Quality first, applied where it’s needed.
The core is pharmaceutical quality management. The other three are what a quality leader runs into anyway. In all four the job is the same: find the real cause, make it right, and make it last.
Quality systems and GMP
You need a quality system that an inspector, a customer or a buyer will trust, and that your own people can actually run on a Tuesday.
What I do
- Gap assessments of an existing QMS, ranked by real risk, not by page count
- Building a QMS from scratch, sized for the company you are
- Deviations, OOS, CAPA, complaints and change control that get to root cause
- Supplier qualification and risk-based audit programs
- FDA inspection readiness and hosting
- 483 and warning letter remediation: the response, and the fixes that make the response true
- Technical transfer, stability programs and analytical method development
- Interim quality leadership while you hire, and training the person who takes over
Connecting systems
The ERP says one thing, the spreadsheet says another, and someone re-keys it more times a week than anyone has counted. When systems don’t talk to each other, people become the integration layer, and people make transcription errors.
What I do
- Map where your quality data actually lives and how it moves (or doesn’t)
- Integrations and data migrations between ERP, LIMS, eQMS and the spreadsheets in between
- eQMS governance that doesn’t depend on one administrator never taking a vacation
- Validated tools and spreadsheets, scaled to risk (GAMP 5, 21 CFR Part 11, data integrity)
Documents and standards
Most SOPs are written for the auditor. The good ones are written for the person doing the work, and they hold up for the auditor too.
What I do
- SOPs and work instructions that match how the work is really done
- Job aids for the moment of the task, designed for people who read differently
- Templates and styles that do the formatting, so people can do the thinking
- Harmonizing standards across sites, companies or acquisitions
- Plain-language summaries of regulatory changes for leadership
Responsible AI adoption
Your people are probably already pasting work into AI tools. The question is whether that happens with rules, review and data controls, or without them.
What I do
- An AI use policy or SOP built on the GMP principle that matters most here: a qualified person reviews and owns the output
- Picking the uses where AI helps, and the ones where it shouldn’t touch the record
- Data controls: what stays out of prompts, and how your tenant is set up
- Verification proportional to risk, the same way you’d approach any computerized system
- Custom training, on-site or remote, built from your own documents, systems and work instead of generic demos
How it usually goes
- A free first conversation. What’s happening, what you’d like to be true, and whether I’m the right person. If I’m not, I’ll say so.
- A scoped look. Usually a short assessment, so we both know what we’re fixing before anyone commits to a big number.
- The work. Sleeves rolled up: on the floor, in the lab, at the label printer, not just in the conference room. On-site, remote, or both. Billed for the hours actually worked. If you need 10 hours once, fine. If you need me full-time for months, that works too. Either way, never more than 40 billed hours in a week, even when the week runs longer.
- The handoff. Your people run it without me. That’s the goal, not a side effect.