ArticleThe AAPS journal2011
Performance and robustness of the Monte Carlo importance sampling algorithm using parallelized S-ADAPT for basic and complex mechanistic models.
Article in The AAPS journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed.
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- Pharmacokinetic modelling of efavirenz, atazanavir, lamivudine and tenofovir in the female genital tract of HIV-infected pre-menopausal women.Clinical pharmacokinetics · 2012Trial
- Population pharmacokinetics of piperacillin at two dose levels: influence of nonlinear pharmacokinetics on the pharmacodynamic profile.Antimicrobial agents and chemotherapy · 2012Trial
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- Population pharmacokinetic rationale for intravenous contezolid acefosamil followed by oral contezolid dosage regimens.Antimicrobial agents and chemotherapy · 2024Article
- Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam inAntimicrobial agents and chemotherapy · 2024Article
- Population pharmacokinetics and humanized dosage regimens matching the peak, area, trough, and range of amikacin plasma concentrations in immune-competent murine bloodstream and lung infection models.Antimicrobial agents and chemotherapy · 2024Article
- Comprehensive stability analysis of 13 β-lactams and β-lactamase inhibitors inAntimicrobial agents and chemotherapy · 2024Article
- Improved characterization of aminoglycoside penetration into human lung epithelial lining fluid via population pharmacokinetics.Antimicrobial agents and chemotherapy · 2024Article
- Ceftolozane-Tazobactam against Pseudomonas aeruginosa Cystic Fibrosis Clinical Isolates in the Hollow-Fiber Infection Model: Challenges Imposed by Hypermutability and Heteroresistance.Antimicrobial agents and chemotherapy · 2023Article
- Individual Components of Polymyxin B Modeled via Population Pharmacokinetics to Design Humanized Dosage Regimens for a Bloodstream and Lung Infection Model in Immune-Competent Mice.Antimicrobial agents and chemotherapy · 2023Article
- Central and peripheral lung deposition of fluticasone propionate dry powder inhaler formulations in humans characterized by population pharmacokinetics.Pharmaceutical research · 2023Article
- Penicillin G concentrations required for prophylaxis against Group A Streptococcus infection evaluated using a hollow fibre model and mathematical modelling.The Journal of antimicrobial chemotherapy · 2022Article
- Metaheuristics for pharmacometrics.CPT: pharmacometrics & systems pharmacology · 2021Review
- Combination Regimens of Favipiravir Plus Interferon Alpha Inhibit Chikungunya Virus Replication in Clinically Relevant Human Cell Lines.Microorganisms · 2021Article
- Using machine learning to optimize antibiotic combinations: dosing strategies for meropenem and polymyxin B against carbapenem-resistant Acinetobacter baumannii.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020Article
5 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Monte Carlo Parametric Expectation Maximization (MC-PEM) algorithm can approximate the true log-likelihood as precisely as needed and is efficiently parallelizable. Our objectives were to evaluate an importance sampling version of the MC-PEM algorithm for mechanistic models and to qualify the default estimation settings in SADAPT-TRAN. We assessed bias, imprecision and robustness of this algorithm in S-ADAPT for mechanistic models with up to 45 simultaneously estimated structural parameters, 14 differential equations, and 10 dependent variables (one drug concentration and nine pharmacodynamic effects). Simpler models comprising 15 parameters were estimated using three of the ten dependent variables. We set initial estimates to 0.1 or 10 times the true value and evaluated 30 bootstrap replicates with frequent or sparse sampling. Datasets comprised three dose levels with 16 subjects each. For simultaneous estimation of the full model, the ratio of estimated to true values for structural model parameters (median [5-95% percentile] over 45 parameters) was 1.01 [0.94-1.13] for means and 0.99 [0.68-1.39] for between-subject variances for frequent sampling and 1.02 [0.81-1.47] for means and 1.02 [0.47-2.56] for variances for sparse sampling. Imprecision was ≤25% for 43 of 45 means for frequent sampling. Bias and imprecision was well comparable for the full and simpler models. Parallelized estimation was 23-fold (6.9-fold) faster using 48 threads (eight threads) relative to one thread. The MC-PEM algorithm was robust and provided unbiased and adequately precise means and variances during simultaneous estimation of complex, mechanistic models in a 45 dimensional parameter space with rich or sparse data using poor initial estimates.
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