Secondary Logo

Journal Logo

HIV Reports

Pharmacokinetics and Safety of Zidovudine, Lamivudine, and Lopinavir/Ritonavir in HIV-infected Children With Severe Acute Malnutrition in Sub-Saharan Africa: IMPAACT Protocol P1092

Owor, Maxensia MMed*; Tierney, Camlin PhD; Ziemba, Lauren MS; Browning, Renee MSN; Moye, John MD§; Graham, Bobbie BS; Reding, Christina MPH; Costello, Diane BS; Norman, Jennifer MS**; Wiesner, Lubbe PhD**; Hughes, Emma BS††; Whalen, Meghan E. PharmD††; Purdue, Lynette PharmD‡‡; Mmbaga, Blandina Theophil PhD§§; Kamthunzi, Portia MBBS, MSc¶¶; Kawalazira, Rachel MBBS∥∥; Nathoo, Kusum MRCP***; Bradford, Sarah MPH†††; Coletti, Anne MS†††; Aweeka, Francesca. PhD††; Musoke, Philippa PhD*,‡‡‡

Author Information
The Pediatric Infectious Disease Journal: May 2021 - Volume 40 - Issue 5 - p 446-452
doi: 10.1097/INF.0000000000003055
  • Open

Abstract

Over 90% of the world’s 1.7 million children living with HIV reside in sub-Saharan Africa,1 and severe acute malnutrition (SAM) remains one of the most common presentations of HIV in African children.2,3 Mortality among children with HIV and SAM is 3 times higher compared with children with SAM alone.4,5 Increasing access to antiretroviral therapy (ARV) for children living with HIV has improved morbidity and mortality. However, sustained control of viral replication is critical for success and dependent upon adequate ARV drug exposure that may be compromised in children with SAM.

Multiple factors influence the pharmacokinetics (PK) of drugs including, malnutrition, age, sex, and genetic variations.6 SAM has been associated with villous atrophy of the intestinal lining, reduced gastric acidity, prolonged gastric emptying time, and reduced protein binding due to low-serum albumin concentrations.6,7 These physiological changes can alter ARV absorption and metabolism. Protease inhibitors [e.g., lopinavir/ritonavir (LPV/r)] prefer an acidic environment for absorption and thus may exhibit reduced exposure in SAM children.8 In contrast, nucleoside reverse transcriptase inhibitors [e.g., zidovudine (ZDV) and lamivudine (3TC)] are acid labile and may show increased absorption in SAM children. The PK of ARVs in children with HIV and SAM has not been well characterized. This study compared steady-state PK, safety, and tolerability of ZDV, 3TC, and LPV/r in children living with HIV, with and without SAM or moderate malnutrition based on standard of care (SOC) (WHO 2013) treatment guidelines.9

MATERIALS AND METHODS

Study Design

IMPAACT P1092 was a phase IV, multicenter, open label, nonrandomized study conducted at 5 sites in 4 countries (Malawi, Tanzania, Uganda, and Zimbabwe) between October 2015 and September 2017. Study participants received ARVs according to the World Health Organization (WHO) pediatric weight band dosing guidelines.10 Abacavir (ABC) was allowed to replace ZDV in cases of ZDV intolerance or grade ≥3 hematologic toxicity based on the Division of AIDS Table for Grading Severity of Adult and Pediatric Events (version 2.0 dated November 2014).11 Participants who prematurely discontinued study treatment continued to be followed in the study.

Enrollment into nutritional cohorts was stratified by age: 6 to <18 months and 18 to <36 months to achieve a balanced distribution. Children with SAM were managed according to WHO nutritional guidelines.12 They were enrolled 10–18 days of starting nutritional rehabilitation. Non-SAM children were recruited from HIV treatment centers and enrolled within 14 days after screening.

Eligibility criteria included documented HIV-1 infection defined as a positive result from 2 samples collected at different time points. A positive HIV DNA or RNA PCR test was required. A positive serological test (HIV rapid test or ELISA) was also permitted in children above 24 months in age. Children with acute serious infections were stabilized for at least 5 days on antimicrobials. Children with SAM had to demonstrate clinical stability and improvement at enrollment. Exclusion criteria included edematous malnutrition, respiratory distress grade ≥3, and current antituberculosis therapy.

