Despite the advancement of antiretroviral therapy (ART) for the treatment of human immunodeficiency virus (HIV), drug-drug interactions (DDIs) remain a relevant clinical issue for people living with HIV receiving ART. Antiretroviral (ARV) drugs can be victims and perpetrators of DDIs, and a detailed investigation during drug discovery and development is required to determine whether dose adjustments are necessary or coadministrations are contraindicated. Maintaining therapeutic ARV plasma concentrations is essential for successful ART, and changes resulting from potential DDIs could lead to toxicity, treatment failure, or the emergence of ARV-resistant HIV. The challenges surrounding DDI management are complex in special populations of people living with HIV,and often lack evidence-based guidance as a result of their underrepresentation in clinical investigations.Specifically, the prevalence of hepatic and renal impairment in people living with HIV are between five and 10 times greater than in people who are HIV-negative, with each condition constituting approximately 15% of non-AIDS-related mortality. Therapeutic strategies tend to revolve around the treatment of risk factors that lead to hepatic and renal impairment, such as hepatitis C, hepatitis B, hypertension, hyperlipidemia, and diabetes. These strategies result in a diverse range of potential DDIs with ART. The purpose of this review was 2-fold. First, to summarize current pharmacokinetic DDIs and their mechanisms between ARVs and co-medications used for the prevention and treatment of hepatic and renal impairment in people living with HIV. Second, to identify existing knowledge gaps surrounding DDIs related to these special populations and suggest areas and techniques to focus upon in future research efforts.
The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18–60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35%–60%) and the plasma concentrations increased (170%–400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.
The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18-60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35% - 60%) and the plasma concentrations increased (170% - 400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.
Aim Long-acting cabotegravir and rilpivirine have been approved to manage HIV in adults, but data regarding safe use in pregnancy are limited. Physiologically-based pharmacokinetic modelling (PBPK) can predict drug disposition in complex populations. Approved dosing regimens were simulated in pregnancy to explore if Ctrough was maintained above target concentrations (664 ng/ml and 50 ng/ml respectively). Methods An adult PBPK model was developed and validated using clinical data of cabotegravir and rilpivirine in non-pregnant adults. This was modified by incorporating pregnancy-induced metabolic and physiological changes. The pregnancy PBPK model was validated with data on oral rilpivirine and raltegravir (UGT1A1 probe substrate) in pregnancy. Acceptance criteria for both adult and pregnancy models was absolute average-fold error (AAFE) < 2 between clinical and simulated values. The pregnancy PBPK model was used to simulate 12 weeks’ disposition of monthly and bimonthly dosing of long-acting cabotegravir and rilpivirine, initiated at different trimesters. Results Models were successfully qualified with all AAFE values below 2. Predicted Ctrough at week 12 for both monthly and bimonthly long-acting cabotegravir was above 664 ng/ml throughout pregnancy. Similarly, predicted Ctrough at week 12 for monthly long-acting rilpivirine was above 50 ng/ml throughout pregnancy. However, for bimonthly rilpivirine administration, predicted Ctrough at week 12 were <50 ng/ml in 1, 0.5, and 2.3% of the pregnant population when initiated in first, second, and third trimester respectively. Conclusion Model predictions suggest monthly and bimonthly long-acting cabotegravir is likely to maintain antiviral efficacy throughout pregnancy. However, bimonthly long-acting rilpivirine requires careful clinical evaluation in pregnancy.
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