Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design

Abstract Clinical development of combination chemotherapies for tuberculosis (TB) is complicated by partial or restricted phase II dose‐finding. Barriers include a propensity for drug resistance with monotherapy, practical limits on numbers of treatment arms for component dose combinations, and limi...

Full description

Bibliographic Details
Main Author: Michael A. Lyons
Format: Article
Language:English
Published: Wiley 2021-03-01
Series:CPT: Pharmacometrics & Systems Pharmacology
Online Access:https://doi.org/10.1002/psp4.12591
id doaj-a548a60e8de646bf8afb6d4770a04845
record_format Article
spelling doaj-a548a60e8de646bf8afb6d4770a048452021-03-17T03:51:07ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062021-03-0110321121910.1002/psp4.12591Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen designMichael A. Lyons0Mycobacteria Research Laboratories Department of Microbiology, Immunology and Pathology Colorado State University Fort Collins Colorado USAAbstract Clinical development of combination chemotherapies for tuberculosis (TB) is complicated by partial or restricted phase II dose‐finding. Barriers include a propensity for drug resistance with monotherapy, practical limits on numbers of treatment arms for component dose combinations, and limited application of current dose selection methods to multidrug regimens. A multi‐objective optimization approach to dose selection was developed as a conceptual and computational framework for currently evolving approaches to clinical testing of novel TB regimens. Pharmacokinetic‐pharmacodynamic (PK‐PD) modeling was combined with an evolutionary algorithm to identify dosage regimens that yield optimal trade‐offs between multiple conflicting therapeutic objectives. The phase IIa studies for pretomanid, a newly approved nitroimidazole for specific cases of highly drug‐resistant pulmonary TB, were used to demonstrate the approach with Pareto optimized dosing that best minimized sputum bacillary load and the probability of drug‐related adverse events. Results include a population‐typical characterization of the recommended 200 mg once daily dosage, the optimality of time‐dependent dosing, examples of individualized therapy, and the determination of optimal loading doses. The approach generalizes conventional PK‐PD target attainment to a design problem that scales to drug combinations, and provides a benefit‐risk context for clinical testing of complex drug regimens.https://doi.org/10.1002/psp4.12591
collection DOAJ
language English
format Article
sources DOAJ
author Michael A. Lyons
spellingShingle Michael A. Lyons
Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design
CPT: Pharmacometrics & Systems Pharmacology
author_facet Michael A. Lyons
author_sort Michael A. Lyons
title Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design
title_short Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design
title_full Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design
title_fullStr Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design
title_full_unstemmed Pretomanid dose selection for pulmonary tuberculosis: An application of multi‐objective optimization to dosage regimen design
title_sort pretomanid dose selection for pulmonary tuberculosis: an application of multi‐objective optimization to dosage regimen design
publisher Wiley
series CPT: Pharmacometrics & Systems Pharmacology
issn 2163-8306
publishDate 2021-03-01
description Abstract Clinical development of combination chemotherapies for tuberculosis (TB) is complicated by partial or restricted phase II dose‐finding. Barriers include a propensity for drug resistance with monotherapy, practical limits on numbers of treatment arms for component dose combinations, and limited application of current dose selection methods to multidrug regimens. A multi‐objective optimization approach to dose selection was developed as a conceptual and computational framework for currently evolving approaches to clinical testing of novel TB regimens. Pharmacokinetic‐pharmacodynamic (PK‐PD) modeling was combined with an evolutionary algorithm to identify dosage regimens that yield optimal trade‐offs between multiple conflicting therapeutic objectives. The phase IIa studies for pretomanid, a newly approved nitroimidazole for specific cases of highly drug‐resistant pulmonary TB, were used to demonstrate the approach with Pareto optimized dosing that best minimized sputum bacillary load and the probability of drug‐related adverse events. Results include a population‐typical characterization of the recommended 200 mg once daily dosage, the optimality of time‐dependent dosing, examples of individualized therapy, and the determination of optimal loading doses. The approach generalizes conventional PK‐PD target attainment to a design problem that scales to drug combinations, and provides a benefit‐risk context for clinical testing of complex drug regimens.
url https://doi.org/10.1002/psp4.12591
work_keys_str_mv AT michaelalyons pretomaniddoseselectionforpulmonarytuberculosisanapplicationofmultiobjectiveoptimizationtodosageregimendesign
_version_ 1724218917169135616