The evolution of drug-resistant malaria: the role of drug elimination half-life
This paper seeks to define and quantify the influence of drug elimination half-life on the evolution of antimalarial drug resistance. There are assumed to be three general classes of susceptibility of the malaria parasite Plasmodium falciparum to a drug: Res0, the original, susceptible wildtype; Res...
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| Published in: | Philosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 357; no. 1420; p. 505 |
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29.04.2002
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| ISSN: | 0962-8436 |
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| Abstract | This paper seeks to define and quantify the influence of drug elimination half-life on the evolution of antimalarial drug resistance. There are assumed to be three general classes of susceptibility of the malaria parasite Plasmodium falciparum to a drug: Res0, the original, susceptible wildtype; Res1, a group of intermediate levels of susceptibility that are more tolerant of the drug but still cleared by treatment; and Res2, which is completely resistant to the drug. Res1 and Res2 resistance both evolve much faster if the antimalarial drug has a long half-life. We show that previous models have significantly underestimated the rate of evolution of Res2 resistance by omitting the effects of drug half-life. The methodology has been extended to investigate (i) the effects of using drugs in combination, particularly when the components have differing half-lives, and (ii) the specific example of the development of resistance to the antimalarial pyrimethamine-sulphadoxine. An important detail of the model is the development of drug resistance in two separate phases. In phase A, Res1 is spreading and replacing the original sensitive forms while Res2 remains at a low level. Phase B starts once parasites are selected that can escape drug action (Res1 genotypes with borderline chemosensitivity, and Res2): these parasites are rapidly selected, a process that leads to widespread clinical failure. Drug treatment is clinically successful during phase A, and health workers may be unaware of the substantial changes in parasite population genetic structure that predicate the onset of phase B. Surveillance programs are essential, following the introduction of a new drug, to monitor effectively changes in treatment efficacy and thus provide advance warning of drug failure. The model is also applicable to the evolution of antibiotic resistance in bacteria: in particular, the need for these models to incorporate drug pharmacokinetics to avoid potentially large errors in their predictions. |
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| AbstractList | This paper seeks to define and quantify the influence of drug elimination half-life on the evolution of antimalarial drug resistance. There are assumed to be three general classes of susceptibility of the malaria parasite Plasmodium falciparum to a drug: Res0, the original, susceptible wildtype; Res1, a group of intermediate levels of susceptibility that are more tolerant of the drug but still cleared by treatment; and Res2, which is completely resistant to the drug. Res1 and Res2 resistance both evolve much faster if the antimalarial drug has a long half-life. We show that previous models have significantly underestimated the rate of evolution of Res2 resistance by omitting the effects of drug half-life. The methodology has been extended to investigate (i) the effects of using drugs in combination, particularly when the components have differing half-lives, and (ii) the specific example of the development of resistance to the antimalarial pyrimethamine-sulphadoxine. An important detail of the model is the development of drug resistance in two separate phases. In phase A, Res1 is spreading and replacing the original sensitive forms while Res2 remains at a low level. Phase B starts once parasites are selected that can escape drug action (Res1 genotypes with borderline chemosensitivity, and Res2): these parasites are rapidly selected, a process that leads to widespread clinical failure. Drug treatment is clinically successful during phase A, and health workers may be unaware of the substantial changes in parasite population genetic structure that predicate the onset of phase B. Surveillance programs are essential, following the introduction of a new drug, to monitor effectively changes in treatment efficacy and thus provide advance warning of drug failure. The model is also applicable to the evolution of antibiotic resistance in bacteria: in particular, the need for these models to incorporate drug pharmacokinetics to avoid potentially large errors in their predictions. This paper seeks to define and quantify the influence of drug elimination half-life on the evolution of antimalarial drug resistance. There are assumed to be three general classes of susceptibility of the malaria parasite Plasmodium falciparum to a drug: Res0, the original, susceptible wildtype; Res1, a group of intermediate levels of susceptibility that are more tolerant of the drug but still cleared by treatment; and Res2, which is completely resistant to the drug. Res1 and Res2 resistance both evolve much faster if the antimalarial drug has a long half-life. We show that previous models have significantly underestimated the rate of evolution of Res2 resistance by omitting the effects of drug half-life. The methodology has been extended to investigate (i) the effects of using drugs in combination, particularly when the components have differing half-lives, and (ii) the specific example of the development of resistance to the antimalarial pyrimethamine-sulphadoxine. An important detail of the model is the development of drug resistance in two separate phases. In phase A, Res1 is spreading and replacing the original sensitive forms while Res2 remains at a low level. Phase B starts once parasites are selected that can escape drug action (Res1 genotypes with borderline chemosensitivity, and Res2): these parasites are rapidly selected, a process that leads to widespread clinical