epitherapies

Codes associated with the paper "A mechanistic digital twin model for epigenetic therapy optimization in triple-negative breast cancer" by Bruno et al. More precisely, this repository contains the codes used to develop and simulate digital twin model for epigenetic therapy optimization in triple-negative breast cancer , as presented in the associated manuscript. The digital twin model integrates mechanistic modeling of chromatin dynamics and tumor progression with pharmacological inputs to study treatment effects, resistance mechanisms, and alternative therapeutic strategies.

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Repository Structure:

• SB_Digital_Twin_Main_Model_Population.R Main digital twin model for combined epigenetic and signaling therapy (tazemetostat + ipatasertib) for population optimization

• SB_Digital_Twin_Main_Model_Patient_Specific.R Main digital twin model for combined epigenetic and signaling therapy (tazemetostat + ipatasertib) for patient-specific optimization

• SB_Digital_Twin_Resist_Model.R Extension of the model to study resistance mechanisms

• SB_Digital_Twin_Capiv.R Alternative treatment scenario using capivasertib

• Posterior_samples_population.Rds Pre-estimated parameters for the population study

• Posterior_samples_patient_i.Rds Pre-estimated parameters for the patient-specific study, with i = 1,2,3,4 for patient 1,2,3,4, respectively.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Setup

Before running any script, you must update the output directories in each file: output_location <- "/Users/..." # to be modified output_location_figures <- "/Users/..." # to be modified Set these paths to your desired local directories where results and figures will be saved.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Reproducibility

• All simulations use estimated parameter values stored in: Posterior_samples_population.Rds Posterior_samples_patient_i.Rds with i = 1,2,3,4 for patient 1,2,3,4, respectively.