Causal Inference for Precision Medicine in Medtech R&D and Clinical Studies

Precision medicine is reshaping the landscape of medtech by tailoring treatments and diagnostics to each patient’s unique genetic, molecular, and clinical profile. As innovative devices and diagnostics enter the market, it becomes critical to understand not only whether they work, but why they work. Causal inference offers a robust statistical framework for distinguishing true treatment effects from mere associations, a…
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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…
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CRF Design for Clinical Studies: The Distinct Roles of Data Managers vs Biostatisticians In medtech clinical trials, the Case Report Form (CRF) is more than a tool for collecting data—it’s the backbone of the study. From capturing critical safety outcomes to evaluating device performance, a well-designed CRF ensures that the study’s goals are met efficiently and reliably. Achieving this balance…
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Expert Opinion: Why Biostatistics Qualifications Matter in Med-Tech Industry Clinical Trials.

Consider the consequences if a medical doctor, without a formal medical education or licensing, were to diagnose and treat patients. Such a doctor might misunderstand symptoms, choose the wrong treatments, or even harm patients due to lack of understanding and experience. Similarly, an unqualified biostatistician might incorrectly analyse data, misinterpret statistical significance, or fail to recognise biases and patterns essential…
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Biometrics & Clinical Trials Success:

Why Outsourcing a Biostatistics Team is Pivotal to the Success of your Clinical Trial Clinical trials are among the most critical phases in bringing a medical device or pharmaceutical product to market, and ensuring the accuracy and integrity of the data generated is essential for success. While some companies may feel confident relying on their internal teams, especially if they…
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The Role of Clinical-Translational Studies in Validation of Diagnostic Devices

Clinical-translational studies refer to research studies that bridge the gap between early-stage diagnostic development and real-world clinical application. In a diagnostics context these studies focus on translating promising diagnostic technologies from laboratory research (preclinical stage) to clinical practice, where they can be validated, assessed for clinical utility, and eventually integrated into routine healthcare settings. The primary goal of clinical-translational studies…
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Stata: Statistical Software for Regulatory Compliance in Clinical Trials

Stata is widely used in various research domains such as economics, biosciences, health and social sciences, including clinical trials. It has been utilised for decades in studies published in reputable scientific journals. While SAS has a longer history of being explicitly referenced by regulatory agencies such as the FDA, Stata can still meet regulatory compliance requirements in clinical trials. StataCorp…
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The Devil’s Advocate: Stata for Clinical Study Design, Data Processing, & Statistical Analysis of Clinical Trials.

Stata is a powerful statistical analysis software that offers some advantages for clinical trial and medtech use cases compared to the more widely used SAS software. Stata provides an intuitive and user-friendly interface that facilitates efficient data management, data processing and statistical analysis. Its agile and concise syntax allows for reproducible and transparent analyses, enhancing the overall research process with…
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The role of Biostatisticians, Bioinformaticians & other Data Experts in Clinical Research

As a medical researcher or a small enterprise in the life sciences industry, you are likely to encounter many experts using statistical and computational techniques to study biological, clinical and other health data. These experts can come from a variety of fields such as biostatistics, bioinformatics, biometrics, clinical data science and epidemiology. Although these fields do overlap in certain ways…
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