Biostatistics & Clinical Trial Methodology · Copenhagen
Frameshift is a biostatistics consultancy supporting biotech sponsors, CROs, and academic research groups. We deliver statistical analysis plans, clinical study reports, and publication-ready outputs, from protocol to manuscript.
Who we are
We are methodologists. Study design, analysis plans, and interpretation follow from the statistics, not the other way around.
Statistical epidemiologist with a PhD from the University of Copenhagen. He trained in statistical genetics at deCODE genetics and held research posts at Statens Serum Institut and the Danish Cancer Institute before co-founding Frameshift. He has led the statistical work on randomized clinical trials, nationwide Danish registry studies, and genetic epidemiology, including research published in NEJM Evidence, the British Journal of Cancer, and The Lancet Obstetrics, Gynaecology & Women's Health. At Frameshift he leads study design, analysis strategy, statistical programming, and reporting.
Statistical geneticist with a PhD in immunology and infectious diseases from the University of Copenhagen. He spent nearly a decade at deCODE genetics working on large-scale human genetics, with further experience in cancer epidemiology at the Danish Cancer Institute, spanning gene discovery, population cohorts, and registry-based research. At Frameshift he leads the practice and works on study design, genetic and observational analyses, and turning complex biomedical questions into tractable statistical ones.
Machine learning and computational analysis for clinical and health research, built on a background in software engineering and data science. His published work spans machine-learning models for clinical risk prediction and the assembly of research-ready health-data infrastructure from real-world records. At Frameshift he leads computational and machine-learning work, bringing model development and validation to problems where standard statistical methods fall short.
We work with teams that have data and broad objectives, and want to shape clear analytical paths. That often means clarifying what can credibly be supported and which analyses are worth pursuing.
Clear, decision-ready SAPs, trial analyses, and reporting. Estimands, endpoints, analysis populations, and strategy are defined at the planning stage—not renegotiated mid-analysis.
Design and execution of observational studies using health registers and other real-world data. Credible results rely on attention to bias, timing, and comparability.
Track record
Peer-reviewed research from our team, and client engagements where we led the statistics.
Randomised trial across 255 patients testing fish skin grafts against standard care for deep diabetic foot ulcers. Fish skin achieved wound closure in 44% versus 26% at 16 weeks.
View Article →Nationwide decomposition separating demographic change from treatment progress in years of life lost to cancer across Denmark.
View Article →Genome-wide analysis identifying a protective ALOX15 loss-of-function variant, implicating the pathway in nasal polyps and chronic rhinosinusitis.
View Article →Nationwide Danish cohort and genetic risk score study finding shared aetiological pathways between migraine and pre-eclampsia, with implications for cardiovascular risk stratification.
View Article →Machine-learning models that sharpen risk stratification and predict treatment failure in diffuse large B-cell lymphoma from routine clinical data.
View Article →Double-blind randomised trial comparing intact fish skin grafts with human amnion/chorion allografts for healing of acute full-thickness wounds.
View Article →Sequence-variant analysis identifying common and rare genetic determinants of serum creatine kinase and lactate dehydrogenase.
View Article →What we deliver
Deliverables for biotech teams and research groups, across the full analytical lifecycle.
Pre-specified SAPs for clinical trials and observational studies, including endpoint definitions, multiplicity strategies, and regulatory-ready documentation.
Primary, secondary, and exploratory analyses for Phase I–IV trials. Clinical study reports and tables, listings, figures (TLFs).
Study design, cohort definition, and analysis using Danish national registers and Nordic administrative data at population scale.
Comparative effectiveness, treatment utilisation, and health outcomes studies using claims, registry, or EHR data.
Publication-quality figures, statistical methods sections, results interpretation, and manuscript support for peer-reviewed journals.
Ongoing senior biostatistical support integrated into your team, from early-phase scoping through final deliverables.
Frameshift Insights
Methodological essays on epidemiology, biostatistics, and study design.
A new Danish nationwide register study followed 1.5 million children and found no association between prenatal acetaminophen exposure and autism, even in a sibling-matched analysis. A look at what the study shows, what the registers made possible, and why the evidence has only converged further.
The Guardian reported that CRC is now the #1 cancer killer in Americans under 50. We pooled 44 years of NORDCAN data across five countries. The trend is real, but the ranking is not: CRC is #3 in the Nordics for both sexes, and the rise is hitting young men hardest.
A 2013 Danish register study found that skin cancer patients had half the all-cause mortality of the general population, an effect that survives even a lottery prize with no biological mechanism whatsoever. Here is why.
Get in touch
We work best with teams that have a defined research question and need statistical methodology, analysis, or reporting support. Tell us about your project and we will typically respond within one business day.