Children were grouped by nutritional status according to WHO standards in weight-for-height Z-score (WHZ) or midupper arm circumference (MUAC). A WHZ > −1 was classified as “normal” nutrition, WHZ > −2 to ≤ −1 as mild malnutrition, and WHZ < −3 or MUAC < 115 mm as severe malnutrition. Children with normal nutrition or mild malnutrition were grouped in the non-SAM cohort. Children with WHO-defined moderate malnutrition were excluded. Children were weighed to the nearest 100 g on scales calibrated daily; lengths were measured to the nearest 0.1 cm using locally built height boards. Study clinic visits occurred at weeks 1, 2, 4, 8, 12, 16, 20, 24, 36, and 48 post enrollment. All visits included nutritional assessments, medical history, and a physical examination. Hematology and Chemistry, CD4 cell count and percentage and plasma HIV-1 RNA (viral load) levels were determined at screening/entry, and weeks 12, 24, 36, and 48.

At enrollment, children initiated ZDV, 3TC, and LPV/r liquid twice daily. At each visit, drug dosing was re-evaluated and adjusted according to the child’s weight. Caregivers were given instructions on ARV administration and dose-time documentation.

Cohorts of 17 participants each were calculated to provide 80% power for a 2-sided t test with alpha of 0.05 to detect a 40% difference in mean LPV AUC0–12h between cohorts. LPV AUC0–12h coefficient of variation (CV) of 0.4 was assumed based on estimates in similarly aged children,13 and a 40% difference in AUC0–12h was considered clinically significant. Accounting for possible loss to follow-up (10%), mortality (20%), and variability in AUC0–12h (10%), a sample size of 25 children per cohort was defined.

All ethical committees of participating sites reviewed and approved the protocol. Written informed consent was obtained from caregivers of study participants. The study was registered with Clinical Trials.gov (ClinicalTrials.gov Identifier NCT0818258).

PK Sample Collection

At study weeks 1, 12, and 24, blood was collected for intensive PK sampling. Caregivers were asked to hold the child’s morning dose of ARVs before sampling. Blood samples were collected just before an observed morning dose and at 1, 2, 4, 8, and 12 hours postdose. Each time point was documented. Intensive PK sample collection was deferred if any doses were missed within the preceding 72 hours, the most recent hemoglobin was <7.5 g/dL, or the child had diarrhea at the visit. To assure PK samples were collected under steady-state conditions, every effort was made to administer doses approximately every 12 hours for the 48 hours preceding the intensive sampling period. Food intake around week 1, PK sampling was standardized to minimize any potential food effect on PK between the cohorts.

All whole blood samples were collected in Greiner-Mini K3EDTA blood collection tubes. Plasma was separated and stored at −80°C until it was shipped for analysis to the Division of Clinical Pharmacology at the University of Cape Town (UCT) in South Africa.

Drug Analysis

Plasma ZDV, 3TC, and LPV/r concentrations were determined with validated liquid chromatography tandem mass spectrometry assays developed at the UCT. Plasma samples for measuring ZDV and 3TC were processed with a liquid-liquid extraction method using 50 μL plasma and 1 mL ethyl acetate. Plasma samples for LPV were processed with a protein precipitation extraction method using 10 μL plasma with 120 μL acetonitrile. Stable isotope-labeled internal standards were used for both assays.

Isocratic chromatographic separation of ZDV and 3TC was achieved on a Higgins Clipeus C18 (150 mm × 3 mm × 5 μm) analytical column. The mobile phase consisted of 0.1% formic acid in water and 0.1% formic acid in methanol (50:50, v/v), delivered at a flow rate of 300 μL/min. Isocratic chromatography for LPV and Ritonavir (RTV) assays was achieved on a Phenomenex Luna PFP (110A, 50 mm × 2 mm × 5 μm) analytical column. The mobile phase consisted of 0.1% formic acid in water and acetonitrile (50:50, v/v) and delivered at a flow rate of 350 μL/min.

