Caroline Flessa, MPH | Clinical Data & Digital Health Leader

0+
Years across clinical and adjacent research: <0 mo
To a novel wearable data governance framework: 0+
Concurrent global eCOA implementations led: 0
Therapeutic areas

I build systems that turn clinical and sensor data into decisions. Across 10+ years in academic research, pharma, CROs, and community and global health nonprofits, I've worked between the scientific teams that need clean, CDISC/SDTM-aligned data and the technical teams that deliver it.

Most recently at Pfizer Digital Sciences, I directed the design and build of a novel QC and governance framework for wearable and digital endpoint data, with no vendor or internal precedent, handed over in under six months. Before that, I was the sole US-based CDM at Kayentis, owning client-facing implementation across 10+ concurrent global eCOA studies, and the main CDM point of contact for a similar portfolio at Clario. In 2026 I began consulting independently as Bridgid Advisory.

I hold an MPH in Epidemiology and Biostatistics, have CDM experience across Phase I–III, and work in Python, SAS, and SQL.

OncologyDermatologyRheumatologyImmunologyRespiratoryReproductive EndocrinologyCNS

Career Path

Founder, Clinical Data & Governance Consultant · Bridgid Advisory

Jan 2026–Present

Advisory practice focused on pre-study data infrastructure decisions: EDC vendor selection, regulatory compliance, and device data integration. Delivered a regulatory-informed vendor comparison framework for a digital health company that informed its platform selection.

Data GovernanceEDC SelectionRegulatory Compliance

Education & Certifications

MPH, Epidemiology & Biostatistics
Boston University School of Public Health
BA, Psychology, Cum Laude
Framingham State University
- Clinical Trials: Good Clinical Practice Specialization, Novartis
- Clinical Trials Operations Specialization, Johns Hopkins
- Faster Together: Enhancing the Recruitment of Marginalized Communities in Clinical Trials, Vanderbilt
- ICH GCP E6(R3), TransCelerate & ICON
- Veeva Vault CDMS & CDB
- REDCap Cloud
Clinical Operations & Compliance
- Change Management for Generative AI and Generative AI & AI Agent Organizational Strategy for Leaders, Vanderbilt
- Responsible AI Governance series, All Tech Is Human
- Ethical Data Handling, Fred Hutch
AI Strategy & Data Governance
- Data Sciences in Pharma and Making Data Science Work for Clinical Reporting, Genentech
- ML in Healthcare and Computer Vision & Sequence Analysis, Cleveland Clinic
- Databricks (Generative AI, AI Agents, Data Engineering)
Data Science in Pharma & Health

Community

Women Applying AI (WAAI): Web Content Manager (2026)
Healthcare Businesswomen's Association (HBA): Connector (2026); Mentee (2025); presented on Executive Presence & Personal Branding to cohort as part of Mentee Program (2026)

Endorsements

“Caroline's blend of technical expertise, attention to detail, and collaborative ethos make her an exemplary candidate for any Clinical Data Manager role. I am confident that she would bring a wealth of knowledge and a positively proactive approach to any team she joins.”

Karnaditya Rana, MBA, MPHAssociate Director, Clinical Data Management · Multi-omics, Precision Medicine & Cancer Gene Therapy

“Caroline would be an asset for any data or project management roles requiring leadership, critical and analytical thinking, and advanced technical knowledge. What stood out most was her dedication to producing quality work, her ability to collaborate, and her consistency in meeting deliverables and deadlines.”

Jessica AbramsDevelopment Director · Kupenda for the Children

Let's Connect

I'm primarily seeking a full-time Associate Director or equivalent senior role in clinical data management, digital health technologies, or research data governance. Onsite, hybrid, or remote.

Get in touch →cmflessa@proton.me

Design for reuse from the start

Modular code, standardized specs, and documentation built to last, so a QC framework or data system can be picked up and applied across studies, not rebuilt each time.

Document for the auditor

Every workflow I build is structured for regulatory and internal governance from day one: validation logs, dataflow maps, and inspection readiness built in, not added at the end.

Work across the aisle

I work closely with programmers on EDC builds, translating test and production specs into data that meets client expectations. At Pfizer, I partnered with data science, biostatistics, and clinical operations to turn new requirements into shared specs, with each data decision traceable to a clinical rationale.

Know the tooling, know its limits

I actively pursue Python, Databricks, and AI coursework so the data practices I recommend reflect where the field is going, and so I can tell the difference between a useful tool and an unvalidated one.

Selected Work · tap a row to expand

Challenge

A wearable study needed a data quality and governance framework for continuous sensor data, with no internal process or vendor precedent to build from.

Approach

Started with a needs assessment, then directed the design and build as the Data Operations lead. Deliverables covered QC code, validation, data lineage, and metrics, and I co-developed reusable master QC requirements with data science and biostatistics.

Outcome

A novel internal framework designed for reuse and handed over for testing, with documentation built for GCP inspection readiness. Program specifics stay confidential; I'm glad to talk through my approach in conversation.

Challenge

A high-visibility global portfolio needed eCOA implementations stood up quickly and correctly, with only one US-based CDM available to lead.

Approach

Led study startup as the sole US-based CDM in charge of implementations, authoring core deliverables (DMPs, DCPs, edit check specs, database build files, and data transfer documentation) while implementing proprietary eCOA SaaS to Sponsor protocols.

Outcome

Led startup across 10+ concurrent global studies, was retained post-handover as the subject matter expert on amendment and data transfer impacts, and trained 3–5 CDMs during a period of restructuring.

