Analytical infrastructure and methodological support for healthcare institutions, academic laboratories, and emerging biotechnology companies.
Sample size and power calculations across comparative trials, diagnostic accuracy studies, and reliability studies — ensuring adequately powered research before data collection begins.
Request this serviceKaplan–Meier estimation and Cox proportional hazards regression for time-to-event outcomes including relapse, recovery, treatment failure, and mortality, with clinical interpretation.
Request this serviceMixed effects models, GEE, and time series approaches for longitudinal and repeated measurement data — understanding how outcomes change within subjects over time.
Request this serviceSensitivity, specificity, predictive values, likelihood ratios, and ROC analysis for test validation and clinical decision-making support, including DeLong method AUC comparisons.
Request this serviceICC, Bland–Altman, and Cohen's κ for measurement reliability and inter-rater or inter-method agreement — validating instruments and diagnostic procedures before larger studies.
Request this serviceHypothesis testing, linear and logistic regression, ANOVA, and multivariable modelling — defensible conclusions with appropriate handling of confounders and model assumptions.
Request this serviceEvidence synthesis across multiple studies using fixed and random effects models, heterogeneity assessment, funnel plots, and GRADE evidence profiling for journal submission.
Request this serviceStructure-based computational methods to evaluate candidate compound–target protein interactions. Practical early-stage lead prioritisation before committing resources to wet lab experimentation.
Request this serviceWhole-genome sequencing analysis for resistance gene identification, outbreak cluster tracking, and stewardship programme support — translating genomic data into actionable clinical insights.
Request this serviceIn vitro screening programme design — assay format selection, control organisms, MIC data interpretation, and compound prioritisation. Informed by hands-on antimicrobial drug discovery research experience.
Request this serviceExperimental design for target identification, resistance selection, transcriptomic analysis, differential gene expression under drug pressure, and Tn-seq analysis to map essential genes and fitness determinants at genome scale.
Request this serviceInteractive calculators for study design and compound characterisation
General Solubility Equation (Yalkowsky & Valvani): logS = 0.5 − 0.01(MP−25) − logP. Estimates for aqueous solubility at 25°C.
Lipinski Rule of Five. Estimates from SMILES atom counts. For precise values use RDKit or ChemDraw.
Biostat & BioDiscovery LLC is a consultancy working at the intersection of biostatistics, antimicrobial science, and molecular discovery. Our work is informed by peer-reviewed contributions to antibiotic drug discovery and resistance genomics, with particular strength in study design, sample size planning, survival analysis, and repeated measures modelling.
We support healthcare institutions, academic laboratories, and biotechnology groups with focused, methodologically sound analytical services — from statistical consulting to computational drug discovery and antimicrobial resistance database development.
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