A Combination Regimen Design Program Based on Pharmacodynamic Target Setting for Childhood Tuberculosis: Design Rules for the Playground

Clinical Infectious Diseases

Volumn 63, Issue , 2016, Pages S75-S79

  Srivastava, Shashikant ^a   Deshpande, Devyani ^a   Pasipanodya, Jotam G ^a   Thomas, Tania ^b   Swaminathan, Soumya ^c   Nuermberger, Eric ^d   Gumbo, Tawanda ^a,e  

^a BAYLOR RESEARCH INSTITUTE   (United States)

^b UNIVERSITY OF VIRGINIA   (United States)

^c NATIONAL INSTITUTE FOR RESEARCH IN TUBERCULOSIS   (India)

^d JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e UNIVERSITY OF CAPE TOWN   (South Africa)

Author keywords

disseminated tuberculosis; drug regimen design; pharmacokinetics pharmacodynamics; target setting; young children

Indexed keywords

ANTIBIOTIC AGENT; TUBERCULOSTATIC AGENT;

ANTIBIOTIC THERAPY; ARTICLE; CHILD; CHILDHOOD DISEASE; COMBINATION DRUG THERAPY; DRUG EFFICACY; DRUG EXPOSURE; HUMAN; MILIARY TUBERCULOSIS; MONOTHERAPY; MONTE CARLO METHOD; NONHUMAN; PHARMACODYNAMICS; PRIORITY JOURNAL; TREATMENT FAILURE; AGE; COMPUTER SIMULATION; DRUG MONITORING; INFANT; MICROBIAL SENSITIVITY TEST; MICROBIOLOGY; NEWBORN; PRESCHOOL CHILD; PROCEDURES; STANDARDS; TUBERCULOSIS;

AGE FACTORS; ANTITUBERCULAR AGENTS; CHILD, PRESCHOOL; COMPUTER SIMULATION; DRUG MONITORING; DRUG THERAPY, COMBINATION; HUMANS; INFANT; INFANT, NEWBORN; MICROBIAL SENSITIVITY TESTS; MONTE CARLO METHOD; TUBERCULOSIS;

EID: 84994660122     PISSN: 10584838     EISSN: 15376591     Source Type: Journal    
DOI: 10.1093/cid/ciw472     Document Type: Article

References (39)