An AB Sciex API 3000 mass spectrometer was used to quantify ZDV and 3TC and operated at unit resolution in the multiple reaction monitoring (MRM) mode, monitoring the transition of the protonated molecular ions m/z 268.2 to the product ions at m/z 127.1 for ZDV, and m/z 230.1 to m/z 112.1 for 3TC. An AB Sciex API 4000 mass spectrometer was used to quantify LPV/r and operated at unit resolution in the MRM mode, monitoring the transition of the protonated molecular ions m/z 629.5 to the product ions at m/z 120.2; and m/z 721.5 to m/z 296.1 for LPV and RTV, respectively.

The assays were validated over the concentration ranges of 0.0238–6.10 μg/mL for ZDV and 3TC, 0.0195–20.0 μg/mL for LPV, and 0.00488–5.00 µg/mL for RTV. The accuracy and precision statistics of the quality controls during intra- and interbatch validation were within FDA and EMA validation criteria.14,15 The laboratory participates in the AIDS Clinical Trial Group Pharmacology Quality Control Program.16

PK and Statistical Analysis

The primary PK outcome measures were steady-state AUC0–12h and oral clearance (CL/F) for LPV, RTV, 3TC, and ZDV at study weeks 1, 12, and 24. PK parameters were calculated using a noncompartmental analysis in the software WinNonlin (v8.1). The linear up-log down trapezoidal method was used when calculating the AUC parameter. CL/F was calculated as dose/AUC0–12hr. For calculating PK parameters, the first concentration value postdose to fall below the limit of assay quantification (BLQ), was assigned a value of 1/2 BLQ, and a concentration of zero thereafter.

Participants were evaluable for analysis if they had an outcome measure at week 1 and either weeks 12 or 24. The AUC0–12h and CL/F for each study week were compared for each analyte between SAM and non-SAM cohorts using Student’s t test, assuming unequal variance. PK parameter comparisons were performed on the natural logarithmic scale and differences between cohorts were summarized using a geometric mean ratio (GMR).

The primary safety outcome measures included experiencing at least 1 new grade 3 or higher adverse event related to study treatment through week 24, or experiencing at least 1 new grade 3 or higher adverse event regardless of relationship to treatment through week 24. Adverse events were those that began or increased in grade after study entry. A Fisher’s exact test compared grade 3 or higher adverse events.

All statistical tests were 2-sided and performed using SAS 9.4 (Cary, NC). Results were considered statistically significant if the P value was less than 0.05.

RESULTS

Baseline Characteristics

Fifty-two participants, 25 in the SAM cohort and 27 in the non-SAM cohort, were enrolled. The median (25th, 75th percentile) age at entry was 19 months13 in the SAM and 18 months12 in the non-SAM cohort. SAM participants had a median (25th, 75th percentile) WHZ of −3.4 (−4.0, −3.0) while WHZ was −1.0 (−1.8, −0.1) in the non-SAM cohort (Table 1).

TABLE 1. - Baseline Characteristics
Cohort
Baseline Characteristics Severe Malnutrition (N = 25) Mild Malnutrition/Normal Nutrition (N = 27)
Nutritional cohort subgroup Severe malnutrition 25 (100%) 0 (0%)
Mild malnutrition 0 (0%) 15 (56%)
Normal nutrition 0 (0%) 12 (44%)
Age (mo) Median (Q1, Q3) 19 (13, 25) 18 (12, 25)
6 to <18 mo 11 (44%) 13 (48%)
≥18 mo 14 (56%) 14 (52%)
Country Malawi 12 (48%) 5 (19%)
Tanzania 7 (28%) 9 (33%)
Uganda 1 (4%) 1 (4%)
Zimbabwe 5 (20%) 12 (44%)
Sex Male 16 (64%) 13 (48%)
Female 9 (36%) 14 (52%)
WHO weight-for-height Z-Score Median (Q1, Q3) −3.4 (−4.0, −3.0) −1.0 (−1.8, −0.1)
Midupper arm circumference (cm) Median (Q1, Q3) 11.0 (10.4, 11.5) 13.9 (12.5, 15.5)
Log10 HIV-1 RNA (copies/mL) Median (Q1, Q3) 4.8 (4.2, 5.6) 5.6 (4.8, 6.1)
HIV-1 RNA (copies/mL, categorized) <400 2 (8%) 2 (7%)
400 to <2000 0 (0%) 0 (0%)
2000 to <10,000 3 (12%) 3 (11%)
10,000 to <20,000 3 (12%) 1 (4%)
≥20,000 17 (68%) 21 (78%)
CD4 cell percent Median(Q1,Q3) 15 (9.0, 22.6) 23 (17, 31)
Total protein g/ L Median(Q1, Q3) 70.1 (66.4, 83.4) 76.4 (73.2, 79.3)
Albumin g/L Median(Q1, Q3) 35 (31, 40) 41.8 (37, 47)

A total of 46 participants (88.5%) completed 48 weeks of study follow-up per protocol.

