Conclusion:
We demonstrate that systematically collated data on the ADME, human PK parameters, DDIs, and organ impairment has enabled verification of simulated plasma and lung tissue exposure of many repurposed COVID-19 drugs to justify broader recruitment criteria for patients. In addition, developed PBPK model helped to assess the correlation between target site exposure to relevant potency values from in vitro studies for SARS-CoV-2.
INTRODUCTION
“Necessity is the mother of invention”: Desperate times have often led to necessary efforts to satisfy an unmet need by unorthodox means. Clinical trials in drug development are no exception to this. In general, clinical trials are conducted in a systematic way and follow stringent recruitment criteria. Lack of diversity in patients recruited to drug trials was the subject of a recent draft Guidance for Industry by the US FDA, where they encouraged inclusion of the elderly, those at the extremes of the weight range, individuals with organ dysfunction, those with malignancies or certain infections such as HIV, and children [1]. This guidance emphasized the need to characterize drugs more comprehensively during early clinical development (e.g., with respect to drug metabolism and clearance pathways). In addition, the guidance indicated that, in many cases, dose adjustments can be made in specific populations to reduce significant differences in systemic exposure to the investigational drug. However, broadened recruitment of patients in COVID-19 drug trials has been an exception to the norm and is happening by default due to the speed of transmission of the virus. The pandemic has accelerated the adoption of the draft guidance in respect to broadening recruitment. However, the question of how this could be done without compromising sub-groups of populations with the burden of potentially higher exposure levels to drugs, especially for drugs that lack dedicated safety studies in these sub-population groups.
COVID-19 pandemic in perspective: Several therapeutic agents have been evaluated for the treatment of COVID-19, but remdesivir, acalabrutinib, ibrutinib, and dexamethasone have shown some positive results [2-4]. The FDA has issued guidance related to COVID-19 [5] which highlights the safety of trial participants as a key consideration for ongoing trials in addition to establishing the efficacy of drug against SARS-CoV-2. The estimated basic reproduction number for SARS-CoV-2 is 2.65 days (with a range from 1.85 to 3.41 days) [6]. High transmission rate of COVID-19 infection has led to changes in study design; trials with greater diversity in patient recruitment are becoming more common than those with strict protocol inclusion and exclusion criteria for patient characteristics. This rapid enrollment, however, may result in higher exposure levels of drugs in study subjects.
Drugs on Trial for COVID-19: As of May 21st, 2020, there were 1,621 COVID-19 trials on clinicaltrials.gov, of which 912 are active and/or recruiting. To address the urgent need for therapeutic remedies for COVID-19, efforts to repurpose existing drugs are increasing hence most trials are focused on existing drugs rather than Investigational New Drugs. These repurposed drugs consist of anti-virals (azithromycin, atazanavir, baloxavir, darunavir, lopinavir, remdesivir, ritonavir), anti-cancer drugs (acalabrutinib, ibrutinib, baricitinib, ruxolitinib), anti-inflammatory (dexamethasone), large molecules (siltuximab, emapalumab, tocilizumab), antimalarials (chloroquine, hydroxychloroquine), and one anti-diabetic and heart failure treatment drug (dapagliflozin). Azithromycin is dosed in combination with hydroxychloroquine.[7]
Typical COVID-19 Patient and Cytokine Storm: A typical hospitalized COVID-19 patient exhibits overproduction of early response pro-inflammatory cytokines such as tumor necrosis factor (TNF), interleukin-6 (IL-6), and interleukin-1 beta (IL-1β). This is known as a ‘cytokine storm,’ and is thought to be one of the major causes of acute respiratory distress syndrome (ARDS) and multiple-organ failure [8] . Patients presenting with cytokine release syndrome typically show cytopenia, elevated creatinine, deranged coagulation parameters, and high C-reactive protein (CRP) [9]. The common symptoms and cascade of a COVID-19 induced cytokine storm [10] are depicted in Figure 1. Due to the relationship between cytokine release syndrome and poor outcomes among COVID-19 patients, many of the drugs (small molecules and biologicals) currently being tested aim to dampen this severe immune response, while others target the virus’ ability to infect cells. Inflammation resulting from cytokine release starts locally, in areas such as pulmonary tissue, and spreads to other organs through systemic circulation. This triggers compensatory biological repair processes which restore tissue and organ function; however, these processes can lead to fibrosis and persistent organ dysfunction of the lungs, heart, liver and kidney [11]. Many small molecule drugs are metabolized by cytochrome P450 (CYP) enzymes typically expressed in the liver, gut, lung and kidney. Several pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, IFN-γ) have been reported to downregulate the expression of these enzymes and transporters such as P-gp by inducing transcription factors (e.g. PXR, CAR, NF-kB, and HNF), which in turn reduce the abundance of CYP450 and P-gp in tissues. This influences the absorption, distribution and metabolism of drugs, as represented in Figure 1.
Information on Study-sub populations: Remdesivir clinical trial [2] patient characteristics included chronic liver (2%) and kidney disease (6%), cancer (8%) and obesity (37%). 36% of patients were >65 years and patients of different race were included in the trial population. A large proportion of COVID-19 patients requiring hospitalization and treatment are geriatric and it is likely that this patient population may exhibit exposure differences. The possibility of testing the effect of intrinsic and extrinsic factors clinically is limited, for instance PK on the geriatric COVID-19 patients.
Physiologically-based pharmacokinetic (PBPK) models: The pharmacokinetic and ADME data for single or multiple doses is relatively abundant for COVID-19 repurposed drugs and can be used to build PBPK models. These models utilize three-components: a system component, a drug-dependent component, and a clinical trial-specific component. Details of human physiology are specified in system components, for instance drug metabolizing enzyme or transporter enzyme abundance, tissue blood flow to organs, and so on. Drug properties such as solubility, fraction metabolized by enzymes and renal clearance, are specified in the drug-dependent components, whilst the clinical trial-specific component defines the simulated scenario, including dosing regimen, population age, and gender proportion. PBPK models combine these components to predict drug ADME, and by extension pharmacokinetics (PK), in a simulated scenario where clinical study data are not available. These verified PBPK models can provide the ability to extrapolate beyond the available data and account for disease-drug interactions [12, 13].
Target site concentrations: As COVID-19 mainly targets lung tissue making it difficult to assess tissue concentration, understanding expected target concentration may be crucial, particularly when attempting to translate observed effect from the in vitro studies to projected clinical situation. PBPK models are useful to predict drug unbound concentrations in the epithelial lining fluid (ELF) [14] which is relevant for treatment of COVID-19 patients, as it can contain a persistent reservoir of virus.
The objectives of this study were to gather information on the ADME, PK/PD, DDI, AEs, and the effect of intrinsic and extrinsic factors on the disposition of all repurposed drugs currently under trial for COVID-19. This enabled us to explore the utility of PBPK models for possible clinical scenarios after verifying them based on the gathered pre-clinical and clinical data. Then we used the models to predict expected alterations in exposure to these drugs in sub-populations of COVID-19 patients which have not yet been studied for some of the drugs e.g., in patients with older age, different race, and hepatic/renal impairment. These variations were studied in relation to target site concentrations. All these models were developed by accounting for the interplay between cytokines and metabolic disposition.
METHODS