Commercialization of Academic Science
Spring Semester 2026

The Mack Institute’s Commercialization of Academic Science (MGMT 891) is hands-on course where MBA student teams collaborate with Penn researchers to explore the real-world potential of early-stage technologies. Students gain practical experience applying commercialization frameworks at the intersection of strategy, innovation, corporate venturing, and entrepreneurship.

Apply by Friday, December 19

Course Description and Guidelines

This 1.0-credit experiential learning course matches small teams of MBA students with innovative technologies developed by Penn researchers. Students will engage directly with inventors to understand the science behind early-stage innovations and explore their potential for commercialization. In some cases, established corporations may also be involved, providing additional industry context and pathways to impact. Through a combination of instructor-led discussions on commercialization frameworks and independent team research, students will gain hands-on experience at the intersection of strategy, innovation, corporate venturing, and entrepreneurship.

Students must apply to be considered for the course. Applications are due December 19, 2025. The course is open to second-semester and second-year MBA students; Wharton Executive MBA (WEMBA) students may also be considered. Ideal candidates have experience or a strong interest in commercialization, innovation, or entrepreneurship. 

View full syllabus here

Applications are open! Apply here

Spring 2026 Projects

To read full project descriptions, click the titles.

1) Smart-Habits: AI-Enabled Home BP Engagement for Kidney Health

Sponsor Introduction: Dr. Sarah Schrauben is an Assistant Professor of Medicine and Epidemiology at the University of Pennsylvania. Her research focuses on improving functional health, self-management, and cardio-kidney-metabolic outcomes for people living with chronic kidney disease (CKD). She leads NIH-funded clinical research and has conducted feasibility trials of Smart-Habits, a digital intervention designed to improve blood pressure control and behavioral engagement in CKD. Her work integrates clinical research, implementation science, and digital innovation to address gaps between patient behavior, remote monitoring, and effective clinical decision-making.  

Why: Hypertension affects the vast majority of individuals with CKD and is a primary driver of kidney decline, cardiovascular complications, and hospitalizations—together contributing over $200 billion annually to U.S. healthcare costs. Yet fewer than half of patients achieve adequate blood pressure control. Persistent clinical inertia and limited patient motivation—exacerbated by fragmented data, episodic visits, and inadequate feedback loops—prevent effective management. 

Existing remote monitoring tools often fail to sustain patient engagement or integrate home BP data meaningfully into clinician workflows. There is a critical need for a scalable solution that connects home BP monitoring with timely, actionable feedback for both patients and providers. Smart-Habits aims to address this gap.  

Project Scope: This project explores the market potential and commercialization strategy for Smart-Habits, an AI-enabled digital platform that: 

  • Integrates with home BP devices and electronic health records using secure APIs and SMART-on-FHIR; 
  • Delivers AI-driven conversational “micro-coaching” to support medication adherence and BP self-monitoring; 
  • Provides clinicians with actionable insights and alerts to reduce therapeutic inertia; 
  • Targets high-risk patients with CKD who require improved hypertension management.  

The goal is to evaluate feasibility, define value propositions for key stakeholders, and develop commercialization pathways for health systems, payers, and potential industry partners. 

Students Will 

  • Conduct customer discovery with patients, nephrologists, population health leaders, and payers to understand unmet needs. 
  • Develop a market analysis, including segmentation and TAM/SAM/SOM estimates. 
  • Analyze the competitive landscape across digital health and BP engagement platforms. 
  • Define Smart-Habits’ value proposition for providers, payers, and health systems. 
  • Recommend go-to-market strategies, pricing models, and partnership opportunities. 
  • Propose a scaling plan, including reimbursement considerations and a 12–24 month commercialization roadmap.  

How (Methods) 

  • Apply frameworks such as Business Model Canvas, TAM/SAM/SOM, Porter’s Five Forces, and reimbursement assessment. 
  • Conduct stakeholder interviews to validate clinical relevance and purchasing priorities. 
  • Benchmark Smart-Habits against existing BP engagement and remote monitoring tools. 
  • Use design-thinking and lean startup methods to propose refinements and pilot strategies. 
  • Evaluate regulatory pathways, integration requirements, and cost considerations.  

Who (Qualifications) 

Ideal teams include MBA and WEMBA students with interests in: 

  • Digital health, medtech innovation, or value-based care 
  • AI-enabled health tools and data integration 
  • Entrepreneurship, product strategy, or healthcare consulting 

Experience with customer discovery, market analysis, product-market fit, or health system operations is beneficial.  

Deliverables 

  • Market analysis and opportunity sizing 
  • Competitive landscape assessment 
  • Value proposition and Business Model Canvas 
  • Go-to-market and partnership strategy 
  • Commercialization roadmap (12–24 months) 
  • Final presentation and brief report summarizing insights and recommendations  

Success Metrics 

Success will be evaluated based on: 

  • Clarity and feasibility of the proposed commercialization pathway 
  • Strength of stakeholder validation and competitive differentiation 
  • Quality of go-to-market and funding recommendations 
  • Demonstrated potential for Smart-Habits to reduce clinical inertia and improve BP management in CKD populations  

2) Osteopontin Fragments for the Treatment of Sarcoidosis

Sponsor Introduction: Dr. Thomas Leung is a physician-scientist in the Department of Dermatology at the University of Pennsylvania and the Philadelphia VA Medical Center. He earned his undergraduate degree from Stanford University and completed his MD/PhD through the UCLA–Caltech MSTP program, training under Nobel laureate Dr. David Baltimore. 

