The discussion of the various plots includes advantages of double coding, intelligent sorting, choosing time intervals, selecting suitable colour gradients and the level order. The latter one is important for streamgraphs, stacked bar charts and Sankey diagrams. The next challenge is to improve a plot on serum K reduction in hyperkalemia patients. See the Wonderful Wednesday homepage for more detail.

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Steve Mallett, Rhys Warham, Mark Baillie, Paolo Eusebi, Martin Brown, Benjamin Lang, Lovemore 

Overview

The speakers cover an introduction to oncology dose finding, discussing the FDA’s Project Optimus, model assisted methods, including BOIN, alongside the escalation package in R which provides a range of dose finding tools, including simulations and head-to-head comparison of methods. Recent dose optimisation approaches are discussed, including a dose comparison paradigm using U-MET (utility-based dose optimization approach for multiple-dose randomized trial designs) and U-DESPE (a Bayesian utility-based approach based on Dose-Exposure, Safety, Pharmacodynamics and Efficacy).

Speakers

Ayon Mukherjee; Michael Sweeting; Gina D'Angelo; Anaïs Andrillon; Pavel Mozgunov (Chair)

Animation of plots over time is a very intuitive way to show development of the results over the course of the study. Lasagna plots allow seeing individual patient data, but then right sorting is crucial. Sankey diagrams make it easy to compare proportions over time. This can also be achieved with stacked area charts with careful interpretation of the intermediate stages. The next challenge is on dose tapering. See the Wonderful Wednesday homepage for more detail.

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Steve Mallett, Rhys Warham, Mark Baillie, Paolo Eusebi, Martin Brown, Benjamin Lang, Lovemore Gakava, Aditeya Pandey

Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modelling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.

Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.

Very common displays for benefit-risk are forest plots on effect sizes. Those improve by adding information about rates or proportions and totals. The comparison of multiple treatments is easy with trade-off plots. A basic overview of benefits and risk is nicely show with a value tree. The next challenge is on Markov traces. See the Wonderful Wednesday homepage for more detail.

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Steve Mallett, Rhys Warham, Mark Baillie, Paolo Eusebi, Martin Brown, Benjamin Lang, Lovemore 

Hosted by Emma Crawford, Katie Gwinnell, Alistair Haston, Tabitha Lennox, Oswald Dallimore, Sarah Crossley

Get an insight into how maths is used to help develop experiments to test lifesaving medicines. This webinar showcases the different roles and pathways into the industry and we hear from a panel of professionals who share their experiences and answer your questions!

It is a real challenge to display adverse event data. There are a lot of different aspects to concentrate on. How this can be approached is presented by Bodo Kirsch. Visualisations are available on the Wonderful Wednesday blog. 
The time course of adverse events can be shown with violin plots. To explore the co-occurrence of events a visually enhanced correlation matrix is helpful. Various ways are presented to effectively combine (stacked) bar charts with induvial patient data display and violin plots to explore subgroup differences. The next challenge is on benefit-risk profiles. See the Wonderful Wednesday homepage for more detail.

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Steve Mallett, Rhys Warham, Mark Baillie, Paolo Eusebi, Martin Brown, Benjamin Lang

What is the best visualisation? That depends heavily on the purpose. For exploration interactive and animated plot are presented that enhance the understanding of the data. For explanation a static plot is best if it delivers the message on the first glance. The next challenge is on adverse event hierarchy. See the Wonderful Wednesday homepage for more detail.

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Steve Mallett, Rhys Warham, Mark Baillie, Paolo Eusebi, Martin Brown, Benjamin Lang

Papers for discussion:

Andrew Grieve: Probability of success and group sequential designs - https://onlinelibrary.wiley.com/doi/10.1002/pst.2346

Zhiwei Zhang, Carrie Nielson, Ching-Yi Chuo & Zhishen Ye: Information-based group sequential design for post-market safety monitoring of medical products using real world data - https://onlinelibrary.wiley.com/doi/10.1002/pst.2385

First some plots are shown to explore the data. Showing the individual data helps to avoid misinterpretations. For the actual comparison of the measurements the Bland-Altman plots are suited best. Further data exploration is supported by adding interactive highlighting to this and other plots. The next challenge is to find the best healthcare related visualisation of 2024. See the Wonderful Wednesday homepage for more detail.

Wonderful Wednesdays are brought to you by the Visualisation SIG. The Wonderful Wednesday team includes: Bodo Kirsch, Zachary Skrivanek, Lorenz Uhlmann, Steve Mallett, Rhys Warham, Mark Baillie, Paolo Eusebi, Martin Brown, Benjamin Lang

Emma May, Holly Prescott, Marius Sieverding, Alun Bedding, Steve Mallett

The 7 Habits of Highly Effective People has had a profound impact on millions of people around the world.  The book focuses on cultivating character and refining personality. Its principles are not only transformative for personal growth but also serve as powerful tools for professional development.  Over the past few months, the PSI Book Club has been deeply engaged in exploring these transformative principles. Through small group discussions, members have examined real-world applications, shared personal insights, and unpacked the key lessons embedded in these habits.  In this session, we’ll bring those rich discussions to the forefront. Our focus will be on how these principles can be effectively applied in the professional realm, driving leadership, teamwork, and personal growth. We are excited to welcome two esteemed guests: Alun Bedding, [Executive Coach and Consultant, former Global Head of Statistical Methods Collaboration and Outreach at Roche], and Steve Malett, [Senior Manager Statistics at Veramed]. Both Alun and Steve bring extensive industry experience and have served as facilitators for “The 7 Habits” discussions within the PSI Book Club.  Join us for an insightful conversation on why these habits remain relevant today, how they’ve impacted members of our book club, and how you can apply them in your own life. This is also an excellent opportunity to engage with our panel experts, ask questions, and gain practical advice for your personal and professional journey.

Lea Vaas

The replacement of concurrent control animals by so-called Virtual Control Groups (VCGs) may reduce the use of animals in systemic toxicity studies and contributes to the 3R's principle of animal experimentation. However, the idea of replacing living beings with virtual data from historical data sets has so far not been introduced into the design of regulatory animal studies. Major steps facilitating review of methodology for derivation of ViCoGs from historical control data and performance testing in statistical analysis, are the collection, curation and sharing of suitable sets of historical control data from preclinical toxicity studies. This talk will summarize accomplished and ongoing efforts for cross-industry provision of data resources, standardization and curation activities and line out both general ideas and specific methodology for derivation of ViCoGs. Moreover, a discussion of advantages, pitfalls, real-world examples, potential solutions is given and ideas for transferring these insights into regulations and guidelines are presented.