a ranked site shortlist and decision tool that made trade-offs transparent, positioning the recommendation as an operational asset rather than a static slide.
Cleveland Clinic Digital Health & AI Case Competition
Prompt Propose two digital health / AI solutions for Cleveland Clinic that improve both physician experience and patient outcomes, including build-vs-buy recommendations.
Core Contributions
Digital Health Landscape Scan
Researched existing tools, internal capabilities, and integration constraints to shortlist viable solution spaces.
Evaluation Framework & Storytelling
Designed a criteria matrix (impact, adoption risk, integration effort) and led slide development to clearly argue build vs. buy for each concept.
Presented two implementation-ready concepts with explicit trade-offs and risk mitigations.