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to drug trials was the subject of a recent draft Guidance for Industry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has accelerated the adoption of the draft guidance in respect to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