PK Parameters for LPV/r, 3TC, and ZDV

At least 42 participants (81%) were evaluable for PK analysis of LPV, RTV, and 3TC while, 31 (60%) participants were evaluable for ZDV analysis. Reasons for exclusion in the AUC analysis included: early study discontinuation (n = 4) or study treatment discontinuation (n = 1) before week 12, and switches from ZDV to ABC before week 12 after experiencing a grade 3 or 4 hematologic toxicity [3 (12%) in the SAM cohort and 5 (18.5%) in the non-SAM cohort].

The mean AUC0–12h or CL/F for LPV and RTV did not differ significantly by cohort at weeks 1, 12, and 24. Although not statistically significant, the SAM cohort consistently had lower LPV and RTV exposures over time (Table 2 and Figure 1A; P 0.11). Mean 3TC AUC0–12h and CL/F did not differ significantly by cohort at weeks 1 and 24 (Table 2; P 0.18). At week 12, however, the 3TC AUC0–12h was significantly lower in the SAM cohort compared with the non-SAM cohort with a GMR [95% confidence interval (CI)] of 0.60 [(0.4–1.0), P = 0.047]. For ZDV, there were no significant differences for AUC0–12h or CL/F at weeks 1 and 12 (P 0.09). However, at week 24, the SAM cohort had a significantly lower mean ZDV CL/F [GMR, 0.64; 0.5–0.8; P = 0.003] and a significantly higher AUC0–12h [GMR, 1.52; 1.2–2.0; P = 0.003] compared with the non-SAM cohort. In a sensitivity analysis, age-group adjusted results were similar.

TABLE 2. - Pharmacokinetic Primary Outcome Measures
Cohort
Severe Malnutrition Mild Malnutrition/Normal Nutrition GMR* (95% CI) of SAM†/Non-SAM‡
Analyte Outcome Measure Study Visit N Geometric Mean (95% CI) N Geometric Mean (95% CI) P
LPV AUC (µg*h/mL) 1 22 49.8 (28.5–87.2) 23 64.8 (37.6–111.9) 0.77 (0.4–1.6) 0.49
12 21 53.0 (26.1–107.5) 23 83.4 (60.4–115.0) 0.64 (0.3–1.4) 0.23
24 19 64.6 (28.3–147.5) 23 79.4 (56.8–111.0) 0.81 (0.3–2.0) 0.63
CL/F (L/h) 1 22 2.2 (1.2–3.9) 23 2.0 (1.2–3.5) 1.06 (0.5–2.3) 0.89
12 21 2.3 (1.1–4.7) 23 1.6 (1.2–2.3) 1.42 (0.7–3.1) 0.37
24 19 2.1 (0.9–4.8) 23 1.7 (1.2–2.5) 1.23 (0.5–2.9) 0.63
RTV AUC (µg*h/mL) 1 22 1.6 (1.0–2.5) 23 2.1 (1.2–3.6) 0.76 (0.4–1.5) 0.42
12 21 1.8 (1.0–3.1) 23 3.0 (2.1–4.5) 0.58 (0.3–1.1) 0.11
24 19 2.3 (1.3–4.3) 23 3.0 (2.2–4.0) 0.77 (0.4–1.5) 0.44
CL/F (L/h) 1 22 16.9 (10.5–27.2) 23 15.8 (9.2–27.2) 1.07 (0.5–2.2) 0.84
12 21 17.3 (9.6–31.0) 23 11.2 (7.6–16.6) 1.54 (0.8–3.1) 0.21
24 19 14.8 (8.1–27.2) 23 11.5 (8.4–15.7) 1.29 (0.7–2.5) 0.44
3TC AUC (µg*h/mL) 1 21 4245.0 (2959.3–6089.3) 21 5520.2 (3981.4–7653.7) 0.77 (0.5–1.2) 0.27
12 20 4365.5 (2743.6–6946.4) 21 7233.0 (5896.4–8872.6) 0.60 (0.4–1.0) 0.047
24 18 6359.0 (5221.9–7743.8) 20 5849.2 (3453.5–9907.0) 1.09 (0.6–1.9) 0.76
CL/F (L/h) 1 21 8.7 (6.0–12.7) 21 8.4 (6.2–11.5) 1.03 (0.6–1.7) 0.89
12 20 9.5 (5.9–15.4) 21 6.8 (5.7–8.1) 1.40 (0.8–2.3) 0.18
24 18 7.5 (6.2–9.0) 20 8.8 (5.3–14.7) 0.85 (0.5–1.4) 0.53
ZDV AUC (µg*h/mL) 1 15 2261.0 (1652.0–3094.4) 16 1774.0 (1079.6–2915.1) 1.27 (0.7–2.2) 0.39
12 12 1826.0 (977.8–3410.0) 16 1335.7 (758.5–2352.2) 1.37 (0.6–3.0) 0.43
24 13 2449.7 (2053.5–2922.5) 15 1609.3 (1306.7–1981.9) 1.52 (1.2–2.0) 0.003
CL/F (L/h) 1 15 34.8 (24.4–49.5) 16 58.3 (34.8–97.9) 0.60 (0.3–1.1) 0.090
12 12 48.8 (24.8–95.8) 16 81.8 (44.9–148.9) 0.60 (0.3–1.4) 0.23
24 13 40.8 (33.0–50.4) 15 64.0 (51.7–79.1) 0.64 (0.5–0.8) 0.003
*Geometric mean ratio.
†Severe acute malnutrition.
‡Non severe acute malnutrition (mild malnutrition and normal nutrition)