failure. Drug treatment is clinically successful during phase A, and health workers may be unaware of the substantial changes in parasite population genetic structure that predicate the onset of phase B. Surveillance programs are essential, following the introduction of a new drug, to monitor effectively changes in treatment efficacy and thus provide advance warning of drug failure. The model is also applicable to the evolution of antibiotic resistance in bacteria: in particular, the need for these models to incorporate drug pharmacokinetics to avoid potentially large errors in their predictions.This paper seeks to define and quantify the influence of drug elimination half-life on the evolution of antimalarial drug resistance. There are assumed to be three general classes of susceptibility of the malaria parasite Plasmodium falciparum to a drug: Res0, the original, susceptible wildtype; Res1, a group of intermediate levels of susceptibility that are more tolerant of the drug but still cleared by treatment; and Res2, which is completely resistant to the drug. Res1 and Res2 resistance both evolve much faster if the antimalarial drug has a long half-life. We show that previous models have significantly underestimated the rate of evolution of Res2 resistance by omitting the effects of drug half-life. The methodology has been extended to investigate (i) the effects of using drugs in combination, particularly when the components have differing half-lives, and (ii) the specific example of the development of resistance to the antimalarial pyrimethamine-sulphadoxine. An important detail of the model is the development of drug resistance in two separate phases. In phase A, Res1 is spreading and replacing the original sensitive forms while Res2 remains at a low level. Phase B starts once parasites are selected that can escape drug action (Res1 genotypes with borderline chemosensitivity, and Res2): these parasites are rapidly selected, a process that leads to widespread clinical failure. Drug treatment is clinically successful during phase A, and health workers may be unaware of the substantial changes in parasite population genetic structure that predicate the onset of phase B. Surveillance programs are essential, following the introduction of a new drug, to monitor effectively changes in treatment efficacy and thus provide advance warning of drug failure. The model is also applicable to the evolution of antibiotic resistance in bacteria: in particular, the need for these models to incorporate drug pharmacokinetics to avoid potentially large errors in their predictions. |
| Author | White, Nicholas J Hastings, Ian M Watkins, William M |
| Author_xml | – sequence: 1 givenname: Ian M surname: Hastings fullname: Hastings, Ian M email: hastings@liverpool.ac.uk organization: Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK. hastings@liverpool.ac.uk – sequence: 2 givenname: William M surname: Watkins fullname: Watkins, William M – sequence: 3 givenname: Nicholas J surname: White fullname: White, Nicholas J |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/12028788$$D View this record in MEDLINE/PubMed |
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| References_xml | – reference: 2290858 - Pharmacol Ther. 1990;47(3):499-508 – reference: 9088432 - Acta Trop. 1997 Feb;63(2-3):185-9 – reference: 15463463 - Parasitol Today. 1991 May;7(5):120-3 – reference: 10722502 - Antimicrob Agents Chemother. 2000 Apr;44(4):991-6 – reference: 9021193 - Antimicrob Agents Chemother. 1997 Feb;41(2):363-73 – reference: 2884288 - J Pharm Pharmacol. 1987 Apr;39(4):261-5 – reference: 9449279 - Antimicrob Agents Chemother. 1998 Jan;42(1):164-9 – reference: 9061961 - Proc Biol Sci. 1997 Jan 22;264(1378):61-7 – reference: 15275291 - Parasitol Today. 1996 Oct;12(10):399-401 – reference: 17092790 - Drug Resist Updat. 1998 Mar;1(1):3-9 – reference: 10837185 - J Infect Dis. 2000 Jun;181(6):2023-8 – reference: 10900482 - Parasitol Today. 2000 Aug;16(8):340-7 – reference: 2091335 - Trans R Soc Trop Med Hyg. 1990 Jul-Aug;84(4):492-5 – reference: 8465404 - Trans R Soc Trop Med Hyg. 1993 Jan-Feb;87(1):75-8 – reference: 10371589 - Lancet. 1999 Jun 5;353(9168):1965-7 – reference: 15275132 - Parasitol Today. 1997 Dec;13(12):459-64 – reference: 10725901 - Parasitol Today. 2000 Apr;16(4):146-53 – reference: 10365399 - Philos Trans R Soc Lond B Biol Sci. 1999 Apr 29;354(1384):739-49 – reference: 10437867 - Lancet. 1999 Jul 31;354(9176):378-85 – reference: 3603638 - Trans R Soc Trop Med Hyg. 1986;80(6):889-92 – reference: 10190169 - Parasitology. 1997 Aug;115 ( Pt 2):133-41 – reference: 8560531 - Trans R Soc Trop Med Hyg. 1995 Sep-Oct;89(5):523-7 – reference: 11037785 - Am J Trop Med Hyg. 2000 Mar;62(3):396-401 – reference: 1683034 - Trans R Soc Trop Med Hyg. 1991 May-Jun;85(3):349-55 – reference: 10163571 - Pharmacoeconomics. 1996 Sep;10(3):225-38 – reference: 1685297 - Acta Trop. 1991 Aug;49(3):165-71 – reference: 2757894 - Br J Clin Pharmacol. 1989 Jun;27(6):781-7 – reference: 8951191 - Br J Clin Pharmacol. 1996 Nov;42(5):599-604 – reference: 9395372 - J Infect Dis. 1997 Dec;176(6):1590-6 – reference: 9769862 - C R Acad Sci III. 1998 Aug;321(8):689-97 – reference: 9778442 - J Theor Biol. 1998 Oct 7;194(3):313-39 – reference: 10326095 - Trans R Soc Trop Med Hyg. 1998 Nov-Dec;92(6):580-5 – reference: 10813475 - Am J Trop Med Hyg. 2000 Feb;62(2):210-6 – reference: 17040817 - Parasitol Today. 1998 Sep;14(9):360-4 – reference: 10516785 - Bull World Health Organ. 1999;77(8):624-40 |
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| SubjectTerms | Animals Anti-Bacterial Agents - pharmacokinetics Anti-Bacterial Agents - pharmacology Antimalarials - pharmacokinetics Antimalarials - pharmacology Biological Evolution Drug Combinations Drug Resistance - genetics Half-Life Humans Malaria - drug therapy Malaria - parasitology Malaria - prevention & control Plasmodium falciparum - drug effects Plasmodium falciparum - enzymology Plasmodium falciparum - genetics Tetrahydrofolate Dehydrogenase - genetics |
| Title | The evolution of drug-resistant malaria: the role of drug elimination half-life |
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