This post originally appeared on Fast Data Science’s blog on LinkedIn.
Clinical research can be better understood through two primary perspectives: the anatomy and physiology of a study. These themes help researchers design and conduct efficient and valid studies.
The anatomy of research encompasses the tangible elements of a study plan. A protocol lays out these elements, serving as a detailed blueprint for the study. The main components of this blueprint include:
Research Question: The core objective or the specific uncertainty the study aims to resolve. It often begins with a broad concern narrowed down to a concrete, researchable issue. For example:
Background and Significance: Conduct a thorough literature review to understand what is already known about the topic. It helps refine the research question and establish the study’s rationale by identifying gaps in existing knowledge.
Design: The study’s structure includes decisions about whether to conduct an intervention or an observational study. Different designs suit different research questions and resources. For example:
Participants: Criteria for selecting study participants and the sampling design.
Variables: Defining predictor variables, confounding variables, and outcome variables, which are the measurements to be made during the study.
Statistical Issues include formulating hypotheses, determining sample size, and deciding on the analytic approach.
The physiology of research focuses on the processes that make the study work and how to ensure these processes yield valid conclusions. The aim is to minimise errors that could compromise the study’s findings and applicability to the larger population.
Design studies to yield reliable results about what happened within the research and how to generalize those results. It involves rigorous data collection, accurate measurement techniques, and appropriate statistical analysis to ensure that conclusions are valid and actionable.
While separating the anatomy and physiology of research helps simplify complex topics, it is essential to understand that these components are interdependent. Just as in the human body, the anatomy of a research study (its structure) and its physiology (how it functions) must work together seamlessly to produce meaningful and reliable results.
Understanding both the anatomy and physiology of clinical research is crucial for designing studies that are efficient, valid, and capable of providing significant insights. By meticulously planning the study’s structure and ensuring the processes are robust, researchers can achieve reliable and applicable findings to broader contexts.
Fast Data Science has created a Clinical Trial Risk Tool that uses AI to help you derive cost and risk estimates from clinical documents. Try the Clinical Trial Risk Tool here: https://mailchi.mp/fastdatascience/clinicaltrialrisktool
Source:
Browner, Warren, S. et al. Designing Clinical Research. Available from: Wolters Kluwer, (5th Edition). Wolters Kluwer Health, 2022.
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Introduction People have asked us often, how was the Clinical Trial Risk Tool trained? Does it just throw documents into ChatGPT? Or conversely, is it just an expert system, where we have painstakingly crafted keyword matching rules to look for important snippets of information in unstructured documents? Most of the tool is built using machine learning techniques. We either hand-annotated training data, or took training data from public sources. How We Trained the Models inside the Clinical Trial Risk Tool The different models inside the Clinical Trial Risk tool have been trained on real data, mostly taken from clinical trial repositories such as clinicaltrials.
Over the years, the overall cost of the drug development process has been exponentially increasing, prompting the adoption and use of adaptive clinical trial design software. Though there are practical difficulties and barriers in implementing clinical trial solutions, these problems are adequately addressed to overcome these issues as they arise. With advancements in software technologies, further improvements are being made to the software’s adaptive clinical trial design. Despite these progresses, just only a handful of well-established software with various types of clinical trial adaptations is currently available.
A clinical trial protocol is a document which serves as the step-by-step playbook for running the trial. The clinical trial protocol guides the study researchers to run the clinical trial effectively within a stipulated period. The prime focus of the clinical trial protocol is to ensure patients’ safety and data security. [1, 2] As the clinical trial protocol is an essential document for the seamless execution of the clinical trial, reviewing (peer-reviewing) the protocol is essential to ensure the scientific validity/viability/quality of the protocol.
