Selection of Drug Combinations for Resistant Malaria Dennis E. Kyle, PhD Professor University of South Florida
Current Issues with ACTs Artemisinin derivative combined with an existing drug Existing drug = Existing resistance Empirical selection of partner drugs Recrudescence Pharmacokinetics/Pharmacodynamics Matched or unmatched? ACT = Antimalarial Combination Therapy
Agenda Artemisinin resistance and recrudescence Methods to identify and evaluate combinations What is the way forward?
Duration of Antimalarial Activity Following a 6 Hr Drug Exposure of Young Rings to Dihydroartemisinin 10 PARASITEMIA (%) 1 0.1 Control DAR 0.2 ng/ml DAR 2.0 ng/ml DAR 20.0 ng/ml 0 24 48 72 96 120 144 168 192 TIME (Hr)
Duration of Antimalarial Activity Following a 6 Hr Drug Exposure of Young Rings to Quinine 10 PARASITEMIA (%) 1 Control QUIN 100 ng/ml QUIN 1000 ng/ml 0.1 0 24 48 72 96 120 144 168 192 TIME (Hr)
A B C D E F G H I J K L M N O P Q R S T Figure 6-8: Effect of drug on rings (A-N) and trophozoites (O-T) of P. falciparum in vitro. Synchronous cultures of ring stage parasites (A) were exposed to compound C (100 nm) for 6 hr, washed three times, and placed into culture. Thick and thin smears were prepared every 24 hr during the study. Panels B-D =24 hr, E = 48 hr, F = 72 hr, G = 96 hr, H =120 hr, I = 144 hr, J-K = 170 hr, and L-N = 192 hr. Panels O-T present the results from experiments with trophozoites (O-P = 6 hr SHAM controls, Q = 24 hr, and R-T = 50 hr.
Exposure of schizonts to DHA (70 nm) 37% DHA Wash x3 24 hr 48 hr 63% Schizonts less susceptible to DHA Second generation dormant rings
Morphology of P. falciparum following treatment of Aotus monkeys with artemisone 10 6 13145 10 5 13137 13136 10 4 Parasites/ul 10 3 10 2 10 1 10 0 10-1 10-2 -5 0 5 10 15 20 25 30 Day of Study
10 12 TOTAL PARASITES m Artesunate + Mefloquine 10 10 10 8 DRUG CONCENTRATION n x Detection limit 10 6 A y t 1/2 β = 2 weeks 10 4 10 2 0 B B 1 WEEKS 0 1 2 3 4
TOTAL PARASITES 10 12 m Artesunate + tetracycline azithromycin chlorproguanil-dapsone 10 10 10 8 n Detection limit 10 6 10 4 t 1/2 β = < 1 day 10 2 0 B WEEKS 0 1 2 3 4
Dormant Rings are Refractory to Subsequent Drug Exposure Regimen (1 st ) Regimen (2 nd ) Dormant Rings Time to Recrud DHA - Yes 120 Hr (100 nm) DHA DHA Yes 120 Hr (100 nm) (100 nm) DHA MFQ Yes 120 Hr (100 nm) (80 or 400 nm) DHA TQ Yes 96 Hr (100 nm) (700 nm)
Selection of Optimal Combination Drug Partners for ACT These data suggest that a successful companion drug must have activity against dormant forms or have a long enough half-life to remain active in the blood when dormant forms begin to emerge and grow.
Drug Concentration (ng/ml) Discontinuous exposure to AL or QHS in vitro produces AL and QHS resistant progeny of P. falciparum 80 70 60 50 40 30 20 10 0 AL Q H S 0 100 200 300 400 500 600 700 Days Clones W2 and D6 were included from the beginning of the study, whereas TM91 C235 was introduced at the 10 ng/ml AL level (left arrow) Parasites that were adapted to grow in 80 ng/ml of AL were then transferred to pressure with a different artemisinin derivative to examine the degree of cross resistance induced. The dashed line shows the point at which drug pressure was switch from 80 ng/ml AL to QHS (right arrow)
Cross Resistance between AL and Other QHS Derivatives As AL drug pressure increased, drug susceptibility decreased to other artemisinin drugs and mefloquine, whereas parasites under AL pressure became more susceptible to chloroquine. In the W2 clone, a significant reduction in sensitivity to AL and QHS was observed when parasites became adapted to 40 ng/ml AL drug pressure and this trend continued through the 200 ng/ml AL level. Resistance Index (IC-50 AL/Parent) In Vitro Drug Susceptibility Changes During Induction of Artelinic Acid Resistance W2 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 AL10 AL20 AL30 AL40 AL50 AL80 Drug Pressure Level (ng/ml) AL QHS DHA MFQ CQ QUIN
Pfmdr1 gene amplification under artelinic acid (AL) or artemisinin (QHS) pressure in vitro W2AL W2QHS mdr1 copy number 5.00 4.00 3.00 2.00 1.00 mdr1 copy number 5.00 4.00 3.00 2.00 1.00 0.00 0 4 10 20 30 50 80 80 120 200 0.00 0 20 40 40 80 200 AL concentration, ng/ml QHS concentration, ng/ml Copy number N=2 Xaver±t*SE, CI 95% (n=5-7)
