Clinical Data Automation

Stop manually reconciling clinical data

I build automation tools that eliminate the tedious, error-prone column mapping and data reconciliation work that bogs down clinical research teams.

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The Problem

Clinical data workflows are stuck in 2005

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Manual Column Mapping

Teams spend hours matching fields between REDCap exports, EDC systems, and sponsor templates — different every single time.

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Form Building Friction

Building REDCap forms from protocol documents is slow, repetitive, and the #1 complaint from clinical data managers.

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The "Swivel Chair" Problem

Copying data between EHRs and research databases by hand. Error-prone, tedious, and completely automatable.

The Approach

Pragmatic automation that works today

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Smart Column Matching

Fuzzy matching algorithms that auto-map between data dictionaries, sponsor templates, and EDC exports — handling the variations that make reconciliation painful.

2

Document Parsing

Extract structured data from pathology PDFs, lab reports, and clinical documents using AI — no FHIR integration required.

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Works With Your Stack

Built for REDCap, Rave, Veeva, and TrialKit workflows. Not a rip-and-replace — a layer that automates the manual steps you already do.

About

Built by someone who understands regulated data

I'm Marius Pasca — a senior data systems engineer with 17 years of experience in banking, trading platforms, and regulated industries. Now applying that expertise to the one domain where manual data work still dominates: clinical research.

17
Years in regulated data systems
.NET
Core engineering background
Boston
Based in the biotech capital
EU + US
Cross-Atlantic perspective

Let's talk about your data pain

If your team spends hours on manual data reconciliation, column mapping, or form building — I'd like to hear about it. 20-minute conversation, no pitch.