Dr. Leung’s laboratory brings together biologists, clinicians, and computational scientists to study how skin and other organs respond to injury and inflammation. His team integrates fundamental immunology with precision medicine approaches to uncover how immune responses shape healing, scarring, and disease. Their discoveries have already informed improved care for patients, and the lab is committed to advancing new diagnostic and therapeutic strategies from bench to bedside. 

Why: Sarcoidosis is a rare inflammatory disorder driven by the formation of granulomas—dense clusters of immune cells that can accumulate in any organ. Patients experience fatigue, respiratory difficulty, and painful skin, eye, or joint involvement. The current standard of care relies heavily on long-term corticosteroids, which reduce inflammation but cause serious side effects including diabetes, osteoporosis, immunosuppression, and weight gain. There is a profound unmet need for safer, targeted therapies. 

To uncover new therapeutic targets, Dr. Leung’s team analyzed skin and blood samples from 28 patients with sarcoidosis and non-sarcoid granulomas. The data revealed that macrophages in sarcoid granulomas express high levels of osteopontin (OPN), a protein known to regulate inflammation. Importantly, OPN becomes biologically active when cleaved by thrombin into smaller fragments. 

Using a validated mouse model, the team demonstrated that: 

  • Mice lacking OPN form significantly fewer granulomas. 
  • Mice engineered with thrombin-resistant OPN also show reduced granuloma formation. 

These findings indicate that thrombin-cleaved OPN fragments—rather than full-length OPN—play a critical role in granuloma development. 

Building on these insights, the lab developed two novel antibodies that selectively block thrombin-cleaved OPN. In mouse studies, both antibodies drastically reduced granuloma formation and accelerated the resolution of existing granulomas—providing strong proof-of-concept for a first-in-class targeted therapy for sarcoidosis. 

Project Scope: This project evaluates the commercialization potential and strategic path for a novel antibody therapeutic targeting thrombin-cleaved osteopontin (OPN) for sarcoidosis. The therapy represents a precision-based, first-in-class approach that could fill a major gap in treatment and reduce reliance on long-term corticosteroids. 

Students Will 

  • Conduct customer discovery with clinicians, patients, and pharmaceutical partners to identify key needs and drivers of adoption. 
  • Perform a market analysis that segments the sarcoidosis ecosystem by geography, healthcare setting, disease subtype, and payer environment. 
  • Assess the competitive landscape of biologics, immunomodulators, and emerging therapies relevant to sarcoidosis and granulomatous disease. 
  • Define a compelling value proposition articulating scientific differentiation, clinical relevance, and health-economic advantages. 
  • Recommend commercialization and go-to-market pathways, including licensing, co-development, startup formation, or hybrid models. 
  • Outline a strategic roadmap for translation from academic discovery to industry partnership, including regulatory, manufacturing, and reimbursement considerations. 

How (Methods) 

  • Stakeholder interviews with dermatologists, pulmonologists, pharmaceutical executives, and patient advocacy leaders. 
  • Application of Business Model Canvas, Porter’s Five Forces, and TAM/SAM/SOM methods to define opportunity size and positioning. 
  • Benchmarking against recent rare-disease biologics and successful immunology therapeutics. 
  • Financial modeling to evaluate pricing, reimbursement dynamics, and partnership or exit scenarios. 
  • Assessment of regulatory pathways, including opportunities for orphan drug designation, fast-track review, and early-access programs. 
  • Use of lean startup and design-thinking frameworks to refine value propositions and identify key commercialization inflection points. 

Who (Qualifications) 

Ideal teams include MBA and WEMBA students or interdisciplinary groups with interests in: 

  • Biopharma commercialization, life sciences innovation, or healthcare consulting 
  • Strategy and business development in biotechnology or pharmaceutical settings 
  • Venture creation, early-stage funding, or academic technology translation 
  • Rare-disease therapeutics, clinical development, or immunology-driven innovation 

A willingness to engage deeply with both science and strategy is highly valued. Scientific background is not required, but curiosity is. 

Deliverables 

  • Market analysis and stakeholder segmentation 
  • Competitive landscape and unmet needs assessment 
  • Value proposition and translational roadmap 
  • Go-to-market and partnership strategy 
  • Final presentation and brief report summarizing insights and recommendations 

3) Outdoor Radiant and Conductive Cooling (ORCC)

Sponsor Introduction: Dorit Aviv is an Assistant Professor of Architecture at the University of Pennsylvania’s Weitzman School of Design and the Director of the Thermal Architecture Lab. Her research integrates architectural design, material science, and environmental engineering to develop low-energy, climate-responsive systems that advance human comfort and environmental resilience. 

The Thermal Architecture Lab has pioneered innovative approaches to passive and hybrid thermal regulation, including radiant and conductive cooling technologies that offer sustainable alternatives to conventional air-conditioning in challenging environments. 

Why: Cities worldwide face rising temperatures, intensifying heat waves, and worsening urban heat island effects. Outdoor cooling—particularly for vulnerable or underserved communities—has become an urgent public health and climate adaptation need. Yet conventional air-conditioning is energy-intensive, expensive, and largely ineffective in open-air settings. 

The Outdoor Radiant and Conductive Cooling (ORCC) system builds on the Thermal Architecture Lab’s OMARC radiant cooling technology and integrates an additional conductive cooling component: the cooling bench. Together, these technologies form a scalable, energy-efficient outdoor cooling suite with several advantages: 

  • Thermal comfort efficiency: Conductive cooling through a bench cools a seated person far more effectively than radiant cooling alone. 
  • Energy efficiency: Water used for the radiant panels can be reused—slightly warmed—to operate the bench with no additional energy input. 
  • System-level value: Combining radiant and conductive systems improves performance, adaptability, and commercial viability. 

