CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2023, Volume and Issue: 12(11), P. 1569 - 1572
Published: Oct. 18, 2023
Language: Английский
CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2023, Volume and Issue: 13(5), P. 691 - 709
Published: Nov. 16, 2023
Project Optimus is a US Food and Drug Administration Oncology Center of Excellence initiative aimed at reforming the dose selection optimization paradigm in oncology drug development. This project seeks to bring together pharmaceutical companies, international regulatory agencies, academic institutions, patient advocates, other stakeholders. Although there much promise this initiative, are several challenges that need be addressed, including multidimensionality problem oncology, heterogeneity cancer patients, importance evaluating long-term tolerability beyond dose-limiting toxicities, lack reliable biomarkers for efficacy. Through lens Totality Evidence with mindset model-informed development, we offer insights into by building quantitative knowledge base integrating diverse sources data leveraging modeling tools build evidence dosage considering exposure, disease biology, efficacy, toxicity, factors. We believe rational can achieved improving outcomes maximizing therapeutic benefit while minimizing toxicity.
Language: Английский
Citations
23
CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2023, Volume and Issue: 12(11), P. 1738 - 1750
Published: May 11, 2023
The dose/exposure-efficacy analyses are often conducted separately for oncology end points like best overall response, progression-free survival (PFS) and (OS). Multistate models offer to bridge these dose-end point relationships by describing transitions transition times from enrollment progression, death, evaluating transition-specific dose effects. This study aims apply the multistate pharmacometric modeling simulation framework in a optimization setting of bintrafusp alfa, fusion protein targeting TGF-β PD-L1. A model with six states (stable disease [SD], unknown, dropout, death) was developed describe totality endpoints data (time PFS, OS) 80 patients non-small cell lung cancer receiving 500 or 1200 mg alfa. Besides dose, evaluated predictor include time, demographics, premedication, factors, individual clearance derived pharmacokinetic model, tumor dynamic metrics observed size model. We found that probabilities progression death upon decreased over time since enrollment. Patients metastasis at baseline had higher probability progress than without had. Despite failed be statistically significant any transition, combined effect quantified through dose-specific estimates still informative. Simulations predicted 69.2% least 1 month longer, and, 55.6% 2-months longer median OS compared supporting selection future studies.
Language: Английский
Citations
7
CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 13, 2024
Abstract The Markov chain is a stochastic process in which the future value of variable conditionally independent past, given its present value. Data with Markovian features are characterized by: frequent observations relative to expected changes values, many consecutive same‐category or similar‐value at individual level, and positive correlation observed between current previous values for that variable. In drug development clinical settings, data available commonly increasingly often modeled using elements dedicated models. This tutorial presents main characteristics, evaluations, applications various modeling approaches including discrete‐time models (DTMM), continuous‐time (CTMM), hidden models, item‐response theory model sub‐models. has specific emphasis on use DTMM CTMM ordered‐categorical features. Although body this written software‐neutral manner, annotated NONMEM code all key included Supplementary Information.
Language: Английский
Citations
2
CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2023, Volume and Issue: 13(2), P. 222 - 233
Published: Oct. 26, 2023
Abstract Appropriate antibiotic dosing to ensure early and sufficient target attainment is crucial for improving clinical outcome in critically ill patients. Parametric survival analysis a preferred modeling method quantify time‐varying exposure – response effects, whereas bias may be introduced hazard functions when competing events occur. This study investigated predictors of in‐hospital mortality patients treated with meropenem by pharmacometric multistate modeling. A model comprising five states (ongoing treatment, other treatment termination, discharge, death) was developed capture the transitions cohort 577 meropenem. Various factors were as potential transitions, including patient demographics, creatinine clearance calculated Cockcroft–Gault equation (CLCR CG ), time that unbound concentrations exceed minimum inhibitory concentration ( f T >MIC microbiology‐related measures. The probabilities transit from ongoing increased over time. 10 mL/min decrease CLCR found elevate transitioning termination death state 18%. 100% significantly transition rate (by 9.7%), associated improved outcome. prospectively assessed can serve useful tool different infection scenarios, particularly risks are present.
Language: Английский
Citations
4
Journal of Antimicrobial Chemotherapy, Journal Year: 2024, Volume and Issue: 79(10), P. 2561 - 2569
Published: Aug. 1, 2024
Abstract Background Studying long-term treatment outcomes of TB is time-consuming and impractical. Early reliable biomarkers reflecting response capable predicting are urgently needed. Objectives To develop a pharmacometric multistate model to evaluate the link between potential predictors outcomes. Methods Data were obtained from two Phase II clinical trials (TMC207-C208 TMC207-C209) with bedaquiline on top multidrug background regimen. Patients typically followed throughout 24 week investigational period plus 96 follow-up period. A five-state (active TB, converted, recurrent dropout, death) was developed describe observed transitions. Evaluated included patient characteristics, baseline disease severity on-treatment biomarkers. Results fast bacterial clearance in first 2 weeks low burden at increased probability achieve conversion, whereas patients XDR-TB less likely reach conversion. Higher estimated mycobacterial load end recurrence. At 120 weeks, predicted 55% (95% prediction interval, 50%–60%), 6.5% (4.2%–9.0%) 7.5% (5.2%–10%) death states, respectively. Simulations substantial increase recurrence after slow regardless burden. Conclusions The successfully described modelling framework enables several simultaneously, allows mechanistically sound investigation novel promising predictors. This may help support future biomarker evaluation, trial design analysis.
Language: Английский
Citations
0
Advanced Drug Delivery Reviews, Journal Year: 2024, Volume and Issue: unknown, P. 115476 - 115476
Published: Nov. 1, 2024
Model-based approaches, including population pharmacokinetic-pharmacodynamic modeling, have become an essential component in the clinical phases of oncology drug development. Over past two decades, models evolved to describe temporal dynamics biomarkers and tumor size, treatment-related adverse events, their links survival. Integrated models, defined here as that incorporate at least pharmacodynamic/ outcome variables, are applied answer development questions through simulations, e.g. support exploration alternative dosing strategies study designs subgroups patients or other indications. It is expected these pharmacometric approaches will be expanded regulatory authorities place further emphasis on early individualized dosage optimization inclusive patient-focused strategies. This review provides overview integrated literature, examples considerations need made when applying advanced outlook expansion model-informed anticancer drugs.
Language: Английский
Citations
0
CPT Pharmacometrics & Systems Pharmacology, Journal Year: 2023, Volume and Issue: 12(11), P. 1569 - 1572
Published: Oct. 18, 2023
Language: Английский
Citations
1