| Autor: |
Ben Andagalu, Pinyi Lu, Irene Onyango, Elke Bergmann-Leitner, Ruth Wasuna, Geoffrey Odhiambo, Lorna J. Chebon-Bore, Luicer A. Ingasia, Dennis W. Juma, Benjamin Opot, Agnes Cheruiyot, Redemptah Yeda, Charles Okudo, Raphael Okoth, Gladys Chemwor, Joseph Campo, Anders Wallqvist, Hoseah M. Akala, Daniel Ochiel, Bernhards Ogutu, Sidhartha Chaudhury, Edwin Kamau |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Frontiers in Medicine. 9 |
| ISSN: |
2296-858X |
| Popis: |
The impact of pre-existing immunity on the efficacy of artemisinin combination therapy is largely unknown. We performed in-depth profiling of serological responses in a therapeutic efficacy study [comparing artesunate-mefloquine (ASMQ) and artemether-lumefantrine (AL)] using a proteomic microarray. Responses to over 200 Plasmodium antigens were significantly associated with ASMQ treatment outcome but not AL. We used machine learning to develop predictive models of treatment outcome based on the immunoprofile data. The models predict treatment outcome for ASMQ with high (72–85%) accuracy, but could not predict treatment outcome for AL. This divergent treatment outcome suggests that humoral immunity may synergize with the longer mefloquine half-life to provide a prophylactic effect at 28–42 days post-treatment, which was further supported by simulated pharmacokinetic profiling. Our computational approach and modeling revealed the synergistic effect of pre-existing immunity in patients with drug combination that has an extended efficacy on providing long term treatment efficacy of ASMQ. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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