With prototypes now validated and multiple derivative applications emerging—including Tenopy, KlimaKover, and mobile units) ORCC is poised for evaluation of real-world deployment models, commercialization strategies, and long-term market potential. 

Project Scope: This project focuses on developing a comprehensive commercialization roadmap for the ORCC system and its related applications. Students will identify high-value use cases, validate demand through customer discovery, evaluate the competitive landscape, and articulate business models and partnership pathways for scalable deployment. 

Students Will 

  • Conduct customer discovery across public, commercial, institutional, and event-based sectors. 
  • Develop a market segmentation analysis (e.g., cities, event organizers, NGOs, architecture and design firms). 
  • Explore use cases such as public cooling stations, outdoor venues, disaster relief, climate-resilient architecture, and pop-up installations. 
  • Define value propositions tailored to different customer personas. 
  • Assess competing or alternative cooling solutions and establish technology positioning. 
  • Propose go-to-market strategies, including early deployment partners and pilot opportunities. 
  • Recommend sustainable business models and partnership strategies for commercialization. 

How (Methods) 

Students will apply innovation, commercialization, and design-thinking frameworks, including: 

  • Market Analysis: Map customer segments including municipalities, NGOs, developers, architects, public health organizations, and event planners. 
  • Customer Discovery: Conduct interviews to understand unmet needs, procurement constraints, and decision-making processes. 
  • Competitive Benchmarking: Evaluate alternatives such as misting systems, shading structures, HVAC-based cooling pavilions, and passive cooling interventions. 
  • Business Model Development: Explore licensing, productization, B2G/B2B contracting, consortium-based models, and social enterprise options. 
  • Value Proposition Design: Craft segment-specific messaging around benefits such as zero-energy operation, mobility, thermal performance, or public health impact. 
  • Go-to-Market Strategy: Identify pilot deployment opportunities, demonstration sites, and early adopters. 
  • Partnership Development: Identify collaboration opportunities with municipalities, climate adaptation nonprofits, event organizers, and architecture firms. 

Who (Qualifications) 

Ideal teams include students with interests or experience in: 

  • Entrepreneurship and innovation strategy 
  • Technology commercialization 
  • Architecture, sustainability, or climate-resilient design 
  • Public health or environmental policy 
  • Business development, market research, or strategic partnerships 

Interdisciplinary teams are strongly encouraged, combining technical, commercial, and social-impact perspectives. 

Deliverables 

Students will produce a strategic business case and supporting documentation, including: 

  • Market assessment with segmentation and use-case analysis 
  • Customer personas and summaries of stakeholder feedback 
  • Competitive landscape and positioning framework 
  • Value proposition development for key segments 
  • Go-to-market strategy with phased rollout and early-adopter targets 
  • Recommended business model(s) and revenue strategy 
  • Partnership development plan for collaborators, funders, or pilot hosts 
  • Risk assessment, success metrics, and a sustainability roadmap 

4) University Atlas (UAtlas): Designing a Sustainable Platform to Visualize and Connect Research Communities

Sponsor Introduction: The University Atlas (UAtlas) is an innovative platform developed at the University of Pennsylvania to map research activity and reveal knowledge networks within and across institutions. By increasing the visibility and discoverability of university-based research, UAtlas supports collaboration, strategic planning, and external engagement. After gaining traction at Penn and interest from external institutions, UAtlas is now moving toward becoming a sustainable venture capable of serving a broad range of academic and industry partners. 

This spring semester project is a direct continuation of the work conducted in the fall class. Students will build on customer discovery insights, market assessments, and preliminary recommendations generated last semester to advance UAtlas toward a scalable, investment-ready venture. 

Why: While universities generate immense research output, the landscape remains difficult to navigate for internal and external stakeholders alike. Faculty, students, administrators, industry partners, funders, and collaborators often struggle to identify relevant research, experts, or initiatives. This lack of visibility slows interdisciplinary work, limits our understanding of institutional strengths, and reduces opportunities for engagement and partnership. 

UAtlas addresses these challenges by providing interactive, data-driven maps of research communities—augmented by planned AI-powered search and natural language Q&A tools. As interest in the platform grows, this semester focuses on maturing the venture model, clarifying its offering, and preparing it for sustainable growth. 

What (Scope of Work for Spring Semester): This semester’s project builds directly on the fall team’s customer discovery, stakeholder interviews, market segmentation, and early business model exploration. Students will use those insights to move the venture toward finalization of its business model, pricing strategy, and go-to-market plan. 

Students will: 

  • Synthesize and refine findings from the fall semester’s customer and market discovery research. 
  • Finalize the UAtlas business model through structured evaluation of revenue options, institutional partnerships, and organizational structure. 
  • Develop pricing strategies tailored to key customer segments. 
  • Build the foundation of a go-to-market strategy, including value messaging, customer acquisition pathways, and partnership opportunities. 
  • Prepare investor-ready materials that clearly articulate market opportunity, business model, competitive advantage, and financial sustainability. 
  • Create customer-facing materials that support institutional adoption, including overview decks, use-case demonstrations, and pilot program proposals. 

The semester culminates in polished investor and customer presentations intended to support real-world stakeholder engagement and future fundraising or partnership discussions. 

How (Methods)

Students will apply venture design methodologies and strategy tools, including: 

  • Integration and analysis of customer discovery data generated in the fall semester 
  • Validation of pricing and business model options through targeted follow-up outreach 
  • Financial modeling and scenario planning 
  • Go-to-market strategy development, including segmentation, positioning, and messaging 
  • Preparation of investor pitch materials and customer presentations 
  • Competitive and benchmarking updates to guide differentiation strategies 

Who (Recommended Student Background) 

This course is ideal for students interested in: 

  • Venture design and early-stage business development 
  • Higher education innovation, research ecosystems, and academic infrastructure 
  • Social impact ventures and mission-driven business models 
  • Nonprofit, public benefit, and hybrid organizational structures 
  • Bringing data-driven digital platforms to market 

Students with experience in consulting, entrepreneurship, product strategy, market research, or financial modeling will find this project especially rewarding, though these skills are not required.  

