Portfolio
At Bayer I deploy AI into regulatory work in life sciences, and I lead the digital transformation that work sits in.
Germany · open to relocation (on-site or hybrid)
About
I work at Bayer in Monheim, as Global Project & Program Lead and Product Owner. The job is regulatory digital transformation in life sciences: getting label and registration data off paper, and putting AI into the workflows the department actually runs. I have been at Bayer since 2018, including Pharma R&D IT in Leverkusen before this role.
For EPA use-summary tables, regulatory managers were spending 100+ hours building the tables by hand from pesticide-label PDFs. The system now in production drafts those tables in a few minutes. Managers only spot-check them, which takes minutes, so the submission gets to market faster. A run costs about $0.50–$0.75 per label. I owned that workflow from the manual process through to the live system. A second system is in production for country registration portfolios. It reads a safety data sheet and drafts the toxicology and ecotoxicology sections, which are most of the work per active ingredient. A reviewer still signs that off. Both ship with the same guardrails: kill switch, cost cap, audit trail.
The scale around it is the label-data platform: 27 countries, more than 100 labels a quarter, a bit over €500k a year, vendor contracts over €250k. I lead the global digital label programme. The mission is to turn static labels into trusted, structured data that people, systems and machines can reuse. AgriGuide is the EU project, live at agriguide.eu with BASF, Syngenta and Corteva. The same programme runs in APAC, North America, ANZ and LATAM. Structured authoring cut label-authoring effort by about 40–50%. Bayer is working toward a digitised EU portfolio by 2028. Separately, I keep a portable AI Pre-Flight checklist — a generic version distilled from shipping agents in regulated work — so the next agent does not reinvent governance from scratch.
Before Bayer I did a PhD in physics at Cologne and Jülich, on nanoparticles and red blood cells. Outside work I teach yoga, meditation and breathwork at Karuṇā Space.
Open to product and programme lead roles in regulatory digital transformation, across life sciences, pharma, medtech and R&D.
Selected impact
In production
across regulatory work
AI extraction is deployed inside Bayer life sciences regulatory work, on the submissions and registration files the department is responsible for.
100+ hrs
no longer spent by hand
Regulatory managers spent 100+ hours building EPA use-summary tables by hand from pesticide-label PDFs. Those tables are now drafted in a few minutes, then spot-checked. About $0.50–$0.75 per label, and the submission gets to market faster.
1,500+
labels on AgriGuide
AgriGuide is the EU project in the global digital label programme I lead. Already published on agriguide.eu, with BASF, Syngenta, Corteva and others. The programme also runs in APAC, North America, ANZ and LATAM. Bayer is working toward a digitised EU portfolio by 2028.
€500k+
a year on the platform
Label data across 27 countries. More than 100 labels a quarter, and vendor contracts over €250k.
Programme and product
The global digital label programme, the label-data platform, and the Pharma programme from the previous role.
Programme·Global
Turns static product labels into trusted, structured data that people, systems and machines can reuse. I lead it across the EU, APAC, North America, ANZ and LATAM.
| Before | Now | |
|---|---|---|
| Programme | No programme | Global: EU, APAC, North America, ANZ, LATAM |
| EU | Separate country builds | 27 countries, 2028 |
| Label in the field | Paper | EU: scan, 1,500+ labels live |
| Authoring effort | Previous practice | About 40–50% less |
Platform·In production · Bayer
Product ownership for the global label-data platform: what gets built, in what order, and with whose budget.
| Before | Now | |
|---|---|---|
| How labels were made | Documents, country by country | One backlog, 100+ labels a quarter |
| Budget | — | About €500k a year |
| Vendors | — | Contracts over €250k |
Programme·Delivered · Bayer Pharma R&D IT
I led PIx Portfolio Tracking (PIx PT), covering every Pharma indication from Phase 0 to Phase 2. I was also one of the business analysts on the PIx platform, and did data analysis for a PIx module.
| Before | Now | |
|---|---|---|
| What shipped | Requests from the labs | PIx Portfolio Tracking, Phase 0 to Phase 2 |
| Analyst work | — | Business analyst on the PIx platform, data analysis for a PIx module |
| Who it served | — | 500–1,000 researchers |
| Money | — | About €1 million, under a steering committee |
Agentic AI
Two agents in regulatory workflows, and the checklist I run before the next one ships.
AI agent·In production at Bayer · used on regulatory submissions
A production AI agent at Bayer. It drafts EPA use-summary tables from pesticide labels. Reviewers spot-check before anything goes out.
| Before | Now | |
|---|---|---|
| EPA tables from pesticide labels | 100+ hours by hand | A few minutes |
| What managers do | Write the tables from the PDFs | Spot check, minutes |
| Cost per label | — | $0.50–$0.75 |
| Submission | Waits on transcription | Faster time to market |
AI agent·In production at Bayer · expert review before scores are used
A production AI agent at Bayer. It reads a safety data sheet and drafts the toxicology sections of country ARS workbooks.
| Before | Now | |
|---|---|---|
| Tox / ecotox | Typed from the safety data sheet | Drafted for review |
| Share of the job | The slow part of every ingredient | About 70% pre-filled |
| Who decides | Expert starts from a blank sheet | Expert checks before scores are used |
AI·Personal working standard · used on Use Summary Table & ARS Automation
A portable checklist for shipping agentic AI — distilled from building and deploying agents in regulated life sciences.
| Before | Now | |
|---|---|---|
| Governance | Reinvented on each agent | One checklist, about 30 items |
| Applied to | — | Use summary and ARS |
| What it forces | A slide | A kill switch, an owner, an audit trail |
Skills
1AI in the department
Systems deployed into life sciences regulatory workflows, so submissions and label data move faster without dropping the human check.
2Digital transformation
The point is the department's cycle time: less transcription across the portfolio, and regulatory information that can be reused instead of retyped.
3Regulated documents
Pesticide labels, country registration files, and the platform those labels sit on. The rules are fussy, and the fussy parts are the job.
4Running the work
Roadmap, backlog, budget, vendors, steering meetings. The unglamorous half, and the half that keeps a tool alive after the demo.
5Safe enough to run
Kill switch, spend cap, audit trail, human sign-off — and a portable AI Pre-Flight checklist I distilled from shipping agents in regulated work (not an official standard; a generic version I reuse on each new agent).
Experience
08/2021 – Present
Bayer AG
Monheim am Rhein, Germany
06/2018 – 07/2021
Bayer AG
Leverkusen, Germany
08/2014 – 05/2018
Forschungszentrum Jülich
Jülich, Germany
PhD in Physics
University of Cologne (2014–2018); dissertation at Forschungszentrum Jülich. International Helmholtz Research Fellowship.
Five-Year Dual BS-MS in Physics
IISER Mohali, India (2009–2014). INSPIRE Scholarship (Government of India).
Nanoparticle-decorated erythrocytes reveal that particle size controls the extent of adsorption, cell shape, and cell deformability
Beyond work
Breathe. Awaken. Belong.
Separate from Bayer. I teach yoga, meditation, breathwork and coaching, and I run the sessions myself. If you want the longer version, it is on karuna-space.com.
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