1932

Abstract

Malaria is a critical public health problem resulting in substantial morbidity and mortality, particularly in developing countries. Owing to the development of resistance toward current therapies, novel approaches to accelerate the development efforts of new malaria therapeutics are urgently needed. There have been significant advancements in the development of in vitro and in vivo experiments that generate data used to inform decisions about the potential merit of new compounds. A comprehensive disease-drug model capable of integrating discrete data from different preclinical and clinical components would be a valuable tool across all stages of drug development. This could have an enormous impact on the otherwise slow and resource-intensive process of traditional clinical drug development.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-pharmtox-010715-103429
2018-01-06
2024-04-19
Loading full text...

Full text loading...

/deliver/fulltext/pharmtox/58/1/annurev-pharmtox-010715-103429.html?itemId=/content/journals/10.1146/annurev-pharmtox-010715-103429&mimeType=html&fmt=ahah

Literature Cited

  1. 1. WHO (World Health Organ.). 2015. Achieving the Malaria MDG Target: Reversing the Incidence of Malaria 2000–2015 Geneva: WHO
  2. Gates B, Chambers R. 2.  2017. From Aspiration to Action: What Will It Take to End Malaria? Geneva: Med. Malar. Ventur.
  3. Berman J, Radhakrishna T. 3.  2017. The tropical disease priority review voucher: a game-changer for tropical disease products. Am. J. Trop. Med. Hyg. 96:11–13 [Google Scholar]
  4. Ridley DB. 4.  2017. Priorities for the priority review voucher. Am. J. Trop. Med. Hyg. 96:14–15 [Google Scholar]
  5. Burrows JN, Duparc S, Gutteridge WE, Hooft van Huijsduijnen R, Kaszubska W. 5.  et al. 2017. New developments in anti-malarial target candidate and product profiles. Malar. J. 16:26 [Google Scholar]
  6. McCarthy J. 6.  2016. Induced blood stage malaria: a tool to facilitate development of antimalarials Presented at Clin. Trial Des. Consid. Malar. Drug Devel., June 30 Silver Spring, MD:
  7. McCarthy JS, Baker M, O'Rourke P, Marquart L, Griffin P. 7.  et al. 2016. Efficacy of OZ439 (artefenomel) against early Plasmodium falciparum blood-stage malaria infection in healthy volunteers. J. Antimicrob. Chemother. 71:2620–27 [Google Scholar]
  8. McCarthy JS, Marquart L, Sekuloski S, Trenholme K, Elliott S. 8.  et al. 2016. Linking murine and human Plasmodium falciparum challenge models in a translational path for antimalarial drug development. Antimicrob. Agents Chemother. 60:3669–75 [Google Scholar]
  9. McCarthy JS, Sekuloski S, Griffin PM, Elliott S, Douglas N. 9.  et al. 2011. A pilot randomised trial of induced blood-stage Plasmodium falciparum infections in healthy volunteers for testing efficacy of new antimalarial drugs. PLOS ONE 6:e21914 [Google Scholar]
  10. 10. FDA (US Food Drug Adm.). 2017. FDA briefing document: pharmaceutical science and clinical pharmacology advisory committee meeting Brief. Doc., FDA Silver Spring, MD:
  11. Wagner C, Pan Y, Hsu V, Grillo JA, Zhang L. 11.  et al. 2015. Predicting the effect of cytochrome P450 inhibitors on substrate drugs: analysis of physiologically based pharmacokinetic modeling submissions to the US Food and Drug Administration. Clin. Pharmacokinet. 54:117–27 [Google Scholar]
  12. Wagner C, Pan Y, Hsu V, Sinha V, Zhao P. 12.  2016. Predicting the effect of CYP3A inducers on the pharmacokinetics of substrate drugs using physiologically based pharmacokinetic (PBPK) modeling: an analysis of PBPK submissions to the US FDA. Clin. Pharmacokinet. 55:475–83 [Google Scholar]
