From clinical research to digital twins: How personalised computational modelling can add value in clinical care

Robyn Walker May^1,2, Tom Gentles³, Frank Bloomfield², Finbar Argus¹, Gonzalo Maso Talou¹, Soroush Safaei¹

¹Auckland Bioengineering Institute, University of Auckland, New Zealand; ²Liggins Institute, University of Auckland, Auckland, New Zealand; ³Starship Hospital, Te Toka Tumai Auckland, Auckland, New Zealand

A demonstrator of the EDITH virtual human twin platform

Marian Bubak, Marek Kasztelnik, Maciej Malawski, Jan Meizner, Piotr Nowakowski, Piotr Połeć

ACC Cyfronet AGH and Sano Centre for Computational Medicine, Krakow, Poland, Poland

12 Labours DigitalTWINS platform: Enabling development and clinical translation of virtual human twins

Thiranja P Babarenda Gamage¹, Chinchien Lin¹, Linkun Gao¹, Jiali Xu¹, Ayah Elsayed^1,2, Alan Wu¹, Mathilde Verlyck¹, Gregory Sands¹, Koray Atalag³, Martyn P Nash^1,4, Peter J Hunter¹, David P Nickerson¹

¹Auckland Bioengineering Institute, University of Auckland, New Zealand; ²Auckland University of Technology, New Zealand; ³GALATA-Digital; ⁴Department of Engineering Science and Biomedical Engineering, University of Auckland, New Zealand

AI-CARE: Digital twin for cancer research

Daniele Tartarini^1,2, Jacob M. Cummins^1,2

¹Department of Computer Science, University of Sheffield, United Kingdom; ²Insigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, United Kingdom

OSS-DBS v2.0: Adaptive meshing for deep brain stimulation modeling

Jan Philipp Payonk¹, Konstantin Butenko², Ursula van Rienen^1,3,4, Julius Zimmermann^1,5

¹Institute of General Electrical Engineering, University of Rostock, Germany; ²Department of Neurology Brigham & Women's Hospital, Harvard Medical School, USA; ³Department Life, Light & Matter, University of Rostock, Germany; ⁴Department of Ageing of Individuals and Society, University of Rostock, Germany; ⁵Now with: Synthetic Physiology Lab, University of Pavia, Italy