DN-ODE: Data-driven neural-ODE modeling for breast cancer tumor dynamics and progression-free survivals.

Pharmacokinetic/Pharmacodynamic (PK/PD) modeling is crucial in the development of new drugs. However, traditional population-based PK/PD models encounter challenges when modeling for individual patients. We aim to explore the potential of constructing a pharmacodynamic model for individual breast cancer pharmacodynamics leveraging only limited data from early clinical trial phases.

Joint modeling of tumor dynamics and progression-free survival in advanced breast cancer: Leveraging data from amcenestrant early phase I-II trials.

A joint modeling framework was developed using data from 75 patients of early amcenestrant phase I-II AMEERA-1-2 dose escalation and expansion cohorts. A semi-mechanistic tumor growth inhibition (TGI) model was developed. It accounts for the dynamics of sensitive and resistant tumor cells, an exposure-driven effect on tumor proliferation of sensitive cells, and a delay in the initiation of treatment effect to describe the time course of target lesion tumor size (TS) data.

Joint modelling and simulation of M-protein dynamics and progression-free survival for alternative isatuximab dosing with pomalidomide/dexamethasone.

Aims: Addition of isatuximab (Isa) to pomalidomide/dexamethasone (Pd) significantly improved progression-free survival (PFS) in patients with relapsed/refractory multiple myeloma (RRMM). We aimed to characterize the relationship between serum M-protein kinetics and PFS in the phase 3 ICARIA-MM trial (NCT02990338), and to evaluate an alternative dosing regimen of Isa by simulation.

Methods: Data from the ICARIA-MM trial comparing Isa 10 mg/kg weekly for 4 weeks then every 2 weeks (QW-Q2W) in combination with Pd versus Pd in 256 evaluable RRMM patients were used.

Application of Item Response Theory to Model Disease Progression and Agomelatine Effect in Patients with Major Depressive Disorder.

Introduction: In this paper, we studied the effect over time of agomelatine, an antidepressant drug administered in patient with major depressive disorder, through item response theory (IRT), taking into account a strong placebo effect and missing not at random. We also assessed the informativeness of the HAMD-17 scale's item.

Materials And Methods: The data includes five phase III clinical trials sponsored by Servier Institute, totalling 1549 patients followed during a maximum of 1 year.

Time-to-Event Modeling of Left- or Right-Censored Toxicity Data in Nonclinical Drug Toxicology.

A time-to-event (TTE) model has been developed to characterize a histopathology toxicity that can only be detected at the time of animal sacrifice. The model of choice was a hazard model with a Weibull distribution and dose was a significant covariate. The diagnostic plots showed a satisfactory fit of the data, despite the high degree of left and right censoring.

Development and performance of npde for the evaluation of time-to-event models.

Purpose: Normalised prediction distribution errors (npde) are used to graphically and statistically evaluate mixed-effect models for continuous responses. In this study, our aim was to extend npde to time-to-event (TTE) models and evaluate their performance.

Methods: Let V denote a dataset with censored TTE observations.

A sudden death risk score specifically for hypertension: based on 25 648 individual patient data from six randomized controlled trials.

Objective: To construct a sudden death risk score specifically for hypertension (HYSUD) patients with or without cardiovascular history.

Methods: Data were collected from six randomized controlled trials of antihypertensive treatments with 8044 women and 17 604 men differing in age ranges and blood pressure eligibility criteria. In total, 345 sudden deaths (1.