1. Cruz AT, Martinez BJ. Childhood tuberculosis in the United States: shifting the focus to prevention. Int J Tuberc Lung Dis 2015; 19(suppl 1):50-3.
2. Perez-Velez CM, Marais BJ. Tuberculosis in children. N Engl J Med 2012; 367:348-61.
3. Jenkins HE, Tolman AW, Yuen CM, et al. Incidence of multidrug-resistant tuberculosis disease in children: systematic review and global estimates. Lancet 2014; 383:1572-9.
4. Becerra MC, Swaminathan S. Commentary: a targets framework: dismantling the invisibility trap for children with drug-resistant tuberculosis. J Public Health Policy 2014; 35:425-54.
5. International Union Against Tuberculosis and Lung Disease. Desk-guide for diagnosis and management of TB in children. Paris: The Union, 2014.
6. Rogers Z, Hiruy H, Pasipanodya J, et al. The non-linear child: ontogeny, isoniazid concentration, and NAT2 gene interactions modulate enzyme reaction kinetics and metabolism. EBioMedicine 2016. Available at: http://dx.doi.org/10.1016/j. ebiom.2016.07.031. Accessed 2016.
7. Swaminathan S, Pasipanodya J, Ramachandran G, et al. Drug concentration thresholds predictive of therapy failure and death in children with tuberculosis: bread crumb trails in random forests. Clin Infect Dis 2016; 63(suppl 3):S63-74.
8. Momper JD, Mulugeta Y, Burckart GJ. Failed pediatric drug development trials. Clin Pharmacol Ther 2015; 98:245-51.
9. Kearns GL, Abdel-Rahman SM, Alander SW, Blowey DL, Leeder JS, Kauffman RE. Developmental pharmacology - drug disposition, action, and therapy in infants and children. N Engl J Med 2003; 349:1157-67.
10. Sutherland JM. Fatal cardiovascular collapse of infants receiving large amounts of chloramphenicol. AMA J Dis Child 1959; 97:761-7.
11. Weiss CF, Glazko AJ,Weston JK. Chloramphenicol in the newborn infant. A physiologic explanation of its toxicity when given in excessive doses. N Engl J Med 1960; 262:787-94.
12. Kearns GL, Jungbluth GL, Abdel-Rahman SM, et al. Impact of ontogeny on linezolid disposition in neonates and infants. Clin Pharmacol Ther 2003; 74:413-22.
13. Kearns GL, Abdel-Rahman SM, Blumer JL, et al. Single dose pharmacokinetics of linezolid in infants and children. Pediatr Infect Dis J 2000; 19:1178-84.
14. Pasipanodya JG, Nuermberger E, Romero K, Hanna D, Gumbo T. Systematic analysis of hollow fiber model of tuberculosis experiments. Clin Infect Dis 2015; 61:S10-7.
15. Gumbo T, Lenaerts AJ, Hanna D, Romero K, Nuermberger E. Nonclinical models for antituberculosis drug development: a landscape analysis. J Infect Dis 2015; 211(suppl 3):S83-95.
16. Gumbo T, Pasipanodya JG, Romero K, Hanna D, Nuermberger E. Forecasting accuracy of the hollow fiber model of tuberculosis for clinical therapeutic outcomes. Clin Infect Dis 2015; 61:S25-31.
17. Srivastava S, Gumbo T. In vitro and in vivo modeling of tuberculosis drugs and its impact on optimization of doses and regimens. Curr Pharm Des 2011; 17:2881-8.
18. Gumbo T. New susceptibility breakpoints for first-line antituberculosis drugs based on antimicrobial pharmacokinetic/pharmacodynamic science and population pharmacokinetic variability. Antimicrob Agents Chemother 2010; 54:1484-91.
19. Srivastava S, Pasipanodya JG, Ramachandran G, et al. A long-term co-perfused disseminated tuberculosis-3D liver hollow fiber model for both drug efficacy and hepatotoxicity in babies. EBioMedicine 2016; 6:126-38.
20. Irwin SM, Gruppo V, Brooks E, et al. Limited activity of clofazimine as a single drug in a mouse model of tuberculosis exhibiting caseous necrotic granulomas. Antimicrob Agents Chemother 2014; 58:4026-34.
21. Lanoix JP, Ioerger T, Ormond A, et al. Selective inactivity of pyrazinamide against tuberculosis in C3HeB/FeJ mice is best explained by neutral pH of caseum. Antimicrob Agents Chemother 2015; 60:735-43.
22. Prideaux B, Via LE, Zimmerman MD, et al. The association between sterilizing activity and drug distribution into tuberculosis lesions. Nat Med 2015; 21:1223-7.
23. Sakai C, Iwaano S, Yamazaki Y, et al. Species differences in the pharmacokinetic parameters of cytochrome P450 probe substrates between experimental animals, such as mice, rats, dogs, monkeys, and microminipigs, and humans. J Drug Metab Toxicol 2014; 5:173.
24. Bliss CI. The toxicity of poisons applied jointly. Ann Appl Biol 1939; 26:585-615.
25. Deshpande D, Srivastava S, Nuermberger E, Pasipanodya J, Swaminathan S, Gumbo T. Concentration-dependent synergy and antagonism of linezolid and moxifloxacin in the treatment of childhood tuberculosis: the dynamic duo. Clin Infect Dis 2016; 63(suppl 3):S88-94.
26. Jeena PM, Bishai WR, Pasipanodya JG, Gumbo T. In silico children and the glass mouse model: clinical trial simulations to identify and individualize optimal isoniazid doses in children with tuberculosis. Antimicrob Agents Chemother 2011; 55:539-45.
27. Metropolis N, Ulam S. The Monte Carlo method. J Am Stat Assoc 1949; 44:335-41.
28. Drusano GL, Preston SL, Hardalo C, et al. Use of preclinical data for selection of a phase II/III dose for evernimicin and identification of a preclinical MIC breakpoint. Antimicrob Agents Chemother 2001; 45:13-22.
29. Gumbo T, Angulo-Barturen I, Ferrer-Bazaga S. Pharmacokinetic-pharmacodynamic and dose-response relationships of antituberculosis drugs: recommendations and standards for industry and academia. J Infect Dis 2015; 211(suppl 3): S96-106.
30. Pasipanodya J, Gumbo T. An oracle: antituberculosis pharmacokinetics-pharmacodynamics, clinical correlation, and clinical trial simulations to predict the future. Antimicrob Agents Chemother 2011; 55:24-34.
31. Ford CB, Shah RR, Maeda MK, et al. Mycobacterium tuberculosis mutation rate estimates from different lineages predict substantial differences in the emergence of drug-resistant tuberculosis. Nat Genet 2013; 45:784-90.
32. Gumbo T. Biological variability and the emergence of multidrug-resistant tuberculosis. Nat Genet 2013; 45:720-1.
33. Pasipanodya J, Srivastava S, Gumbo T. New susceptibility breakpoints and the regional variability of MIC distribution in Mycobacterium tuberculosis isolates. Antimicrob Agents Chemother 2012; 56:5428.
34. Gumbo T, Pasipanodya JG, Nuermberger E, Romero K, Hanna D. Correlations between the hollow fiber model of tuberculosis and therapeutic events in tuberculosis patients: learn and confirm. Clin Infect Dis 2015; 61:S18-24.
35. Pasipanodya JG, McIlleron H, Burger A, Wash PA, Smith P, Gumbo T. Serum drug concentrations predictive of pulmonary tuberculosis outcomes. J Infect Dis 2013; 208:1464-73.
36. Chigutsa E, Pasipanodya JG, Visser ME, et al. Impact of nonlinear interactions of pharmacokinetics and MICs on sputum bacillary kill rates as a marker of sterilizing effect in tuberculosis. Antimicrob Agents Chemother 2015; 59:38-45.
37. Deshpande D, Srivastava S, Pasipanodya JG, et al. Linezolid for infants and toddlers with disseminated tuberculosis: first steps. Clin Infect Dis 2016; 63(suppl 3): S80-7.
38. Deshpande D, Srivastava S, Nuermberger E, Pasipanodya J, Swaminathan S, Gumbo T. A faropenem, linezolid, and moxifloxacin regimen for both drug-susceptible and multidrug-resistant tuberculosis in children: FLAME path on the Milky Way. Clin Infect Dis 2016; 63(suppl 3):S95-101.
39. Srivastava S, Deshpande D, Pasipanodya J, et al. Optimal clinical doses of faropenem, linezolid, and moxifloxacin in children with disseminated tuberculosis: Goldilocks. Clin Infect Dis 2016; 63(suppl 3):S109-9.