Cross Resistance to QHS Derivatives Adaptation to tolerate QHS derivatives AL (200 ng/ml) QHS (200 ng/ml) DHA (200 ng/ml) Discontinuous pressure versus continuous 10 8 Parasites exposed to DHA (100 nm) Increased to 400 nm Recrudescence after 7 days continuous exposure
Models to Evaluate Drugs and Drug Combinations In vitro drug susceptibility assays Robust, relevant drug resistance genotypes and phenotypes Standardization issues Resistance threshold issues Cidal versus static? Underestimates QHS resistance
Induction of P. falciparum Resistance to Artelinic Acid In Vitro Parasite Isolate Clone IC 50 (nm) Resistance Index IC 90 (nm) Resistance Index W2 W2.AL50 D6 D6.AL50 TM91 C235 C235.AL50 4.73 (+ 0.19) 23.30 (+ 3.95) 4.9 9.81 (+ 1.41) 34.00 (+ 3.14) 3.5 11.08 (+ 1.68) 33.72 (+ 1.64) 3.0 7.45 (+ 0.40) 51.31 (+ 1.31) 6.9 21.83 (+ 3.04) 81.26 (+ 8.67) 3.7 22.99 (+ 2.60) 53.51 (+ 1.12) 2.3
In Vitro Drug Interactions Isobolograms Qualitative indicator of synergy, additivity, or antagonism Data often over interpreted Most combinations of antimalarial drugs are additive Can be a useful indicator with clinical correlates
Interaction of Artemisinin Drugs and Mefloquine 1.4 1.4 1.4 Mefloquine (IC-50) 1.2 1.0 0.8 0.6 0.4 0.2 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Artesunate (IC-50) 113 151 155 Mefloquine (IC-50) 1.2 1.0 0.8 0.6 0.4 0.2 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Artesunate (IC-50) 81 82 Mefloquine (IC-50) 1.2 1.0 0.8 0.6 0.4 0.2 W2 263 275 341 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Dihydroartemisinin (IC-50)
ACT Drug Combinations Additive In Vitro Mefloquine plus DHA, artemisinin, or artesunate Pyronaridine plus artesunate Piperaquine plus DHA Amodiaquine plus artesunate
Interaction of Artemisinin Drugs and Methylene Blue ARTELINIC ACID 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 METHYLENE BLUE W2 WR 87 D6 PNG 1917 RCS TM91C235 KN 27 TM90C2B Synergy ARTESUNATE 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 METHYLENE BLUE PNG 1917 TM91C235 KN 27 RCS D6 W2 TM90C2B WR 87 Synergy 1.0 1.0 ARTEMISININ 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 WR 87 D6 PNG 1917 RCS TM91C235 KN 27 W2 TM90C2B Synergy DIHYDROARTEMISININ 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 WR 87 D6 CLONE PNG 1917 RCS TM91C235 KN 27 W2 CLONE TM90C2B Synergy 0.1 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 METHYLENE BLUE 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 METHYLENE BLUE
High Throughput Screen for Drug Interactions Carefully define the quantitative dose response for drug of interest (e.g., QHS) Combine QHS at IC 5 IC 10 with test substances Compare inhibition of test substance alone and in combination with subinhibitory concentrations of QHS
Reversal Phenotypes are linked to Pfcrt allelic types
METHYLENE BLUE FIC 1.0 0.8 0.6 0.4 0.2 D6 W2 TM91-C235 WR87 TM90-C2b Line of Synergy Line of Additivity 0.0 0.0 0.2 0.4 0.6 0.8 1.0 TAFENOQUINE FIC
Optimization of Artemisinin Combinations 1.2 1.2 ZN57448 1.0 0.8 0.6 W2AL 200C57 W2QHS 200C1 D6 TM91C235 TM90C2A W2 ZN57448 1.0 0.8 0.6 W2QHS 200C1 W2AL 200C57 TM90C2A TM91C235 W2 D6 0.4 0.4 0.2 0.2 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Artemisinin 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Artelinic Acid
Models for Combinations In Vivo Rodent Models See Peters et al Mechanisms of resistance may differ Metabolism differences 24 vs 44 hr life cycle Aotus Plasmodium model Schmidt, Rossan, and Obaldia Excellent clinical correlates
Recrudescence following Treatment with AS
P. falciparum:aotus Model for Drug Combinations
Way Forward Current demands require development of combinations with old drugs Proactively identify unique drug interactions Use available models, particularly Aotus, to evaluate new drugs and combinations thereof Better PK/PD required to select optimal combinations
Acknowledgements Walter Reed Army Institute of Research (WRAIR) Lucia Gerena Miriam Lopez-Sanchez H. Kyle Webster Maryanne Vahey Marty Nau Zhining Wang Armed Forces Research Institute of Medical Sciences (AFRIMS) Kosol Yonvanitchit Queensland Institute of Medical Research (QIMR) Jennifer Peters Marina Chavchich Michelle Gatton Tobias Spielmann Australian Army Malaria Institute (AMI) Qin Cheng Nanhua Chen Gorgas Memorial Laboratory Nicanor Obaldia Funding: NIH R01 AI058973 & US Military Infectious Diseases Program University of South Florida Susan Lukas Matt Tucker Azliyati Azizan Tina Mutka