Biological systems & data infrastructure
I'm Oleksandr Petrenko, physician-scientist and computational biologist.
I help biotech, pharma, and academic teams sharpen their R&D decisions by:
- 01Computational systems biology expertise, on demand.
Designing assays and studies, analysing data, and delivering decision-ready outputs. - 02Building data & AI architecture your team needs.
Designing secure research infrastructure and deploying biomedical AI workflows for sensitive data.
Data infrastructure outgrown
Studies stuck
No off-the-shelf tool fits
I trained as a medical doctor and then became a computational systems biologist through research. This dual background benefits your scientific teams: I can read the underlying biology and pathology accurately, help frame the right question, and then engineer the system (or run the analysis) that answers it.
I work directly with clients - flexible, open for urgent requests.
Based in Vienna. Working hybrid across the EU, open for consideration elsewhere.
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Medical & scientific background
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Privacy-first solutions for sensitive data
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Everything is reproducible by default
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You work with me directly
You reach out
During a brief call, we talk about your challenge and whatever is on your mind, and how I see the scope of work.
Discovery & scope
A short results-oriented dive. For example: stakeholder interviews, data audit, written technical specification. For R&D work: question framing, study design, analysis plan, named deliverables.
Execute & hand over
Phased delivery as agreed together, weekly check-ins, specific deliverables at each milestone. At the end: a working system your team runs, or a completed study with figures, code, and a decision memo.
Biotech startup
Custom genomics framework for target discovery
Supported the R&D programme by developing a custom genomics framework for target discovery in difficult-to-target genomic regions, and provided computational analysis of multi-omics data.
Biotech startup
AI agent-driven intelligence digest system
Designed and implemented the on-premises architecture supporting the client's scientific and operational activity, including an AI agent-driven intelligence digest that compiles internal and external developments into decision-ready briefings.
Consortium
Computational work-package lead in an academia-pharma collaboration
As part of one of Europe's leading laboratories on portal hypertension and liver fibrosis, I led the computational working package within an academia-pharma partnership with Boehringer Ingelheim. I worked on an unresolved therapeutic gap together with talented colleagues and mentors, and contributed to publications in the field's top journals.
The biology leads, the tooling follows.
Not a "here are the results, interpret them yourself" approach. I do this out of a genuine love for computational biology, and to use whatever serves your aims best. I work closely with your scientific team to give pathology- and biology-relevant conclusions from the results I deliver.
Your data, your rules.
On your own infrastructure or within your own virtual environment, always. No shadow copies, and no training data leaving your network. When I work remotely, I use encrypted storage, isolated per-project environments, and careful security practices. If a vendor would require otherwise, we pick a different vendor.
Delivered, documented, useful.
Specs, analysis plans, and decision memos are written as the work develops, not retrofitted at the end.
No one-person bottlenecks.
Every engagement ends with someone on your team able to run the system, continue the analysis, or explain the decisions. If I become a single point of failure, I've done the job wrong.
How much do engagements cost?
Discovery is a fixed fee, roughly one to two weeks of an implementation specialist at average EU rates. Full engagements are priced by complexity, time constraints, and the duration of the work. We set this together after discovery.
How soon can you start?
If I'm not tied up with a major commitment, expect to start within one to a few weeks of the first call and CDA signing. Currently booking Q2-Q3 2026.
Do you work solo?
Scientific contracts and discovery are just me. For implementation, when the work calls for it, I can assemble and lead a computational research team from my network of recognised experts.
Do you have an approach to sensitive data?
Yes. Sensitive data stays where it belongs - on your own infrastructure or within your own virtual environment. Non-sensitive workflows run on an EU-hosted, encrypted environment, and remote work goes through encrypted storage, isolated per-project environments, and sound security practices.
What do you work with?
Reproducible, well-documented setups: Nextflow pipelines in containerised environments and versioned code repositories. Within them I work mainly in R, Python, and Julia, whichever best fits the problem.
Do you build AI agent systems?
Yes, including multi-agent orchestration and the tooling around it. I build these human-first - the agents support your team's judgement rather than replace it - with ethical guardrails and the same data-security practices as the rest of my work, run on your own infrastructure where the data is sensitive.
Can we start without a polished project deck / document?
Encouraged. Let's meet each other and discuss your challenge.
Can I call you Sasha?
Undoubtedly. Most people do, myself included!
Let's talk. No polished deck or pitch is required.
We can have a quick, informal call, or you can show me a non-confidential, rough example of what you are working on. Together we'll work out whether I can help, which service pathway fits, and a realistic estimate of the engagement's duration and cost.
Book the intro call