5) Commercialization Strategy for the CiPD EDIBLE Project

Sponsor Introduction: The Center for Innovation & Precision Dentistry (CiPD) is a cross-disciplinary initiative uniting Penn Engineering and Penn Dental Medicine to advance the next generation of oral healthcare solutions. CiPD’s mission is to drive breakthroughs at the intersection of materials science, nanotechnology, AI, robotics, and clinical dentistry. With a strong focus on translational impact, the Center cultivates industry partnerships and public health collaborations to bring innovative, accessible oral health products to diverse populations.   

Why: Tooth decay remains the most prevalent chronic childhood disease globally, disproportionately affecting underserved communities. Traditional oral health solutions are effective but often inaccessible due to cost, infrastructure, or clinical delivery barriers. EDIBLE offers a novel, non-invasive, low-cost, and child-friendly approach that can be deployed in both clinical and non-clinical settings—including schools, community health programs, and low-resource environments. 

The next phase of the project requires rigorous refinement of EDIBLE’s value proposition, business model, pricing strategy, and go-to-market approach across key segments identified in the fall semester. 

Project Scope: This spring project builds directly on the work completed by the Fall 2025 student team, who conducted early customer and market discovery for EDIBLE, an innovative line of food-grade products designed to disrupt oral biofilms and prevent tooth decay. The fall team explored multiple market pathways, generated initial segmentation insights, and produced early recommendations for EDIBLE’s commercialization. 

In this continuation, students will take these findings as a foundation and develop deeper, more actionable commercialization strategies tailored to specific markets of interest to CiPD.  Students will refine and operationalize the commercialization strategy through: 

  • Prioritization of high-potential market segments  
  • Development of tailored value propositions for each priority segment 
  • Creation of detailed business models, including revenue and partnership structures 
  • Pricing strategy development for B2B, B2C, and hybrid models 
  • Go-to-market strategies with attention to channels, partnerships, regulatory considerations, and scale 
  • Deeper exploration of partnerships with NGOs, health systems, school districts, foundations, and global health implementers 
  • Recommendations for pilot designs informed by stakeholder insights and cost considerations 

Student Will

Students will synthesize the fall team’s research and conduct targeted new discovery to produce an integrated, high-fidelity commercialization plan. Deliverables will include: 

  • Refined customer segmentation and prioritized target markets 
  • Articulated value proposition(s) for selected segments 
  • Business model options with revenue projections 
  • Pricing strategy backed by market research and unit economics 
  • Go-to-market strategy with recommended channels, partnerships, and rollout steps 
  • Pilot design framework(s) for school-based or public health deployment 
  • Updated pitch materials for partners, investors, and global health audiences 

How (Methods) 

Students will use a combination of strategic, analytical, and user-centered approaches, such as: 

  • Secondary research and synthesis of fall team deliverables 
  • Targeted customer and stakeholder interviews (clinicians, parents, NGOs, school administrators, public health leaders, industry experts) 
  • Market segmentation refinement 
  • Competitive analysis updates 
  • Regulatory and reimbursement pathway validation 
  • Business model prototyping and financial modeling 

Who (Qualifications) 

Ideal for MBA and interdisciplinary graduate students interested in: 

  • Commercializing health and biotech innovations 
  • Strategy consulting, product strategy, or entrepreneurship 
  • Consumer health, global health, or public health delivery models 
  • Innovation in underserved or resource-limited markets 
  • Business model and go-to-market development 

Deliverables 

Final outputs will include: 

  • A clear and prioritized market strategy for EDIBLE 
  • A high-quality pitch deck and narrative commercialization document 
  • Refined value propositions and business models for target segments 
  • Pricing strategy and early financial projections 
  • Go-to-market roadmap with partnerships, channels, and rollout steps 
  • Pilot implementation plan for schools or public health settings 

Success Metrics 

Success will be measured by the clarity, rigor, and strategic depth of: 

  • The refined market prioritization 
  • The feasibility and sustainability of proposed business models 
  • The strength and applicability of pricing and go-to-market strategies 
  • Recommendations for impactful deployment in underserved and global health settings 

6) Building Sustainable AI-Enabled Solutions for Pediatric Mental Health: Strategy for the PROSPER Center

Sponsor Introduction: The PROSPER Center (Precision Personalized Pediatric Psychiatry) at the Children’s Hospital of Philadelphia (CHOP) is led by Dr. Ran Barzilay, MD, PhD, a child psychiatrist with deep expertise in multimodal data and clinical insight generation. He is joined by Dr. Scott Haag, PhD, Director of Technology and an expert in AI development and complex data systems. The center is situated within CHOP—one of the first pediatric hospital systems to digitize its EHR, now maintaining over one million patient records, offering an unparalleled data foundation for clinical AI innovation.

The PROSPER Center is launching formally in January with secured funding for a 3-year operating budget, a growing team including the Center Director, the Director of technology, lead Product, lead Operations, and strong institutional support. Their goal is to build intelligent, clinically aligned AI systems that help clinicians, patients, and families navigate the complexities of pediatric mental health care. 

Why: Pediatric mental health is in crisis. One in five adolescents has a diagnosed mental or behavioral health condition, with sharp rises in anxiety and depression in recent years. In 2023, 20% of high school students reported seriously considering suicide, and 9% attempted suicide that year . 

