Paul Schwerd-Kleine

Data Science Innovation Fellow at Novartis, Cambridge, MA.

PhD in computational biology & cancer multi-omics (German Cancer Research Centre, Heidelberg).

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Portrait of Paul Schwerd-Kleine
Novartis

About me

I’m enthusiastic about applying mathematical modelling and AI to improve patients’ lives, with a focus on oncology.

My work spans model development, outcome prediction, multi-omics, single-cell & spatial transcriptomics, all aiming at translation into actionable insights.

Paul in profile

Selected projects

Cell2trial visual

Cell2Trial simulation

Mathematical framework predicting patient progression-free survival from unmatched single-cell data.

 popTK visual

Trial outcome prediction from pre-clinical data

Mathematical framework parameterised with treatment data from panels of xenografts and cell lines, allowing prediction of progression-free survival gains over standard of care.

 BRCA NE visual

Neuroendocrine transdifferentiation in breast cancer

Identification of molecular drivers and effective therapy combination for this extraordinarily aggressive cancer.