Challenge

15+ concurrent global studies required test and production SAS data exports delivered on time without compromising data quality.

Approach

Owned eCOA data management from study setup through database lock, managing instrument and export metadata and removing unnecessary fields that were slowing exports.

Outcome

Zero missed SAS data export deadlines across 15+ concurrent studies, and received the ERT Endeavor Award for measurable, sustained client impact.

Challenge

A digital health company needed to choose an EDC platform and set regulatory-aligned standards for sensor and outcome data.

Approach

Led discovery, then assessed platform options against FDA/EMA expectations and 21 CFR Part 11 for sensor and outcome data.

Outcome

Delivered a vendor comparison and compliance framework over a multi-month engagement; it informed the CSO's platform selection and downstream data standards.

Challenge

Kupenda needed a mobile Child Case Management app and supporting data systems to serve children with disabilities in Kenya, with no dedicated technical staff.

Approach

Consulted through BU School of Public Health, working with the BUSPH team and Kupenda's US and Kenya-based staff on a CommCare build aligned to organizational workflows. Stayed on a year past the coursework to iterate with Kenyan users, and wrote and validated SAS code to analyze piloted app data in-house.

Outcome

App launched and deployed in Kilifi County, Kenya, along with an in-house SAS analysis capability.

Data Science & Analytics

PythonReproducible WorkflowsDataset PrepLongitudinal & Observational DataData Summaries & VisualizationDatabricks (fundamentals)SASSQL

Digital Measures & Endpoints

Wearable & Sensor Data QCSensor-Derived Digital MeasuresPRO / COA Instrument RevieweCOA / ePROProtocol & Amendment Review

Data Quality & Governance

Data Governance & QCEdit Check & Data Transfer SpecsData Specs & RequirementsAudit & Inspection ReadinessVendor System UAT

Standards & Regulatory

CDISC / SDTMGCP / ICH E6(R3)21 CFR Part 11Documentation for Regulatory

Clinical Data Management

Study Startup LeadershipDatabase BuildData Review & CleaningDatabase Lock & CloseoutEDC Systems & ConfigVeeva Vault CDBREDCap

Live Tools & Products Live items link out · Gated items available on request

Live

AI Solution Quality & Risk ScorecardIndependent / Open Source · 2026

AI GovernanceRisk AssessmentRegulated IndustriesLive

Live

Trial Terms: Negotiation Prep for Clinical Data & R&D DealsIndependent / Open Source · 2026

StrategyNegotiationResponsible AIClinical OpsLive

Challenge

Providers and health systems lack a structured, compliance-first way to discover and compare clinical AI models. Regulatory status, evidence level, and bias disclosures sit scattered across vendors, so model selection happens without governance.

Approach

Designed a clinical decision-support platform that puts regulatory status, evidence level, and documented limitations at the center of AI model discovery and comparison, with verified provider access and role-based controls.

Outcome

Gated demo showing compliance-first AI model discovery, comparison, and selection. Built on Base44. Full design available on request.

Request access to this demo

Challenge

People navigating chronic GI and autoimmune diagnostic limbo lack tools that combine daily symptom tracking, validated peer support, and doctor-ready summaries, leaving them without data or validation between appointments.

Approach

Designed a self-management app combining structured daily symptom tracking, peer support organized by symptom cluster, and plain-language summaries built for clinician visits, with personal health data scoped to its owner.

Outcome

Gated demo illustrating patient-centered tracking, community, and doctor-ready reporting. Built on Base44. Full design available on request.

Request access to this demo

Challenge

AI-assisted AE coding tools can introduce automation bias when the governance layer is absent: reviewers approve proposals without working exceptions, and weak matches or serious-event misclassifications go undetected.

Approach

Browser-based governance console built on a fully fictitious dummy study (VRN-204) with synthetic, non-patient data: AI proposes MedDRA terms with confidence scores; reviewers work exceptions (Approve / Remap with reason / Escalate to medical review). Designed with reference to FDA's 2025 draft AI guidance and FDA/EMA good AI practice principles: narrow context of use, risk-matched oversight, full decision provenance.

Outcome

Functional demo on dummy data, not a real study: illustrates compliant AI-assisted AE coding governance, where every decision logs reviewer, timestamp, and reason for audit readiness.

Challenge

Show a measurable physiological response to a calming intervention within a single hackathon day, without overclaiming from what an n=1 design can actually support.

Approach

Led measurement and methodology: designed a within-subject A/B protocol where the participant serves as their own control, moving through baseline, stress induction, intervention, and recovery while capturing HR, HRV (RMSSD), and self-reported distress. Built the honest-caveats framing directly into the deck (n=1, single session, fixed order, known confounds like decay and demand effects) so the result was never presented as more than a proof of concept.

Outcome

Presented live, with the day's data capture centered on a single-participant A/B run framed as a proof of concept.

Challenge

No reusable framework existed for QC of continuous wearable sensor data.

Approach

Directed the design and build, covering QC code, validation, data lineage, and metrics, with master QC requirements co-developed with data science.

Outcome

Formally handed over for testing; designed for reuse and structured for inspection readiness.

Deployed in Kenya

Child Case Management Mobile AppKupenda for the Children · 2020–2021

mHealthCommCareSASLive

Live

WAAI Website & Content InfrastructureWomen Applying AI (WAAI) · 2026

Web ContentAI CommunityManagementLive

How I work

Design for reuse from the start

Document for the auditor

Work across the aisle

Know the tooling, know its limits