Yet treating pediatric mental health remains extremely difficult: 

  • Mental health conditions are caused by bio-psycho-social factors requiring a holistic, contextualized understanding of the patient.
  • Critical information is scattered across disparate systems—clinical, environmental, school-related, social—and therefore not available when clinicians need it.
  • Patients, families, and clinicians must navigate complex, fragmented systems where effective advocacy is nearly impossible. 
  • Increasingly, young people seek mental health support outside traditional care, including through generative AI conversations—more than 1 million people have discussed suicide with ChatGPT, illustrating both need and risk. 

Meanwhile, technology developers in the market-driven attention economy are incentivized to maximize engagement, not well-being. Pediatric clinicians cannot influence the information environment (“technology diet”) that shapes patient behavior, risk, and distress. 

The alignment problem is core: Pediatric mental health needs technology that is clinically grounded, ethically aligned, and socially responsible—not driven by engagement economics. 

PROSPER aims to address this gap by building AI systems that: 

  • Integrate diverse patient data sources to give clinicians a real-time, comprehensive view of the child’s health story . 
  • Use Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP) to surface relevant insights from across the child’s medical, social, and environmental history. 
  • Employ agentic AI to support and advocate for patients within complex hospital systems, from report generation to appointment scheduling to risk escalation . 

To succeed, however, PROSPER must not only build AI technologies—it must build a sustainable market and partnership ecosystem that supports their responsible development and adoption. 

Project Scope 

This project centers on helping PROSPER define the commercial, competitive, and sustainability pathways for a future suite of pediatric mental-health-focused AI technologies. Because the center may develop multiple tools (e.g., clinical support software, exposome assessment tools, patient-facing digital agents, scheduling algorithms), the team needs a structured analysis of: 

Potential product categories:

  • Patient-facing digital tools 
  • Clinical decision support tools integrated with EHR systems 
  • Hospital-operations solutions (e.g., scheduling algorithms, triage optimization) 

Competitive ecosystems for each category: 

  • Pediatric-focused mental health apps and digital therapeutics 
  • EHR-integrated clinical support software 
  • Enterprise solutions addressing systemwide hospital needs 
  • Generative AI wellness tools used by patients outside clinical care 

Sustainability models: 

  • FDA-regulated clinical decision support tools 
  • Reimbursement and philanthropy-supported digital health 
  • Enterprise licensing and hospital partnerships 
  • Hybrid models supporting both clinical systems and patients at home 
  • Market models that avoid misaligned incentives common in consumer mental-health technology 

Strategic priorities:

  • Inform PROSPER’s decision on which technologies to build first and how to build a long-term sustainable platform. 

Students will synthesize PROSPER’s current status—launching in January, identifying problem priorities through clinic-by-clinic intake, developing their first MVP for completion by late 2026, establishing a stakeholder board in Q1 2026, and seeking strategic philanthropy and industry partnerners—and translate these into a commercialization roadmap. 

Students Will 

  • Conduct customer discovery with clinicians, pediatric mental health specialists, hospital administrators, patient advocates, and potential industry partners. 
  • Map the competitive landscape across consumer mental health tech, clinical decision support tools, and hospital enterprise software. 
  • Segment potential markets: patient-level, clinic-level, enterprise-level, and cross-institutional. 
  • Evaluate regulatory and technological pathways, including FDA Algorithmic Medical Device certification for clinical tools. 
  • Assess sustainability and revenue models for different categories of products. 
  • Recommend a focused strategy for PROSPER’s first product(s) and longer-term platform development. 
  • Develop a translational strategy connecting clinical relevance, technology feasibility, and market alignment. 

How (Methods) 

Students will apply innovation, health-tech commercialization, and venture strategy frameworks, including: 

  • Customer Discovery: Interviews with clinical providers, administrators, policymakers, and digital health companies. 
  • Market Mapping and TAM/SAM/SOM Analysis: Across patient apps, clinical support systems, and enterprise hospital solutions. 
  • Competitive Benchmarking: Comparing PROSPER’s opportunities to current mental health apps, EHR-integrated analytics tools, scheduling platforms, and agentic AI tools used in health systems. 
  • Regulatory Pathway Assessment: FDA considerations for AI-driven clinical decision support, privacy constraints, and pediatric data requirements. 
  • Business Model Design: Licensing, integration partnerships, B2G/B2B enterprise contracts, philanthropic-supported models, hybrid sustainability structures. 
  • Go-to-Market Strategy: Identification of early pilot partners, rollout sequencing, value messaging, and ecosystem partnerships. 
  • Impact Alignment: Ensuring technology supports clinical objectives, patient safety, and ethical pediatric mental health care. 

Who (Qualifications) 

Ideal for students interested in: 

  • Digital health innovation and AI strategy 
  • Pediatric mental health, public health, or clinical decision support 
  • Venture design, commercialization, and early-stage business strategy 
  • Health system operations, EHR integration, and regulatory pathways 
  • Social-impact ventures and technologies aligned with mission-driven care 

No technical or clinical background is required—just curiosity and a desire to shape ethical, sustainable health innovation. 

Deliverables 

  • Market landscape analysis with segmentation across patient, clinical, and enterprise software categories 
  • Competitive benchmarking across pediatric mental health, EHR-integrated tools, and AI agents 
  • Stakeholder personas and summaries of interviews 
  • Sustainability and business model recommendations for multiple product pathways 
  • Go-to-market and partnership strategy 
  • Strategic roadmap identifying recommended product focus, MVP trajectory, and long-term platform development 
  • Final presentation and concise report integrating insights and actionable recommendations 

7) Deliberation Lab: Scaling High-Quality Dialogue Through Research-Driven Conversation Technology

Sponsor Introduction: The Deliberation Lab is an advanced platform for studying, improving, and scaling live, synchronous human conversations. Developed at the Computational Social Science Lab at the University of Pennsylvania, the platform is built atop the open-source Empirica framework and automates the logistics required to run real-time, high-throughput conversation experiments. 

