HEALTHCARE × LIFE SCIENCE × GENERATIVE AI

Working AI
for healthcare and
life sciences.

Drawing on clinical and data analysis experience, we build generative AI into healthcare and pharma work — from development through to training.

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Medicare Part D × Text-to-SQL — Built with Claude Code

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WORKS

We show what we can do through what we have built. Everything here runs on public data, and the code is on GitHub.

Medicare Part D × Text-to-SQL

2026 / PUBLIC DATA / 80.7M ROWS / JA & EN

An app for exploring 80.7 million rows of US prescription data in plain language, without writing SQL. Ask a question and Claude writes and runs the SQL on BigQuery, then returns maps, charts and an interpretation.

ClaudeBigQueryCloud RunPython

Read the series GitHub

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PROJECTS

We take on projects that put data and generative AI to work, mainly in healthcare and life sciences.

PHARMAPharmaceutical
Data & analytics

Embedded in the team from analysis to generative AI, continuously building several apps. Replaced a purchased external service with in-house tools, and moved repetitive aggregation and first-draft documents onto generative AI.

DevelopmentEmbedded support

GOVERNANCEPharmaceutical
RWD governance

Joined the build-out of a foundation for sharing and using real-world data across the organization. Beyond selecting and configuring the tooling, designed the operating rules and ownership model — who maintains what — and stayed through to the point where teams actually use it.

FoundationsEmbedded support

ACADEMIAAcademic research
Large-scale data

Ran the analysis for a study combining a large commercial health dataset with DPC claims data, turning the researchers’ “this kind of patient” into variable definitions across two datasets with different granularity and coding. The work carried through to an accepted paper.

Foundations

DATA VENDORHealthcare data vendor
Offer design

Clarified what pharma buyers want, from time on the buying side and fresh interviews. Rebuilt the offering, the proposal structure and the PoC format — and it led to a signed deal.

Embedded support

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WHAT WE DO

Analysis tools and business apps

We build the screens people use to work with medical data, from sorting out requirements to implementation. Not a one-off analysis report, but something the team touches every day.

We start from how it will be used — for example, switching the same result between a map, a bar chart and a table.

Treatment pattern visualizationCo-occurrence analysisExploratory dashboardsAutomated reports

Automated visualization and reporting

We replace the aggregation, charting and slide-making that medical affairs and commercial teams repeat every month with a system that has generative AI built in. People only check whether the numbers hold up and how to read them.

From PoC design through to running it in production. Built around guardrails and human-in-the-loop, so output never flows through unchecked.

Automated recurring reportsAutomated dashboard refreshCollecting and triaging papers and trialsGuardrail designHuman-in-the-loop

Training and teaching

Hands-on training on real data — for pharma data teams through to hospital management and operations staff.

We have taught in programs delivered with training companies and in a university course for medical data scientists.

Exercises on your own dataOne day or a multi-session courseOn-site / onlinePartnering with training companies

PROGRAM — TRACK RECORD

Claude Code

Build your own medical data appPublic data, from requirements to implementation and release · hands-on

Problem framing

Scoping the problem before any data workWith a training company · for a major real-estate group · hybrid

GenAI × operations

Turn your team’s repetitive work into a systemFor practitioners at pharma companies and hospitals · hands-on

SQL / Python

Data preparation for machine learning and statisticsFor analysts · hands-on

CLIENTS

The people who most often come to us are in roles like these.

PHARMA / MEDTECH

Pharma &
medtech companies

Data & analytics, medical affairs, commercial and digital transformation teams

TYPICAL ASKS

Monthly reports take days to put together
We want to use RWD but lack hands in-house
Our generative AI PoCs never reach production

DATA VENDOR

Healthcare data
companies

Data vendors and health-IT companies looking to take their products to pharma

TYPICAL ASKS

We need to reframe our pitch in pharma’s language
We need a demo or test environment, fast
We need someone who understands medical data

HOSPITAL

Hospitals

Planning, medical billing and nursing management teams building in-house analytics or adopting generative AI

TYPICAL ASKS

We want to use DPC claims data for management decisions
We want to grow people who can analyze data in-house
We want to stop tallying by hand

05 WHY

The field. The data.
The build.

HerzLeben draws on four settings: data analysis inside a pharmaceutical company, digital transformation for life-science clients at a consulting firm, product rollout at a medical device manufacturer, and clinical practice. From there, we build generative AI into the day-to-day work of healthcare and life sciences.

Depending on scale and domain, we team up with outside specialists — so one point of contact can carry a project from requirements through implementation to adoption.