4.4 Article

Optimizing the programmatic deployment of the anti-malarials artemether-lumefantrine and dihydroartemisinin-piperaquine using pharmacological modelling

Journal

MALARIA JOURNAL
Volume 13, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/1475-2875-13-138

Keywords

Falciparum malaria; Anti-malarials; Artemisinins; Dosing regimen; Mathematical model; Pharmacokinetics; Piperaquine; Lumefantrine; Drug resistance; Patient adherence; Medication adherence

Funding

  1. Medical Research Council [G1100522, GO0501401]
  2. European & Developing Countries Clinical Trials Partnership [IP-07-31060-003]
  3. Bill and Melinda Gates Foundation [37999.01]
  4. MRC [G1100522, MR/L022508/1] Funding Source: UKRI
  5. Medical Research Council [MR/L022508/1, G1100522] Funding Source: researchfish

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Background: Successful programmatic use of anti-malarials faces challenges that are not covered by standard drug development processes. The development of appropriate pragmatic dosing regimens for low-resource settings or community-based use is not formally regulated, even though these may alter factors which can substantially affect individual patient and population level outcome, such as drug exposure, patient adherence and the spread of drug resistance and can affect a drug's reputation and its eventual therapeutic lifespan. Methods: An in silico pharmacological model of anti-malarial drug treatment with the pharmacokinetic/pharmacodynamic profiles of artemether-lumefantrine (AM-LF, Coartem (R)) and dihydroartemisinin-piperaquine (DHA-PPQ, Eurartesim (R)) was constructed to assess the potential impact of programmatic factors, including regionally optimized, age-based dosing regimens, poor patient adherence, food effects and drug resistance on treatment outcome at population level, and compared both drugs' susceptibility to these factors. Results: Compared with DHA-PPQ, therapeutic effectiveness of AM-LF seems more robust to factors affecting drug exposure, such as age- instead of weight-based dosing or poor adherence. The model highlights the sub-optimally low ratio of DHA:PPQ which, in combination with the narrow therapeutic dose range of PPQ compared to DHA that drives the weight or age cut-offs, leaves DHA at a high risk of under-dosing. Conclusion: Pharmacological modelling of real-life scenarios can provide valuable supportive data and highlight modifiable determinants of therapeutic effectiveness that can help optimize the deployment of anti-malarials in control programmes.

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