In one recent study, the system enabled over 400 cross-partisan conversations in just two weeks, compressing a traditionally year-long effort into a single sprint and unlocking cleaner causal inference and richer behavioral insights. 

The Deliberation Lab is now transitioning from a purely academic infrastructure to a commercially viable platform designed to support researchers, educators, community organizations, and corporate teams. Recent strategy discussions with the Mack Institute demonstrate strong alignment with Wharton’s Innovation Ecosystem and a clear pathway toward market-ready tools for research, training, and high-stakes professional deliberation. Students will work directly with the Deliberation Lab team: James Houghton, Duncan Watts, and Anushkaa Gupta. 

Why: High-quality conversation underpins effective governance, teamwork, conflict resolution, leadership development, and civic life. Yet most conversations are: 

  • unstructured 
  • unmeasured 
  • unsupported by tools grounded in behavioral science 

At the same time, organizations across sectors increasingly require scalable training, structured dialogue tools, and real-time behavioral insights. Existing virtual meeting platforms prioritize convenience, not deliberation quality or scientific rigor. 

The Deliberation Lab fills this need by combining social-science methodology with a modern experimentation and facilitation interface. But to achieve sustained real-world impact, the platform must evolve into a self-sustaining commercial entity. 

Two early commercialization pathways have emerged: 

1. Experimentation Platform (Research Product): a drag-and-drop interface enabling researchers to design, deploy, and analyze synchronous conversation experiments—“Qualtrics for synchronous interaction.” 

2. Virtual Facilitation Platform (Applied Product): a real-world conversation tool that guides teams, classrooms, and community groups through evidence-based structures—“Zoom augmented with behavioral science.” 

Across both pathways, demand is growing from business schools, corporate boards, civic organizations, philanthropic groups, and dialogue networks for structured, reproducible, scientifically grounded conversation tools. 

What (Scope) 

Students will develop a comprehensive commercialization and business strategy for the Deliberation Lab, including: 

  • Market segmentation across research, education, corporate, governance, and civic sectors 
  • Competitive analysis of facilitation tools, training platforms, and virtual meeting systems 
  • Product definition for both the research experimentation platform and applied facilitation platform 
  • Revenue model development (institutional licensing, enterprise tiers, nonprofit/for-benefit hybrids) 
  • A roadmap for the MVP, initial pilots, and a field-ready product 
  • Recommendations for go-to-market and partnership strategies within Wharton and beyond 

How (Methods) 

Market Analysis 

Assess demand across education (especially business schools), corporate governance, bridging organizations, local governments, and research labs. Identify high-value segments and early adopters highlighted during discussions. 

Competitive Landscape 

Benchmark the Deliberation Lab against tools such as Zoom, Miro, breakout-room tools, facilitation apps, and behavioral analytics platforms. Identify differentiators including: 

  • real-time behavioral feedback 
  • controlled experimentation features 
  • synchronous data capture 
  • customizable dialogue structures 

Product Development Strategy 

Define feature sets for: 

  • Lab Version: high-throughput studies and experimentation 
  • Classroom Version: structured training modules 
  • Field Version: secure, enterprise-ready applications 

Revenue Models 

Explore institutional subscriptions, enterprise licensing, premium analytics, consulting support layers, and tiered access for nonprofits. 

Pilot Strategy & Go-To-Market Plan 

Propose pilots with business schools, bridging organizations, and early corporate partners. Consider specialized requirements such as confidentiality, security, and real-time analytics for sensitive environments like boardrooms. 

Sustainability & Risk Management 

Construct a 12–18 month sustainability roadmap aligned with the team’s objective of developing a polished, revenue-generating field-ready product. 

Who (Qualifications) 

Ideal for students with interest or experience in: 

  • Entrepreneurship and technology commercialization 
  • Innovation management and product design 
  • Organizational strategy and business modeling 
  • EdTech, GovTech, HR/organizational behavior, civic tech, or collaboration tools 
  • AI-augmented platforms, conversational AI, or behavioral science 

Students will collaborate with the Deliberation Lab team to translate research-grade infrastructure into a viable commercial offering. 

Deliverables 

Students will produce a PowerPoint presentation and supporting documentation, including: 

  • Market Segmentation & Opportunity Analysis 
  • Competitive Analysis & Positioning Strategy 
  • Product Definition for Research vs. Applied Platforms 
  • Organizational Structure Recommendations 
  • Detailed Revenue Model (licensing tiers, enterprise, training, etc.) 
  • Go-To-Market Strategy (education → corporate → governance) 
  • Pilot Roadmap & MVP Timeline 
  • Sustainability Plan (12–18 months) 
  • Draft Business Plan 

8) Commercializing AI Workflow Orchestration for Cancer Treatment

Sponsor Introduction: Dr. Rafe McBeth is an Assistant Professor of Radiation Oncology and Director of AI at Penn Medicine, where he leads AI strategy across the radiation oncology network. His team has deployed commercial AI tools across more than 25,000 patients and built a proof-of-concept orchestration pipeline that compresses radiation treatment preparation from nine days to just two hours. Dr. McBeth also serves on the ASTRO AI Task Force, helping shape national clinical AI adoption guidelines. His work focuses on closing the gap between AI model development and scalable, real-world deployment in high-stakes clinical environments. 