FIGURE 1.
FIGURE 1.:
A, Plasma concentration—time profile of LPV and RTV in children with severe malnutrition (blue) and mild malnutrition/normal nutrition (red) for study weeks 1, 12, and 24. Data are reported as median (25th and 75th percentile). B, Plasma concentration—time profile of 3TC and ZDV in children with severe malnutrition (blue) and mild malnutrition/normal nutrition (red) for study weeks 1, 12, and 24. Data are reported as median (25th and 75th percentile). 3TC indicates lamivudine; LPV, lopinavir; RTV, ritonavir; ZDV, zidovudine.

A repeated measures analysis for each analyte for the AUC and CL/F across the 3 intensive PK weeks among the evaluable participants showed there was no significant evidence that the mean difference between cohorts in AUC or CL/F changed over time (P 0.35).

Safety and Tolerability

Overall, 23 (44.2%) participants experienced at least 1 new grade ≧3 adverse event by week 24; this did not differ significantly between cohorts: 13 (52%) [95% CI (31.3%–72.2%)] in the SAM and 10 (37%) [(19.4%–57.6%)] in the non-SAM cohort (P = 0.40). Similarly, there was no significant difference between cohorts for grade ≧3 adverse events that were at least probably related to study treatment: 6 (24%) [95% CI (9.4%–45.1%)] in SAM and 7 (25.9%) (11.1%–46.3%) in the non-SAM cohort (P > 0.999). The most common nonmalnutrition events were anemia (n = 10), pneumonia or bacterial pneumonia (n = 5), decreased hemoglobin (n = 11), and decreased neutrophil count (n = 6). Three children in the SAM cohort died (2 due to gastroenteritis at weeks 1 and 20, and 1 with probable pneumonia at week 19).

Tolerability of study treatment was assessed as experiencing vomiting or diarrhea through week 24 and permanently discontinuing all study treatment by week 24. Among those who experienced vomiting, 7 (100%) in the SAM cohort were of mild grade. In the non-SAM cohort, 4 (80.0%) were of mild grade and 1 (20.0%) of moderate grade. Four of 9 (44.4%) in the SAM cohort and 2 of 3 (66.7%) in the non-SAM cohort had a moderate grade diarrhea event through week 24. Eight (15.4%) participants permanently discontinued study treatment by week 24: 5 (20%) SAM children [due to deaths unrelated to study treatment,3 edematous malnutrition,1 and taking disallowed medication1] and 3 (11%) non-SAM children [due to caregiver consent withdrawal,1 inability to attend clinic,1 and lost to follow-up1].