  13. Vieira MD, Kim MJ, Apparaju S, Sinha V, Zineh I. 13.  et al. 2014. PBPK model describes the effects of comedication and genetic polymorphism on systemic exposure of drugs that undergo multiple clearance pathways. Clin. Pharmacol. Ther. 95:550–57 [Google Scholar]
  14. Morris WWD, Grasela T, Clark R. 14.  2017. PI-078 novel antimalarial identification using in silico prediction methods and simulation. Clin. Pharmacol. Ther. 101:S40 [Google Scholar]
  15. Ito R, Takahashi T, Katano I, Ito M. 15.  2012. Current advances in humanized mouse models. Cell Mol. Immunol. 9:208–14 [Google Scholar]
  16. Jiménez-Díaz MB, Mulet T, Viera S, Gómez V, Garuti H. 16.  et al. 2009. Improved murine model of malaria using Plasmodium falciparum competent strains and non-myelodepleted NOD-scid IL2Rγnull mice engrafted with human erythrocytes. Antimicrob. Agents Chemother. 53:4533–36 [Google Scholar]
  17. Le Manach C, Nchinda AT, Paquet T, Gonzàlez Cabrera D, Younis Y. 17.  et al. 2016. Identification of a potential antimalarial drug candidate from a series of 2-aminopyrazines by optimization of aqueous solubility and potency across the parasite life cycle. J. Med. Chem. 59:9890–905 [Google Scholar]
  18. Phillips MA, Lotharius J, Marsh K, White J, Dayan A. 18.  et al. 2015. A long-duration dihydroorotate dehydrogenase inhibitor (DSM265) for prevention and treatment of malaria. Sci. Transl. Med. 7:296ra111 [Google Scholar]
  19. Le Bihan A, de Kanter R, Angulo-Barturen I, Binkert C, Boss C. 19.  et al. 2016. Characterization of novel antimalarial compound ACT-451840: preclinical assessment of activity and dose-efficacy modeling. PLOS Med 13:e1002138 [Google Scholar]
  20. Baragana B, Hallyburton I, Lee MC, Norcross NR, Grimaldi R. 20.  et al. 2015. A novel multiple-stage antimalarial agent that inhibits protein synthesis. Nature 522:315–20 [Google Scholar]
  21. Jiménez-Díaz MB, Ebert D, Salinas Y, Pradhan A, Lehane AM. 21.  et al. 2014. (+)-SJ733, a clinical candidate for malaria that acts through ATP4 to induce rapid host-mediated clearance of Plasmodium. PNAS 111:E5455–62 [Google Scholar]
  22. Nilsen A, LaCrue AN, White KL, Forquer IP, Cross RM. 22.  et al. 2013. Quinolone-3-diarylethers: a new class of antimalarial drug. Sci. Transl. Med. 5:177ra37 [Google Scholar]
  23. 23. FDA (US Food Drug Adm.). 2007. Guidance for industry: malaria: developing drug and nonvaccine biological products for treatment and prophylaxis Guid. Doc., FDA Rockville, MD:
  24. Patel K, Simpson JA, Batty KT, Zaloumis S, Kirkpatrick CM. 24.  2015. Modelling the time course of antimalarial parasite killing: a tour of animal and human models, translation and challenges. Br. J. Clin. Pharmacol. 79:97–107 [Google Scholar]
  25. Patel K, Batty KT, Moore BR, Gibbons PL, Kirkpatrick CM. 25.  2014. Predicting the parasite killing effect of artemisinin combination therapy in a murine malaria model. J. Antimicrob. Chemother. 69:2155–63 [Google Scholar]
  26. Patel K, Batty KT, Moore BR, Gibbons PL, Bulitta JB, Kirkpatrick CM. 26.  2013. Mechanism-based model of parasite growth and dihydroartemisinin pharmacodynamics in murine malaria. Antimicrob. Agents Chemother. 57:508–16 [Google Scholar]
  27. Jiménez-Díaz MB, Viera S, Ibáñez J, Mulet T, Magán-Marchal N. 27.  et al. 2013. A new in vivo screening paradigm to accelerate antimalarial drug discovery. PLOS ONE 8:e66967 [Google Scholar]
  28. Tarning J, Zongo I, Some FA, Rouamba N, Parikh S. 28.  et al. 2012. Population pharmacokinetics and pharmacodynamics of piperaquine in children with uncomplicated falciparum malaria. Clin. Pharmacol. Ther. 91:497–505 [Google Scholar]
