Causal Inference for Precision Medicine in Medtech R&D and Clinical Studies (Updated for 2026)
Precision medicine is reshaping the landscape of medtech by tailoring treatments and diagnostics to each patient's unique clinical profile. As innovative devices and diagnostics enter the market, it becomes critical to understand not only whether they work, but how much, and for whom. Causal inference offers a robust statistical framework for distinguishing true treatment effects from associations, a challenge that is particularly pronounced in observational studies and real-world data…
Analytics for Precision Medicine in Medtech R&D and Clinical Trials
Precision medicine is transforming healthcare by allowing treatments and diagnostics to be tailored to the unique genetic, molecular, and clinical profiles of individual patients. As research and clinical evaluation evolves, sophisticated analytics have become essential for integrating complex datasets, optimising study designs, and supporting informed decision-making. This article will explore 3 core quantitative approaches core to supporting the development of precision treatment solutions in Medtech. 1. Bayesian Adaptive Designs…
Why Biostatistics Qualifications Matter in Med-Tech Industry Clinical Trials.
In the medtech industry, a growing misconception equates proficiency in statistical software with competence in clinical trial design. As data pipelines become more automated, statistical analysis is increasingly delegated to professionals from adjacent fields, such as biomedical engineers, bioinformaticians, or data scientists. While these disciplines possess strong computational skills, they often lack the in-depth biostatistical training required to safeguard a clinical trial. The result is a fundamental misalignment between…
P Values, Confidence Intervals and Clinical Trials
P values are so ubiquitous in clinical research that it’s easy to take for granted that they are being understood and interpreted correctly. After all, one might say, they are just simple proportions and it’s not brain surgery. At times, however, it's the simplest of things that are easiest to overlook. In fact, the definitions and interpretations of p values are sufficiently subtle that even a minute pivot from…
Master Protocols for Clinical Trials
Part 1: Basket & Umbrella Trial Designs Introduction As the clinical research landscape becomes ever more complex and interdisciplinary alongside an evolving genomic and biomolecular understanding of disease, the statistical design component that underpins this research must adapt to accommodate this. Accuracy of evidence and the speed with which novel therapeutics are brought to market remain hurdles to be surmounted. Traditionally, efficacy and non-inferiority clinical trials included broad disease…
Simpson’s Paradox: the perils of hidden bias.
How Simpson’s Paradox Confounds Research Findings And Why Knowing Which Groups To Segment By Can Reverse Study Findings By Eliminating Bias. Introduction The misinterpretation of statistics or even the "mis"-analysis of data can occur for a variety of reasons and to a variety of ends. This article will focus on one such phenomenon contributing to the drawing of faulty conclusion from data: Simpson’s Paradox. At times a situation arises where…