Viral Load and CD4 Cell Percent

Viral load suppression (≤400 copies/mL) did not differ significantly between cohorts at baseline (8.0% [95% CI (1.0%–26.0%)] in SAM vs. 7.4% (0.9%–24.3%) in non-SAM, P > 0.999) or week 12 [34.8% (16.4%–57.3%) in SAM vs. 58.3% (36.6%–77.9%) in non-SAM, P = 0.15]. At both weeks 24 and 48, viral load was ≤400 copies/mL in 50.0% (28.2%–71.8%) of SAM versus 78.3% (56.3%–92.5%) of non-SAM children (P = 0.065).

At baseline, mean (95% CI) CD4 cell percent was 15.5 (11.9–19.2) in the SAM and 24.5 (20.0–29.0) in the non-SAM cohort. No significant cohort differences of change in CD4 percent from baseline were observed at weeks 12, 24, and 36 (P 0.18). At week 48, the SAM cohort had a significantly higher mean (95% CI) change in CD4 cell percent from baseline [12.7 (8.3–17.1)] than the non-SAM group [6.7 (4.2–9.1); P = 0.018]. At week 48, the mean (95% CI) CD4 percent was 28.9 (23.2–34.7) in the SAM cohort and 29.0 (25.3–32.8) in the non-SAM cohort.

DISCUSSION

This study showed that SAM and non-SAM children who were dosed according to WHO weight bands had highly variable AUC0–12h and CL/F, particularly for LPV and RTV. On average, each drug’s PK parameters did not differ significantly by cohort or time period. While our study did not find a significant difference in mean LPV/r exposure between the 2 cohorts, the SAM cohort had a trend toward lower exposures. This trend was consistent with Bartelink et al who previously reported lower LPV exposure in Ugandan children with a higher prevalence of malnutrition in comparison to European children with a low prevalence of malnutrition.17 Our CL/F values were also comparable with those previously reported in children from both resource rich and poor countries.17,18

For 3TC, the AUC0–12h and CL/F did not differ significantly between cohorts at week 1 or 24. At week 12, SAM children had a significantly lower AUC0–12h than non-SAM children (P = 0.047). The finding given was not consistent across study weeks, and it may be a result of other factors, such as adherence, rather than nutritional differences. Our AUC0–12h and CL/F values were similar to those reported by Kasirye et al and Kulkanya et al for children using liquid formulations.19,20

At week 24, the SAM cohort had a significantly higher mean ZDV AUC0–12h (P = 0.003). While not significantly different, SAM children also had higher AUC0–12h values at weeks 1 and 12. The exposure values were comparable to those reported by Kulkanya et al and within the range of values previously reported in adults.20 Fillekes et al found that age and lower weight were both independently associated with higher ZDV exposures.21 We tested for an age effect and found age did not appear to affect the primary PK parameters in our study. Therefore, higher exposure across study weeks among SAM children could be due to weight differences between cohorts. ZDV is an acid-labile compound and malnutrition can lead to increased gastric pH resulting in increased absorption, which might explain our findings.22 Given the observed ARV exposures in SAM children, the differences in virologic control between the cohorts, although not significant, needs further exploration. One plausible hypothesis is that SAM children have different profile of immune activation.

There were no apparent safety concerns or differences in prevalence of drug-related adverse events between cohorts. More SAM children experienced diarrhea on study. This was not unusual since SAM is associated with coinfections and metabolic complications, which may lead to vomiting and diarrhea, or death.

Strengths of this study included the relatively large numbers of evaluable children in both cohorts for PK parameters. All children received liquid formulation and were of similar ages. In addition, this study recruited participants from 4 countries in eastern and southern Africa, increasing the generalizability of results. Study limitations included children in the SAM cohort receiving nutritional rehabilitation for 2 weeks and showing clinical improvement before study enrollment and during the study. Therefore, improvements to their nutritional status may have reduced differences between the 2 groups. SAM participants also improved after baseline: median (25th, 75th percentile) change in WHZ from baseline to 24 weeks was 2.6 (1.2–3.2) in the SAM cohort and 0.2 (−0.4 to 0.6) in the non-SAM cohort. Given this study did not observe all ARV doses, potential nonadherence could have obscured differences between cohorts.23 Maternal ARV exposure during breast-feeding may have impacted pharmacokinetic results, albeit the number of potentially exposed infants was small.