  29. Hoglund RM, Workman L, Edstein MD, Thanh NX, Quang NN. 29.  et al. 2017. Population pharmacokinetic properties of piperaquine in falciparum malaria: an individual participant data meta-analysis. PLOS Med 14:e1002212 [Google Scholar]
  30. Hendriksen IC, Maiga D, Lemnge MM, Mtove G, Gesase S. 30.  et al. 2013. Population pharmacokinetic and pharmacodynamic properties of intramuscular quinine in Tanzanian children with severe falciparum malaria. Antimicrob. Agents Chemother. 57:775–83 [Google Scholar]
  31. Douglas NM, Lampah DA, Kenangalem E, Simpson JA, Poespoprodjo JR. 31.  et al. 2013. Major burden of severe anemia from non-falciparum malaria species in Southern Papua: a hospital-based surveillance study. PLOS Med 10:e1001575 [Google Scholar]
  32. Kloprogge F, Piola P, Dhorda M, Muwanga S, Turyakira E. 32.  et al. 2013. Population pharmacokinetics of lumefantrine in pregnant and nonpregnant women with uncomplicated Plasmodium falciparum malaria in Uganda. CPT Pharmacomet. Syst. Pharmacol. 2:e83 [Google Scholar]
  33. Hendriksen IC, Mtove G, Kent A, Gesase S, Reyburn H. 33.  et al. 2013. Population pharmacokinetics of intramuscular artesunate in African children with severe malaria: implications for a practical dosing regimen. Clin. Pharmacol. Ther. 93:443–50 [Google Scholar]
  34. Johnson TN, Rostami-Hodjegan A. 34.  2011. Resurgence in the use of physiologically based pharmacokinetic models in pediatric clinical pharmacology: parallel shift in incorporating the knowledge of biological elements and increased applicability to drug development and clinical practice. Paediatr. Anaesth. 21:291–301 [Google Scholar]
  35. 35. Simulations Plus. 2015. GastroPlus user's manual, version 9.0.0007 User's Man., 208–19 Simul. Plus Lancaster, CA: [Google Scholar]
  36. Abduljalil K, Furness P, Johnson TN, Rostami-Hodjegan A, Soltani H. 36.  2012. Anatomical, physiological and metabolic changes with gestational age during normal pregnancy: a database for parameters required in physiologically based pharmacokinetic modelling. Clin. Pharmacokinet. 51:365–96 [Google Scholar]
  37. White LJ, Maude RJ, Pongtavornpinyo W, Saralamba S, Aguas R. 37.  et al. 2009. The role of simple mathematical models in malaria elimination strategy design. Malar. J. 8:212 [Google Scholar]
  38. Mandal S, Sarkar RR, Sinha S. 38.  2011. Mathematical models of malaria - a review. Malar. J. 10:202 [Google Scholar]
  39. Gravenor MB, Lloyd AL, Kremsner PG, Missinou MA, English M. 39.  et al. 2002. A model for estimating total parasite load in falciparum malaria patients. J. Theor. Biol. 217:137–48 [Google Scholar]
  40. McKenzie FE, Bossert WH. 40.  2005. An integrated model of Plasmodium falciparum dynamics. J. Theor. Biol. 232:411–26 [Google Scholar]
  41. Miller LH, Ackerman HC, Su XZ, Wellems TE. 41.  2013. Malaria biology and disease pathogenesis: insights for new treatments. Nat. Med. 19:156–67 [Google Scholar]
  42. Silal SP, Little F, Barnes KI, White LJ. 42.  2014. Towards malaria elimination in Mpumalanga, South Africa: a population-level mathematical modelling approach. Malar. J. 13:297 [Google Scholar]
  43. Eckhoff PA. 43.  2011. A malaria transmission-directed model of mosquito life cycle and ecology. Malar. J. 10:303 [Google Scholar]
  44. Yakob L, Yan G. 44.  2010. A network population model of the dynamics and control of African malaria vectors. Trans. R. Soc. Trop. Med. Hyg. 104:669–75 [Google Scholar]
