Levofloxacin Pharmacokinetics/Pharmacodynamics, Dosing, Susceptibility Breakpoints, and Artificial Intelligence in the Treatment of Multidrug-resistant Tuberculosis
| Autor: | Scott K. Heysell, Paul G. Ambrose, Guy E. Thwaites, Pooi S Lee, Paula Bendet, Shashikant Srivastava, Tawanda Gumbo, Thearith Koeuth, Sujata M. Bhavnani, Devyani Deshpande, Jotam G. Pasipanodya, Stellah G. Mpagama |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Microbiology (medical) Tuberculosis medicine.drug_class 030106 microbiology Antibiotics Antitubercular Agents Supplement Articles Drug resistance Levofloxacin Microbial Sensitivity Tests Tuberculous meningitis lung Mycobacterium tuberculosis 03 medical and health sciences Moxifloxacin Artificial Intelligence Drug Resistance Multiple Bacterial Tuberculosis Multidrug-Resistant pharmacodynamics Medicine Humans Tuberculosis Pulmonary minimum inhibitory concentration measurement biology business.industry Sputum multidrug-resistant tuberculosis medicine.disease biology.organism_classification probit trial Infectious Diseases tuberculosis exposure minimum inhibitory concentration result tuberculous meningitis Pharmacodynamics Drug Therapy Combination Artificial intelligence mutation moxifloxacin business pharmacokinetics pulmonary tuberculosis Monte Carlo Method Algorithms medicine.drug |
| Popis: | Background Levofloxacin is used for the treatment of multidrug-resistant tuberculosis; however the optimal dose is unknown. Methods We used the hollow fiber system model of tuberculosis (HFS-TB) to identify 0–24 hour area under the concentration-time curve (AUC0-24) to minimum inhibitory concentration (MIC) ratios associated with maximal microbial kill and suppression of acquired drug resistance (ADR) of Mycobacterium tuberculosis (Mtb). Levofloxacin-resistant isolates underwent whole-genome sequencing. Ten thousands patient Monte Carlo experiments (MCEs) were used to identify doses best able to achieve the HFS-TB–derived target exposures in cavitary tuberculosis and tuberculous meningitis. Next, we used an ensemble of artificial intelligence (AI) algorithms to identify the most important predictors of sputum conversion, ADR, and death in Tanzanian patients with pulmonary multidrug-resistant tuberculosis treated with a levofloxacin-containing regimen. We also performed probit regression to identify optimal levofloxacin doses in Vietnamese tuberculous meningitis patients. Results In the HFS-TB, the AUC0-24/MIC associated with maximal Mtb kill was 146, while that associated with suppression of resistance was 360. The most common gyrA mutations in resistant Mtb were Asp94Gly, Asp94Asn, and Asp94Tyr. The minimum dose to achieve target exposures in MCEs was 1500 mg/day. AI algorithms identified an AUC0-24/MIC of 160 as predictive of microbiologic cure, followed by levofloxacin 2-hour peak concentration and body weight. Probit regression identified an optimal dose of 25 mg/kg as associated with >90% favorable response in adults with pulmonary tuberculosis. Conclusions The levofloxacin dose of 25 mg/kg or 1500 mg/day was adequate for replacement of high-dose moxifloxacin in treatment of multidrug-resistant tuberculosis. |
| Databáze: | OpenAIRE |
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