In conclusion, we found children with and without SAM had similar AUCs following WHO weight band dosing of ZDV, 3TC, and LPV/r and these doses appeared safe for children with SAM. These PK and safety findings indicate that the current WHO syrup formulation doses provide adequate exposure in children with SAM.

TABLE 3. - Grade 3 or Higher Adverse Events through Study Week 24 among Participants Evaluable for the Intensive PK Analysis
Cohort
Severe Malnutrition Mild Malnutrition/Normal Nutrition
Outcome Experienced At Least One Grade 3 or Higher Adverse Event through Study Week 24 n (%) 95% CI n (%) 95% CI P
All events Yes 13 (52.0%) (31.3%–72.2%) 10 (37.0%) (19.4%– 57.6%) 0.40
No 12 (48.0%) 17 (63.0%)
Events related to study treatment Yes 6 (24.0%) (9.4%–45.1%) 7 (25.9%) (11.1%–46.3%) >0.999
No 19 (76.0%) 20 (74.1%)

ACKNOWLEDGMENTS

We gratefully acknowledge the contributions of the site investigators and staff who conducted the IMPAACT P1092 study:

ZIMBABWE. University of Zimbabwe College of Health Sciences-Clinical Trials Research Centre: Mutsa Bwakura-Dangarembizi, MSc Clin Epi; Tapiwa G. Mbengeranwa, MBA; Tsungai P. Mhembere, MPH; Bernadette Malunda, Honors in Biological Sciences. TANZANIA. Kilimanjaro Christian Medical Centre: James Ngocho, MD, MSc; Aisa Shayo MD, MMED; Boniface Njau, MPH; Winfrida Shirima, BSc. MALAWI. University of North Carolina Project-Malawi: Noel Mumba, Diploma Clinical Medicine; Tionge Kamvaunamwali, NMT, BSPH; Wanangwa Nyirenda, B.Soc.Sc; Wilberforce Mhango, BA, Diploma Pharmacy. College of Medicine-Johns Hopkins Research Project: Macpherson Mallewa, MBBS, MCRP, PhD; Dingase Dula, MBBS; Sufia Dadabhai, MHS, PhD; Taha Taha, MD, PhD. UGANDA. MU-JHU Research Collaboration: Phionah Kibalama, MBChB, MSc PH; Annette Miwanda; Linda Barlow-Mosha, MD, MPH; Irene Lubega, MBChB, MMED. IMPAACT Laboratory Center: Carolyn Yanavich, PhD, CCRP; Nancy Tustin, MLT (ASCP) (HEW). IMPAACT Data Management Center: Frederic Bone; Kyle Lambert.

