Benjamin Keane

Bioinformatician specialising in machine learning

Translating transcriptomic data into clinical solutions such as prognostic biomarkers in cancer.

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Available for consulting, contract work, and academic collaborations.

Bridging Data Science and Drug Discovery

I help pharmaceutical companies and biotech startups accelerate their R&D pipelines by building robust, reproducible, and regulatory-aware machine learning solutions. My work focuses on translating complex biological questions into actionable data strategies, leading to faster insights and de-risked clinical development.

For academic partners, I offer deep expertise in computational biology and statistical modeling, seeking collaborations that push the boundaries of bioinformatics. I am passionate about open science and contributing to high-impact joint publications and grant proposals.

How I Help Pharma & Startups

Translate Clinical Questions into ML Experiments

I bridge the gap between clinical teams and data science, designing experiments that deliver statistically significant and clinically relevant results.

Production-Ready Model Delivery

I develop and deploy validated ML models that integrate seamlessly into your existing data infrastructure, complete with documentation and version control.

Data Pipeline & Governance

I design efficient data pipelines and establish governance frameworks to ensure data quality, integrity, and compliance (e.g., GxP, GDPR).

Regulatory & Validation-Aware Analysis

My approach incorporates regulatory considerations from day one, producing analysis and documentation suitable for internal validation and external review.

Business Services

ML/AI Strategy Consulting

Business Benefit: Align your AI initiatives with core business goals to maximize ROI and competitive advantage.

Biomarker Discovery

Business Benefit: Identify novel predictive and prognostic biomarkers from high-throughput data to stratify patients and accelerate trials.

Custom ML Model Development

Business Benefit: Get tailored predictive models for tasks like target identification or patient outcome prediction, moving beyond off-the-shelf solutions.

Model Validation & Reporting

Business Benefit: Gain confidence in your models with rigorous validation and clear reporting, ready for internal audits and regulatory submissions.

Data Pipeline Automation

Business Benefit: Reduce manual analysis time and increase reproducibility by automating your data ingestion, processing, and analysis workflows.

Contract Data Science / Bioinformatics

Business Benefit: Augment your internal team with specialized expertise on-demand, saving on long-term hiring costs for short-to-medium term projects.

Projects & Case Studies

Predictive Model for Patient Stratification

Problem: A mid-size pharma company needed to identify which patients would respond best to a new oncology drug based on genomic data.

Approach: Developed a random forest model using RNA-seq and clinical data. Implemented rigorous cross-validation and feature importance analysis.

Outcome: Delivered a validated model with 85% predictive accuracy, enabling the design of a more targeted and cost-effective Phase II trial.

PythonScikit-learnPandasNextflow

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Selected Publications

G., Tran, F., ... Keane, B., et al. (2024). A review of machine learning applications in rheumatoid arthritis. Rheumatology Advances in Practice.
Contributed to a comprehensive review of machine learning's role in diagnosing, predicting, and treating rheumatoid arthritis.
View on Journal Website (PMC)

View Full Publication List on ORCID

Get In Touch

Let's Collaborate

I'm currently accepting new projects. Whether you have a well-defined data challenge or need strategic guidance on leveraging your data, I'm here to help.

The best way to start is by booking a complimentary 30-minute consultation to discuss your needs.

Schedule a call: Book on Calendly
Or email me directly: benjaminjameskeane@gmail.com

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