Technology Tales

Notes drawn from experiences in consumer and enterprise technology

AI & Data Science Jottings

16:11, 17th September 2020

Visual Define-XML Editor

The VDE Dataset Viewer is a multiplatform tool, available on Windows, Linux and macOS, built to help users visualise and explore datasets in several formats, including Dataset-JSON v1.1, NDJSON, compressed Dataset-JSON, XPORT v5 and SAS7BDAT. It supports features such as reading large datasets, filtering with value autocomplete, sorting, row and column navigation, cell selection, metadata information and automatic updates. Users can customise their viewing experience through settings covering numeric date formats, number rounding, dynamic cell height, automatic width estimation and encoding control. The tool also offers API access based on the DataExchange-DatasetJson-API specification and is released under the MIT Licence.

09:15, 17th September 2020

Business Science University provides online education focused on applying data science and machine learning in business contexts through virtual workshops that guide learners through problem-solving processes, from data analysis to deploying interactive applications. The programme targets data analysts, consultants and students, offering courses that cover real-world applications in areas such as customer analytics, financial modelling and text processing, with an emphasis on systematic project workflows and advanced techniques like automated machine learning. Learners gain practical skills through end-to-end projects, develop web-based tools for organisational use and build portfolios on GitHub, supported by a lifetime access model and certification upon course completion. The curriculum is structured into tracks that progressively build expertise, though the university clarifies it does not offer accredited degrees.

17:41, 29th January 2020

Smart Submission Dataset Viewer

The Smart Submission Dataset Viewer is an open-source application designed to inspect and analyse CDISC SDTM, SEND and ADaM submission files formatted in the modern CDISC Dataset-JSON 1.1 standard. It leverages contemporary technologies such as RESTful web services and CDISC CORE for validation, offering advanced capabilities beyond traditional tools used by regulatory authorities, which often rely on outdated formats like XPT. The tool is particularly beneficial for regulatory reviewers, pharmaceutical sponsors, contract research organisations and technology providers involved in CDISC electronic submissions, and it is among the first open-source implementations of the CDISC Library API.

22:02, 23rd October 2019

What is eCOA, and How Does it Improve Clinical Trial Data Quality?

Electronic Clinical Outcome Assessments (eCOA) have emerged as a transformative tool in clinical trials, leveraging electronic devices such as smartphones and tablets to collect patient-reported outcomes (PROs) and other critical data more efficiently and accurately than traditional paper-based methods. By enabling real-time data monitoring, reducing errors and improving patient compliance, eCOA enhances the reliability of trial results and supports timely interventions. It is particularly valuable in scenarios requiring precise data collection, such as monitoring suicidal ideation, managing complex assessments, or conducting large-scale studies, and offers benefits like cost savings and seamless integration with other medical technologies.

The technology encompasses various forms, including patient-reported (ePRO), clinician-reported (eClinRO), observer-reported (eObsRO) and performance-based (ePerfO) outcomes, each tailored to specific trial needs. Choosing an eCOA solution involves evaluating a provider’s scientific expertise, operational experience and technological capabilities to ensure alignment with the trial’s objectives and regulatory requirements. As clinical research evolves, eCOA continues to play a pivotal role in advancing data quality and streamlining processes across the pharmaceutical industry.

15:08, 1st October 2019

What is a geometric mean?

The geometric mean is a statistical measure used to calculate the average of a set of positive numbers by taking the nth root of their product, often applied in contexts involving growth rates, financial returns, or multiplicative processes. It is particularly useful when dealing with percentages or ratios, as it accounts for compounding effects, such as in calculating average annual growth rates for investments or populations. Unlike the arithmetic mean, the geometric mean is derived from the logarithmic transformation of data, making it more appropriate for datasets spanning multiple orders of magnitude or where extreme values could distort results. It also has a physical interpretation in terms of volume, representing the side length of an n-dimensional cube with the same volume as a rectangular solid defined by the original numbers. In statistics, the geometric mean is closely related to the log normal distribution, which models phenomena involving the accumulation of small proportional changes and is often preferred over the arithmetic mean in such cases due to its ability to handle skewed data more effectively.

19:21, 24th October 2017

Nature Reviews Drug Discovery

Published monthly, Nature Reviews Drug Discovery serves professionals across the drug discovery and development field, offering high-quality reviews, perspectives, news stories and summaries of key research alongside updates on new drug approvals, patent law and emerging industry trends. The journal covers a broad range of subjects, spanning target discovery and validation, high-throughput screening, medicinal chemistry, pharmacology, toxicology, drug delivery, biopharmaceuticals, biotechnology, vaccines, clinical trials, drug regulation and pharmacoeconomics, among others.

23:26, 22nd October 2017

Institute of Clinical Research

For over 40 years, the Institute of Clinical Research has served the clinical research community by providing training, networking opportunities and professional support. It works to define and refine standards within the profession, facilitate discussion of key issues affecting clinical research, and foster positive relationships with other healthcare-related groups. The Institute offers a broad range of training delivered by industry experts, hosts forums and special interest groups and provides members with access to a wider professional community and ongoing resources relevant to the clinical research field.

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