REFERENCES

1. UNAIDS. UNAIDS data 2019 (updated 2018 data). 2019. Available at: https://www.unaids.org › resources › documents › 2019 › 2019-UNAIDS-data. Accessed November 16, 2019.
2. Cross Continents Collaboration for Kids (3Cs4kids) Analysis and Writing Committee. Markers for predicting mortality in untreated HIV-infected children in resource-limited settings: a meta-analysis. AIDS. 2008; 22:97–105.
3. Walker AS, Mulenga V, Sinyinza F, et al.; CHAP Trial Team. Determinants of survival without antiretroviral therapy after infancy in HIV-1-infected Zambian children in the CHAP Trial. J Acquir Immune Defic Syndr. 2006; 42:637–645.
4. Fergusson P, Tomkins A. HIV prevalence and mortality among children undergoing treatment for severe acute malnutrition in sub-Saharan Africa: a systematic review and meta-analysis. Trans R Soc Trop Med Hyg. 2009; 103:541–548.
5. Muenchhoff M, Healy M, Singh R, et al. Malnutrition in HIV-infected children is an indicator of severe disease with an impaired response to antiretroviral therapy. AIDS Res Hum Retroviruses. 2018; 34:46–55.
6. Krishnaswamy K. Drug metabolism and pharmacokinetics in malnourished children. Clin Pharmacokinet. 1989; 17suppl 168–88.
7. Gilman RH, Partanen R, Brown KH, et al. Decreased gastric acid secretion and bacterial colonization of the stomach in severely malnourished Bangladeshi children. Gastroenterology. 1988; 94:1308–1314.
8. Falcon RW, Kakuda TN. Drug interactions between HIV protease inhibitors and acid-reducing agents. Clin Pharmacokinet. 2008; 47:75–89.
9. World Health Organization. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. 2013. Available at: https://www.who.int/hiv/pub/guidelines/arv2013/en. Accessed June 16, 2020.
10. World Health Organization. Antiretroviral Therapy for HIV Infection in Infants and Children: Recommendations for a Public Health Approach 2010 Revision. 2010, World Health Organization; 206.
11. Division of AIDS. DAIDS AE Grading table Version 2.0 dated November 2014. 2014. Available at: https:rsc.niaid.nih.gov/sites/default/files/daids-ae-grading-table-v2-nov2014.pdf. Accessed November 16, 2019.
12. World Health Organization. Guideline: Updates on the management of severe acute malnutrition in infants and children. 2013.World Health Organization
13. Capparelli E, Pinto J, Robbins B, et al. Lopinavir pharmacokinetic (PK) maturational changes and variability in HIV-infected infants beginning Kaletra (LPV/r) therapy at <6 weeks (WK) of age. 2008. In: Conference on Retroviruses and Opportunistic Infections, Boston, 2008
14. Food and Drug Administration, Center for Drug Evaluation and Research. Guidance for Industry: Bioanalytical Method Validation. 2013. FDA. Available at: http://www.bioagilytix.com/wp-content/uploads/2016/02/FDA-Bioanalytical-Method-Validation-Draft-Guidance-2013.pdf. Accessed November 16, 2019.
15. European Medicines Agency. Guideline on Bioanalytical Method Validation. 2011. EMA. Available at: http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2011/08/WC500109686.pdf. Accessed November 16, 2019.
16. DiFrancesco R, Rosenkranz SL, Taylor CR, et al. Clinical pharmacology quality assurance program: models for longitudinal analysis of antiretroviral proficiency testing for international laboratories. Ther Drug Monit. 2013; 35:631–642.
17. Bartelink IH, Savic RM, Dorsey G, et al. The effect of malnutrition on the pharmacokinetics and virologic outcomes of lopinavir, efavirenz and nevirapine in food insecure HIV-infected children in Tororo, Uganda. Pediatr Infect Dis J. 2015; 34:e63–e70.
18. Yang J, Nikanjam M, Best BM, et al. Population pharmacokinetics of lopinavir/ritonavir: changes across formulations and human development from infancy through adulthood. J Clin Pharmacol. 2018; 58:1604–1617.
19. Kasirye P, Kendall L, Adkison KK, et al.; ARROW Trial Team. Pharmacokinetics of antiretroviral drug varies with formulation in the target population of children with HIV-1. Clin Pharmacol Ther. 2012; 91:272–280.
20. Chokephaibulkit K, Cressey TR, Capparelli E, et al.; IMPAACT P1069 Team. Pharmacokinetics and safety of a new paediatric fixed-dose combination of zidovudine/lamivudine/nevirapine in HIV-infected children. Antivir Ther. 2011; 16:1287–1295.
21. Fillekes Q, Kendall L, Kitaka S, et al.; ARROW Trial Team. Pharmacokinetics of zidovudine dosed twice daily according to World Health Organization weight bands in Ugandan HIV-infected children. Pediatr Infect Dis J. 2014; 33:495–498.
22. Charman WN, Porter CJ, Mithani S, et al. Physiochemical and physiological mechanisms for the effects of food on drug absorption: the role of lipids and pH. J Pharm Sci. 1997; 86:269–282.
23. Biressaw S, Abegaz WE, Abebe M, et al. Adherence to antiretroviral therapy and associated factors among HIV infected children in Ethiopia: unannounced home-based pill count versus caregivers’ report. BMC Pediatr. 2013; 13:132.
Keywords:

pharmacokinetics; HIV; severe acute malnutrition; children; lopinavir/ritonavir

Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.