Why: Cancer patients are waiting longer for treatment—and the delays are deadly. A study of 3.67 million patients in the National Cancer Database found that median time from diagnosis to treatment increased from 21 to 29 days between 2004 and 2013. Each week of delay in curative settings increases absolute mortality by 1.2–3.2% for multiple major cancers. Patients also experience severe anxiety, distress, and diminished psychological well-being while waiting. 

At the same time: 

  • Cancer incidence among adults 65+ is projected to rise 67% between 2010 and 2030. 
  • By 2050, total U.S. cancer cases are expected to increase by ~50%. 
  • Over 90% of radiation oncology practices face staff shortages that already cause treatment delays. 
  • More patients + fewer staff = worsening access and outcomes. 
  • The system cannot scale without a major increase in productivity per unit of staff. 

Why AI Workflow Orchestration? Current AI tools in radiation oncology—contouring, planning, QA—are sold as point solutions. They accelerate individual tasks but do not change the critical path, because each step remains a manual handoff queued behind overextended staff. 

Penn’s proof-of-concept demonstrated that when AI models are chained together intelligently, treatment preparation can shrink from nine days to under two hours. 

The opportunity is not just better AI models—it is a workflow orchestration engine that: 

  • Coordinates and automates handoffs 
  • Minimizes idle time 
  • Learns institutional patterns over time 
  • Embeds itself deeply into clinical workflow 
  • Delivers defensible value beyond commodity AI 

Platform Scalability: Beyond Cancer 

A similar orchestration challenge appears in low-dose radiation therapy (LDRT) for osteoarthritis and other benign conditions, widely used in Central Europe and now re-emerging in the U.S. With 32.5 million Americans affected by osteoarthritis and treatment success rates of 60–70%, adoption could increase radiation therapy episodes by an order of magnitude, making workflow automation even more essential. 

The product could launch as: 

  • A cancer-focused workflow engine with benign indications added later, or 
  • A radiation medicine operating system from the outset. 

What (Scope): Students will assess and translate the commercialization potential of AI-enabled workflow orchestration in radiation oncology—using Penn Medicine’s advanced infrastructure as the reference implementation. The project includes: 

  • Evaluating the value proposition of orchestration versus point-solution AI 
  • Defining product strategy and optimal form factor (enterprise SaaS, managed service, integrated module) 
  • Identifying primary customers (health systems, equipment vendors, payers) 
  • Assessing regulatory implications of orchestration platforms 
  • Determining market readiness and timing 
  • Developing commercialization pathways (spin-out, licensing, co-development, internal asset) 
  • Considering the long-term vision across cancer and benign radiation indications 

Students Will 

Students will conduct a comprehensive strategic evaluation of the opportunity, including: 

Customer Discovery & Workflow Analysis

  • Conduct 15–20 structured interviews with medical physicists, dosimetrists, therapists, radiation oncologists, operations leaders, IT leadership, vendors, and payers. 
  • Map the current treatment workflow, quantify bottlenecks, and compare against a hypothetical orchestrated workflow. 

Market, Competition & Positioning

  • Analyze the competitive landscape for AI point solutions (e.g., Limbus, MVision, Radformation, RayStation, Eclipse) and assess commoditization risk. 
  • Perform TAM/SAM/SOM market sizing for oncology and a second scenario including benign indications (e.g., osteoarthritis). 
  • Apply Porter’s Five Forces and value curve analysis to articulate differentiation for workflow orchestration. 

Value Proposition & Product Strategy

Students will define and evaluate: 

  • The defensible value proposition (workflow orchestration vs. improved AI models) 
  • The optimal product form factor (SaaS orchestration layer, managed service, or deeply integrated platform) 
  • The primary customer (health systems, equipment vendors, or payers) 
  • The regulatory pathway for an orchestration platform leveraging cleared components 
  • Market timing driven by demographic trends and workforce constraints 
  • Whether to position the offering as a cancer workflow product first, or a broader radiation medicine operating system 

Business Model & Go-to-Market Strategy

  • Evaluate commercialization models: spin-out, licensing, vendor partnership, white-labeling, or retaining as an internal Penn asset. 
  • Assess regulatory risks and pathways specific to orchestration. 
  • Propose a go-to-market strategy that addresses long hospital sales cycles and integration challenges. 

How (Methods) 

  • Customer Discovery: Interviews across clinical, administrative, and industry stakeholders. 
  • Market & Financial Analysis: Incidence projections, workforce capacity modeling, extended TAM for benign indications, ROI modeling for health systems. 
  • Competitive Analysis: Vendor mapping and assessment of AI tool commoditization. 
  • Strategic Frameworks: Porter’s Five Forces, value curve analysis, Business Model Canvas. 
  • Regulatory Assessment: High-level FDA pathway considerations for orchestrated systems. 

Who (Qualifications) 

Ideal for students interested in: 

  • Health technology and digital health commercialization 
  • AI and enterprise software in regulated environments 
  • Healthcare operations, workflow redesign, and automation 
  • Venture creation, corporate strategy, and medtech partnerships 

Helpful but not required: 

  • Healthcare consulting or administration 
  • Biomedical engineering or exposure to clinical workflows 
  • Experience in product management or enterprise SaaS 

Clinical training is not required—the core questions are strategic and operational. 

Deliverables 

Value Proposition & ROI Analysis 

  • Clear articulation of orchestration’s value vs. point-solution AI 
  • Quantified ROI based on throughput, staff efficiency, and time-to-treatment reduction 

Market & Competitive Analysis 

  • TAM/SAM/SOM for oncology and benign indications 
  • Competitive landscape and commoditization trajectory 

Strategic Recommendation 

  • Recommended commercialization path (spin-out, licensing, partnership, or internal asset) with assumptions and trade-offs 

Business Model & Go-to-Market Plan 

  • Business Model Canvas 
  • Revenue model and customer segmentation 
  • Pilot strategy and early adopter profile 

Final Presentation & Written Report 

  • Prepared for Penn Medicine leadership and potential partners/investors. 