  45. Chitnis N, Schapira A, Smith T, Steketee R. 45.  2010. Comparing the effectiveness of malaria vector-control interventions through a mathematical model. Am. J. Trop. Med. Hyg. 83:230–40 [Google Scholar]
  46. Ghosh M, Lashari AA, Xue-Zhi Li. 46.  2013. Biological control of malaria: a mathematical model. Appl. Math. Comput. 219:7923–39 [Google Scholar]
  47. Gerardin J, Eckhoff P, Wenger EA. 47.  2015. Mass campaigns with antimalarial drugs: a modelling comparison of artemether-lumefantrine and DHA-piperaquine with and without primaquine as tools for malaria control and elimination. BMC Infect. Dis. 15:144 [Google Scholar]
  48. Stuckey EM, Stevenson J, Galactionova K, Baidjoe AY, Bousema T. 48.  et al. 2014. Modeling the cost effectiveness of malaria control interventions in the highlands of western Kenya. PLOS ONE 9:e107700 [Google Scholar]
  49. Pongtavornpinyo W, Yeung S, Hastings IM, Dondorp AM, Day NP, White NJ. 49.  2008. Spread of anti-malarial drug resistance: mathematical model with implications for ACT drug policies. Malar. J. 7:229 [Google Scholar]
  50. Hecht D, Fogel GB. 50.  2012. Modeling the evolution of drug resistance in malaria. J. Comput.-Aided Mol. Des. 26:1343–53 [Google Scholar]
  51. Ayala D, Guerrero RF, Kirkpatrick M. 51.  2013. Reproductive isolation and local adaptation quantified for a chromosome inversion in a malaria mosquito. Evolution 67:946–58 [Google Scholar]
  52. Eckhoff PA. 52.  2012. Malaria parasite diversity and transmission intensity affect development of parasitological immunity in a mathematical model. Malar. J. 11:419 [Google Scholar]
  53. Pinkevych M, Petravic J, Chelimo K, Kazura JW, Moormann AM, Davenport MP. 53.  2012. The dynamics of naturally acquired immunity to Plasmodium falciparum infection. PLOS Comput. Biol. 8:e1002729 [Google Scholar]
  54. Simpson JA, Zaloumis S, DeLivera AM, Price RN, McCaw JM. 54.  2014. Making the most of clinical data: reviewing the role of pharmacokinetic-pharmacodynamic models of anti-malarial drugs. AAPS J 16:962–74 [Google Scholar]
  55. Grasela TH, Slusser R. 55.  2014. The paradox of scientific excellence and the search for productivity in pharmaceutical research and development. Clin. Pharmacol. Ther. 95:521–27 [Google Scholar]
  56. Berry SM, Connor JT, Lewis RJ. 56.  2015. The platform trial: an efficient strategy for evaluating multiple treatments. JAMA 313:1619–20 [Google Scholar]
  57. Saville BR, Berry SM. 57.  2016. Efficiencies of platform clinical trials: a vision of the future. Clin. Trials. 13:358–66 [Google Scholar]
  58. Redig AJ, Janne PA. 58.  2015. Basket trials and the evolution of clinical trial design in an era of genomic medicine. J. Clin. Oncol. 33:975–77 [Google Scholar]
  59. Wang Y, Bhattaram AV, Jadhav PR, Lesko LJ, Madabushi R. 59.  et al. 2008. Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004–2006. J. Clin. Pharmacol. 48:146–56 [Google Scholar]
  60. 60. FDA (US Food Drug Adm.). 2009. Guidance for industry: end-of-phase 2A meetings Guid. Doc. FDA Silver Spring, MD:
  61. 61. FDA (US Food Drug Adm.). 2016. Chronic hepatitis C virus infection: developing direct-acting antiviral drugs for treatment: guidance for industry Guid. Doc. FDA Silver Spring, MD:
  62. 62. IPCS (Int. Prog. Chem. Saf.), WHO (World Health Organ.). 2010. Characterization and application of physiologically based pharmacokinetic models in risk assessment Harmon. Proj. Doc. No. 9 WHO Geneva:
/content/journals/10.1146/annurev-pharmtox-010715-103429
Loading
/content/journals/10.1146/annurev-pharmtox-010715-103429
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error