Himanshu Manchanda
Machine Learning Senior Scientist Bayer
Seminars
Thursday 3rd December 2026
Insight Exchange – How Can AI & Computational Models Improve Confidence Before the Clinic?
9:10 am
- Which data sources provide the greatest opportunity to improve prediction of patient outcomes: pathology, imaging, clinical, biomarker, or multi-omic data?
- How can digital pathology, digital twins, and computational approaches be integrated with traditional tumour models to strengthen translational confidence?
- What evidence is needed before organisations can trust AI-generated insights to influence development and progression decisions?
- Audience Q&As
Thursday 3rd December 2026
Evidence – Leveraging Digital Twins & In Silico Clinical Trials to Improve Predictive Modelling and Translational Success
8:20 am
- Applying digital twin approaches to simulate patient outcomes and support development decisions before clinical testing
- Integrating clinical, biological, and computational datasets to improve prediction of efficacy, safety, and patient variability
- Understanding how in silico models can complement traditional preclinical approaches to reduce uncertainty and strengthen translational confidence
