Hydroxychloroquine (HCQ) is a promising candidate for Coronavirus disease of 2019 (COVID-19) treatment. The optimal dosing of HCQ is unknown. Our goal was to integrate historic and emerging pharmacological and toxicity data to understand safe and efficacious HCQ dosing strategies for COVID-19 treatment. The data sources included were (i) longitudinal clinical, pharmacokinetic (PK), and virologic data from patients with severe acute respiratory syndrome-2 (SARS-CoV-2) infection who received HCQ with or without azithromycin (n = 116), (ii) in vitro viral replication data and SARS-CoV-2 viral load inhibition by HCQ, (iii) a population PK model of HCQ, and (iv) a model relating chloroquine PKs to corrected QT (QTc) prolongation. A mechanistic PK/virologic/QTc model for HCQ was developed and externally validated to predict SARS-CoV-2 rate of viral decline and QTc prolongation. SARS-CoV-2 viral decline was associated with HCQ PKs (P < 0.001). The extrapolated patient half-maximal effective concentration (EC 50 ) was 4.7 µM, comparable to the reported in vitro EC 50s . HCQ doses > 400 mg b.i.d. for ≥5 days were predicted to rapidly decrease viral loads, reduce the proportion of patients with detectable SARS-CoV-2 infection, and shorten treatment courses, compared with lower dose (≤ 400 mg daily) regimens. However, HCQ doses > 600 mg b.i.d. were also predicted to prolong QTc intervals. This prolongation may have clinical implications warranting further safety assessment. Due to COVID-19's variable natural history, lower dose HCQ regimens may be indistinguishable from controls. Evaluation of higher HCQ doses is needed to ensure adequate safety and efficacy.

Tuberculosis (TB) kills more people than any other infectious disease. Challenges for developing better treatments include the complex pathology due to within-host immune dynamics, interpatient variability in disease severity and drug pharmacokinetics-pharmacodynamics (PK-PD), and the growing emergence of resistance. Model-informed drug development using quantitative and translational pharmacology has become increasingly recognized as a method capable of drug prioritization and regimen optimization to efficiently progress compounds through TB drug development phases. In this review, we examine translational models and tools, including plasma PK scaling, site-of-disease lesion PK, host-immune and bacteria interplay, combination PK-PD models of multidrug regimens, resistance formation, and integration of data across nonclinical and clinical phases. We propose a workflow that integrates these tools with computational platforms to identify drug combinations that have the potential to accelerate sterilization, reduce relapse rates, and limit the emergence of resistance. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 61 is January 8, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Amikacin and kanamycin are second line injectables used in the treatment of multidrug resistant tuberculosis (MDR-TB), based on the clinical utility of streptomycin, another aminoglycoside and first line anti-TB drug. While streptomycin was tested as a single agent in the first controlled TB clinical trial, introduction of amikacin and kanamycin into MDR-TB regimens was not preceded by randomized controlled trials. A recent large retrospective meta-analysis revealed that compared with regimens without any injectable drug, amikacin provided modest benefits, and kanamycin was associated with worse outcomes. Although their long-term use can cause irreversible ototoxicity, they remain part of MDR-TB regimens because they have a role in preventing emergence of resistance to other drugs. To quantify the contribution of amikacin and kanamycin to second-line regimens, we applied 2-dimensional MALDI mass spectrometry imaging in large lung lesions, quantified drug exposure in lung and lesions of rabbits with active TB, and measured the concentrations required to kill or inhibit growth of the resident bacterial populations. Using these metrics, we applied site-of-action pharmacokinetic and pharmacodynamic (PK-PD) concepts and simulated drug coverage in patients’ lung lesions. The results provide a pharmacological explanation for the limited clinical utility of both agents and reveal better PK-PD lesion coverage for amikacin than kanamycin, consistent with retrospective data of contribution to treatment success. Together with recent mechanistic studies dissecting antibacterial activity from aminoglycoside ototoxicity, the limited but rapid penetration of streptomycin, amikacin and kanamycin to the sites of TB disease supports the development of analogs with improved efficacy and tolerability.

Nontuberculous mycobacterial pulmonary disease (NTM-PD) is a potentially fatal infectious disease requiring long treatment duration with multiple antibiotics and against which there is no reliable cure. Among the factors that have hampered the development of adequate drug regimens is the lack of an animal model that reproduces the NTM lung pathology required for studying antibiotic penetration and efficacy. Given the documented similarities between tuberculosis and NTM immunopathology in patients, we first determined that the rabbit model of active tuberculosis reproduces key features of human NTM-PD and provides an acceptable surrogate model to study lesion penetration. We focused on clarithromycin, a macrolide and pillar of NTM-PD treatment, and explored the underlying causes of the disconnect between its favorable potency and pharmacokinetics, and inconsistent clinical outcome. To quantify pharmacokinetic-pharmacodynamic target attainment at the site of disease, we developed a translational model describing clarithromycin distribution from plasma to lung lesions, including the spatial quantitation of clarithromycin and azithromycin in mycobacterial lesions of two patients on long-term macrolide therapy. Through clinical simulations, we visualized the coverage of clarithromycin in plasma and four disease compartments, revealing heterogeneous bacteriostatic and bactericidal target attainment depending on the compartment and the corresponding potency against nontuberculous mycobacteria in clinically relevant assays. Overall, clarithromycin’s favorable tissue penetration and lack of bactericidal activity indicated that its clinical activity is limited by pharmacodynamic rather than pharmacokinetic factors. Our results pave the way towards the simulation of lesion pharmacokinetic-pharmacodynamic coverage by multi-drug combinations, to enable the prioritization of promising regimens for clinical trials.

The beta-1 adrenergic receptor (ADRB1) is a promising therapeutic target intrinsically involved in the cognitive deficits and pathological features associated with Alzheimer’s disease (AD). Evidence indicates that ADRB1 plays an important role in regulating neuroinflammatory processes, and activation of ADRB1 may produce neuroprotective effects in neuroinflammatory diseases. Novel small molecule modulators of ADRB1, engineered to be highly brain permeable and functionally selective for the G protein with partial agonistic activity, could have tremendous value both as pharmacological tools and potential lead molecules for further preclinical development. The present study describes our ongoing efforts toward the discovery of functionally selective partial agonists of ADRB1 that have potential therapeutic value for AD and neuroinflammatory disorders, which has led to the identification of the molecule STD-101-D1. As a functionally selective agonist of ADRB1, STD-101-D1 produces partial agonistic activity on G protein signaling with an EC50 value in the low nanomolar range, but engages very little beta-arrestin recruitment compared to the unbiased agonist isoproterenol. STD-101-D1 also inhibits the tumor necrosis factor α (TNFα) response induced by lipopolysaccharide (LPS) both in vitro and in vivo, and shows high brain penetration. Other than the therapeutic role, this newly identified, functionally selective, partial agonist of ADRB1 is an invaluable research tool to study mechanisms of G protein-coupled receptor signal transduction.