Clinical Development Statistical Strategy
Statistical consulting for clinical development: objectives, endpoints, populations, design options and evidence-generation strategy.
Algoria Biometrics
Biostatistics, clinical programming and scientific software
Find support for developing a scientific application, reviewing clinical programming, or automating analyses and reports. You can also explore study design, biostatistical analysis, data quality and other services for your project.
What you can receive
An analysis plan with explicit decisions and assumptions; datasets and tables with code and QC; or a scientific tool with tests and handover instructions. Deliverables are defined around your question and available materials.
A defined project, part-time support or integration into your team. We agree allocation, responsibilities and review criteria before work begins.
Biostatistics and strategy
Statistical Analysis Plan Development
SAP authorship and updates for clinical studies: endpoints, estimands, populations, methods, sensitivity analyses and output specifications.
Study Design, Sample Size & Power
Statistical study design, sample size and power analysis for biomedical research, with documented scenarios, simulation, sampling and randomisation planning.
Trial Feasibility & Enrolment Scenarios
Data and assumption assessment for trial feasibility: eligibility, populations, follow-up and enrolment scenarios subject to validation.
Applied Statistics for Business: Project Assessment
Feasibility assessment for demand forecasting, segmentation and statistical process control: data requirements, validation and analytical scope for businesses.
Clinical programming
CDISC SDTM & ADaM Dataset Programming
SDTM and ADaM preparation, transformation and review: mapping, derivations, metadata, QC and traceability between source data, SAP and outputs.
SAS & R Statistical Programming and TLF Delivery
Clinical trial tables, listings and figures with production and QC in SAS and R: shells, derivations, safety, efficacy, interim and final reporting.
SAS–R Modernisation & Programming Libraries
Modernise SAS macros and R workflows with reusable functions, TLF templates, QC automation, documentation and equivalence checks.
Data science and scientific software
Clinical Data Platforms & Analytical Integration
Clinical and biomarker data integration with R, Python, SQL and Databricks: data models, pipelines, QC, lineage and analytical applications.
R/Shiny development, recovery and maintenance
Build, recover and maintain R/Shiny applications with source code, tests and handover. Scope and support agreed for each project.
Research Data Preparation & CRF Design
Research database cleaning and coding, data dictionaries and case report form design with traceable validation rules and analysis-ready transformations.
Oversight and technical leadership
Technical review of CRO and vendor deliverables
Technical review of clinical programming deliverables: prioritised findings, acceptance criteria and remediation recommendations.
Interim Analysis & DSMB/DMC Statistical Support
Interim analysis and DSMB/DMC statistical packages: data cuts, TLF programming, QC and traceability under defined access and review rules.
Senior clinical programming oversight
Senior review of specifications, SDTM/ADaM, TLFs and QC evidence, with technical coordination and an agreed time allocation.
Clinical analytics and evidence
Biomedical Statistical Analysis
Reproducible statistical analysis for clinical studies, cohorts and registries, including longitudinal models, survival, missing data and scientific reporting.
Longitudinal, Survival & Sensitivity Analysis
Repeated-measures, mixed-effects and time-to-event analysis for clinical studies: covariates, censoring, missingness and sensitivity.
RWE & Intervention Effect Analysis
Observational, post-marketing, pragmatic and before-after study analysis: adherence, outcomes, covariate adjustment and sensitivity.
Predictive Models & Patient Stratification
Predictive modelling, responder profiling and clinical stratification: regression, classification, clustering, validation, discrimination and calibration.
Clinical Technology & Patient-Reported Outcome Evaluation
Statistical support for clinical technologies, procedures, PROMs and repeated symptoms: design, outcomes, comparison and interpretation.
Vaccines, assays and biomarkers
Vaccine & Immunogenicity Biostatistics
Analysis and reporting for vaccine studies and immunogenicity data: SAPs, clinical/laboratory integration, longitudinal response and QC.
Assay Validation, Stability & Reproducibility Statistics
Statistical support for clinical laboratory assays: variability, reproducibility, stability, validation design and evaluation criteria.
Tailored biomarker and omics analysis
We assess the question, technology, processing stage and specific expertise needed before proposing an analysis. Scope identifies the input data, methods, and who will perform and review the work.
Research, publication and training
Statistical Manuscript Review & Reviewer Responses
Statistical review of biomedical manuscripts, methods, results and tables, with focused support for journal reviewer responses and analysis corrections.
Statistical Consulting for PhD Research
Statistical support for biomedical PhD research: study design, data preparation, reproducible analysis and interpretation with the research team.
Research Proposal Review & R&D Collaboration
Statistical and methodological review of research proposals: objectives, endpoints, sample size, feasibility and analysis plans for biomedical R&D.
Biostatistics & R Training for Biomedical Teams
Tailored biostatistics, R and reproducible analysis training for researchers and biomedical teams, with practical workshops matched to objectives and experience.
Defined-scope projects
For an urgent decision or a bounded review, these engagements provide a focused starting point with defined inputs and deliverables.
Study Rescue Diagnostic
We review agreed materials to identify inconsistencies, prioritise findings and propose a remediation plan. You receive an issue log and outstanding decisions; subsequent corrections are scoped separately.
Submission Readiness Pre-Audit
Find evidence and traceability gaps before CSR, audit, due diligence or submission.
SAP & Estimand Risk Review
Identify statistical, estimand and analysis risks before finalisation or regulatory review.
RWE / Observational Data Fitness Sprint
We assess whether the data and rules for population, dates and follow-up support a specific question. You receive findings, limitations and recommendations; cohort definition and analysis are specified in scope.
Translational, Biomarker & Immunogenicity Analytics
We assess the question, technology, processing stage and specific expertise needed before proposing an analysis. Scope identifies the input data, methods, and who will perform and review the work.
Analysis and reporting automation
For teams that update data and need to regenerate tables, figures or reports consistently. We turn agreed steps into a reproducible workflow, with parameters, checks and a record of each run.
Discuss your project
Tell us about the objective, study stage and deadline. We review the need and availability; we then define the scope with you and prepare a proposal with deliverables, timing and fees.
Do not email patient, clinical or confidential study data. Access and the working environment are agreed before materials are shared.
Discuss your project