Contribution to another of the Wonderful Wednesdays challenges (13 Nov 24) run by the Visualisation Special Interest Group of Statisticians in the Pharmaceutical Industry.

Current dosing practices are based on average responses from limited clinical trials. However, overlooking variations such as in sex, age, and genetics can lead to adverse events in certain patient groups. Conversely, it is possible that a new drug with benefit in a select sub-group of patients fails to get approval because the pivotal trial showed insufficient efficacy in the general population. These scripts were written for the VIS-SIG Wonderful Wednesdays challenge on 10 Oct 24. Wonderful Wednesdays are a monthly webinar organised by the Visualisation Special Interest Group of Statisticians in the Pharmaceutical Industry (https://psiweb.org/).

I wrote this script for a paper describing a rare disease caused by genetic variants of the CLN6 gene. The script served three purposes: 1. translating the Human Phenotype Ontology (HPO) term IDs of the patient records into HPO term names 2. replacing HPO terms of variable specificity with HPO terms at a defined, more general level 3. generating publication-ready plots of HPO term frequencies. Summarizing HPO terms at the organ system level revealed that the eye was the third most often affected organ in CLN6 disease. This was hidden by the heterogeneity of the original HPO annotations, and had not been noted in previous publications.

T-cells which recognise and kill cells expressing tumour-associated antigens are a promising new anti-cancer agent. However, in a few cases reactivity to antigens expressed by normal tissue caused serious adverse events. To mitigate such risks, Adaptimmune developed an extensive in-vitro testing pipeline. A pivotal element was predicting the repertoire of potential targets in human tissues that the therapeutic T-cells might respond to. The script reproduces two important figures of our paper. It involved checking > 10 million peptide sequences for matches in the human proteome; under 126 different criteria.

One of my favorite kind of plots for comparing data which might not be normally distributed.

The two figures together visualised a key message of our paper: T cells transduced with the AFPc332 T-cell receptor recognised target cells in vitro which expressed alpha fetoprotein (AFP) at levels found in ~30% of liver tumors. Importantly, these levels were outside the range of AFP expression in normal tissues and diseased liver. The results supported the use of AFPc332 T-cells as a safe and effective anti-cancer agent.