Success Metrics 

The project will be successful if it produces: 

  • A defensible strategic recommendation grounded in interviews and market data 
  • A quantified market opportunity with sensitivity analysis 
  • A realistic assessment of regulatory and operational barriers 
  • A 6–12 month action plan with recommended next steps 
  • A clear demonstration of how workflow orchestration could meaningfully reduce time-to-treatment and increase departmental throughput

9) PanoRadar: High-Resolution Radio Frequency (RF) 3D Imaging for Next-Generation Autonomous Systems

Sponsor Introduction: Mingmin Zhao is an Assistant Professor in the Computer and Information Science Department at the University of Pennsylvania, with a secondary appointment in the Electrical and Systems Engineering Department. His research focuses on wireless sensing, RF-enabled perception, and computational imaging, bringing together signal processing, machine learning, and robotics. His lab develops next-generation sensing technologies that push the boundaries of how systems perceive and interact with the physical world.  

PanoRadar is an emerging 3D imaging technology from his research group that leverages advanced radiofrequency (RF) sensing to deliver LiDAR-comparable 3D imagery at lower cost, reduced power, and with significantly greater robustness in challenging environments. The technology is currently in the prototype stage, with a U.S. provisional patent application filed, positioning it for commercialization and early pilot testing.  

Why: Across sectors—autonomous vehicles, construction robotics, warehouse automation, search and rescue, and healthcare assistance—robotic and autonomous systems increasingly depend on reliable, high-fidelity perception of their surroundings. While optical sensors like cameras and LiDAR dominate today’s perception stack, they face significant limitations:  

  • Highly sensitive to dust, fog, rain, smoke, and lighting conditions  
  • Expensive and power-intensive, especially LiDAR  
  • Vulnerable in real-world environments where visibility is compromised  

By contrast, RF signals are resilient, able to penetrate visual obstructions, and operate reliably in adverse conditions. However, their longstanding limitation is poor spatial resolution, due to the small number of antennas in traditional RF systems.  

PanoRadar overcomes this fundamental constraint, producing high-resolution 3D RF images that rival LiDAR quality—unlocking robust sensing for environments where optical systems often fail.  

The Solution: PanoRadar is a high-resolution, RF-based 3D imaging system that uses a motor-operated, rotating single-chip millimeter-wave (mmWave) radar integrated with a synthetic cylindrical antenna array to generate detailed 3D reconstructions. This configuration, combined with advanced image-processing algorithms, delivers dense, high-resolution point clouds using compact hardware and low power.

Key Capabilities  

  • LiDAR-comparable 3D imaging at RF cost and power levels  
  • Surface normal estimation for detecting object orientation  
  • Semantic segmentation classifying each pixel by object or category  
  • Object detection and human recognition  
  • Robust performance in dust, fog, rain, smoke, or low-light environments  
  • Efficient computation due to streamlined signal generation and processing  

These capabilities make PanoRadar particularly well-suited for robotics and autonomy applications where conventional sensors are unreliable or unsafe.  

Project Scope: This project will develop a commercialization and go-to-market strategy for PanoRadar as it transitions from prototype to early-stage deployment. Students will identify high-potential use cases, evaluate market demand, and determine value propositions across sectors requiring robust 3D sensing.  

Students Will  

  • Conduct customer discovery with robotics companies, autonomous vehicle developers, construction and industrial automation firms, and public safety organizations.  
  • Segment markets across AV/autonomy, construction tech, defense, logistics, environmental monitoring, and infrastructure inspection.  
  • Benchmark competing technologies, including LiDAR, radar systems, mmWave sensors, and hybrid perception stacks.  
  • Define PanoRadar’s differentiating value propositions for different industries.  
  • Assess technical and regulatory considerations for RF sensing in commercial and safety-critical applications.  
  • Recommend business models (e.g., licensing, OEM partnerships, component sales, or a standalone venture).  
  • Outline near-term pilot opportunities and a development roadmap aligned with current prototype capabilities.  

How (Methods)  

  • Customer discovery interviews with technical leads, robotics engineers, and industry stakeholders  
  • Market sizing and segmentation using TAM/SAM/SOM analyses  
  • Competitive benchmarking vs. LiDAR, radar, and perception system alternatives  
  • Technical feasibility and integration analysis for RF sensing in real-world conditions  
  • Business model exploration, including licensing, OEM integration, and partnerships with sensor manufacturers  
  • Go-to-market strategy development, including pilot programs and early adopter identification  
  • Roadmapping for productization, IP strategy, and commercialization milestones  

Who (Qualifications)  

Ideal for students interested in:  

  • Robotics, autonomy, and frontier sensing technologies  
  • Deep tech commercialization and hard-tech venture creation  
  • Computer vision, RF sensing, or emerging perception systems 
  • Market research, business strategy, or industrial B2B innovation  
  • Technology transfer, IP strategy, or applied research commercialization  

No technical background is required, but curiosity about advanced sensing technologies is valuable.  

Deliverables  

  • Market and segmentation analysis  
  • Competitive landscape and positioning framework  
  • Customer discovery insights and user personas  
  • Value proposition statements for target industries  
  • Proposed go-to-market and partnership strategy  
  • Pricing and business model recommendations  
  • Commercialization roadmap with milestones and risks  
  • Final presentation summarizing insights and recommendations