More than two decades inside life sciences R&D. We turn research data into answers you can act on, and into software your teams use every day.
We understand the biology and the data before we analyse anything or write a line of code. Some questions need an answer — which patients differ, which pathway matters, what a time series predicts. Others need a tool that keeps working after we have left. Many need both, and because one team is accountable for both, nothing is lost between the analysis and the software.
AI is a tool in our own work, not something we sell. It means a first result arrives in weeks rather than quarters — and work that could not justify a project can now justify one.
Biomarker discovery, patient stratification, network and pathway inference, prognosis and prediction, computational biology. We work with the data you already hold and deliver the result in the form it will be used: a report that supports a decision, a process your team can repeat, or a software tool.
Every result states how it was reached and how far it can be trusted.
Whether you are building a new system or modernising one that has outgrown how it was written, we deliver production-grade software and data pipelines for life sciences industry R&D — including the software that puts an analysis into daily use. That means tested, documented, and maintainable by people other than the ones who wrote it.
Judgement stays human: every change is reviewed and owned by a named engineer.
We do not carry out formal GxP computerised-system validation, and we do not take on analyses intended to support a regulatory submission. We build and analyse so the work can move into a validated environment later without being redone, and say so early if something starts to need it.
Every engagement combines domain science with data analytics or software engineering. We take one on when that combination is what the work needs.
It concerns biology, disease, compounds or patients, and solving it needs someone who understands them — not only the data or the IT.
A named scientist or owner on your side who can say what a useful result is, and accept it.
An analysis, a process or a system, defined well enough to agree acceptance criteria before work starts.
Someone who reads the question, the data and every result in the terms of your field — from emergentec itself, never passed on.
Done by senior specialists under our own technical standard: nothing reaches you unreviewed, and everything is documented so others can follow it.
A fixed price per work package, written acceptance criteria, and a result you can test. You own it, whoever continues the work.
Framing takes about three weeks and ends in a priced plan. The first result follows at a fixed price set after framing; after that, call-offs you control, not blocks of people you carry. One contract and one liable party throughout.
We have delivered to pharma, diagnostics and life sciences clients under commercial contract, and inside eleven EU and nationally funded programmes — commercial accountability on one side, large-scale collaborative work on the other. Aligning data and systems across many institutions is the same problem a large company has inside its own walls.
With AI the limit moves from what we can produce to what we can be sure of — in an analysis as much as in code. That is what this experience is for.
Founded 2002 and led by Dr. Arno Lukas and Dr. Bernd Mayer. Data analytics and software engineering are our own domains. Your single contracting party, carrying delivery responsibility for every engagement — your contact for scope, commercial terms and acceptance.
Architecture and implementation are led by a senior software architect who owns the technical standard — how the software is structured, tested, reviewed and deployed. Additional EU-resident specialists are contracted where a work package requires them.
emergentec biodevelopment GmbH, Vienna. Tell us what you're working on — we take it from there.