Date of Award

2020

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Pharmaceutical Sciences

Department

Pharmaceutical Sciences

First Advisor

Stephen J. Kogut

Abstract

Drug-induced liver injury (DILI) is one of the leading reasons for clinical candidate termination during drug discovery and development. Similarly, many drugs have received a black-box warning or withdrawn from the market due to DILI. It is reported that DILI is the 4th leading cause of liver disease leading to liver failure. It is estimated that the DILI has an annual incidence rate of 13.9 ± 2.4 cases per 100,000 people, translating to about 44,000 liver injury patients in the United States each year. Despite tremendous research in the predictive field, liver injury prediction using in vitro and in vivo models remains a substantial challenge. In this dissertation, I use the three-manuscript format to address the literature gap based on the drug's toxicological properties and its ability to cause mitochondrial dysfunction. I also evaluated the risk of liver injury among patients newly treated with atypical antipsychotics.

Manuscript 1 combined physicochemical properties and in vitro cytotoxicity assays, including mitochondrial dysfunction, to build organ-specific univariate and multivariable logistic regression models to derive odds ratios for the prediction of clinical hepatotoxicity, nephrotoxicity, and cardiotoxicity for 215 marketed drugs. The multivariable hepatotoxic predictive model showed an odds ratio of 6.2 or 7.5 for mitochondrial inhibition or drug plasma Cmax >1 μM for drugs associated with liver injury, respectively. The multivariable nephrotoxicity predictive model showed an odds ratio of 5.8, 6.4, or 15.9 for drug plasma Cmax >1 μM, mitochondrial inhibition, or hydrogen bond acceptor atoms greater than 7 for drugs associated with kidney injury, respectively. Conversely, drugs with a total polar surface area ≥75Å were 79% less likely to be associated with kidney injury. Based on this study, I found that combining in silico physicochemical properties descriptors along with in vitro toxicity assays can be used to build predictive toxicity models to select small molecule therapeutics with less potential to cause liver and kidney toxicity. Therefore, I recommend a blended approach of utilizing readily calculated physicochemical properties combined with in vitro toxicity assessments to select small molecules with less potential for clinical organ toxicity for the liver and kidney.

There is a growing need for characterization of age-differences in the susceptibility and frequency of DILI caused by hepatotoxicants according to their ability to cause mitochondrial dysfunction. Manuscript 2 investigated the relationship between liver injury reports submitted to the Food and Drug Administration Adverse Event Reporting System with drugs associated with hepatotoxicity via mitochondrial mechanisms compared with non-mitochondrial mechanisms of toxicity. This study provides evidence that a higher proportion of reports of severe liver injury adverse events among drugs are associated with mitochondrial mechanisms of toxicity compared with non-mitochondrial mechanisms of toxicity. Furthermore, I found that reports of liver injury were 2.2 times more likely to be associated with older patient age than reports involving patients ages under 65 years. This finding agreed with the theory that age is a susceptibility factor in liver injury via mitochondrial mechanisms of toxicity. The findings from this study align with mitochondrial mechanisms of toxicity being an important cause of DILI, and this should be further investigated in real-world studies with robust designs.

Compared to typical antipsychotics, atypical antipsychotics (AAP) medications have improved safety profiles and rarely cause liver injury. However, no retrospective cohort studies have evaluated AAP's liver injury risk using an administrative database in the United States. In manuscript 3, I conducted a retrospective cohort study using an administrative claims database to estimate the cumulative incidence rate and identify risk factors for liver injury in patients taking AAP medications. Univariate and multivariate logistic regression analyses were utilized to identify risk factors associated with liver injury. The study estimated the cumulative incidence rate of liver injury 15.2 to 25.1 per 1000 persons per year among patients newly treated with AAP medications. During the first months of treatment, quetiapine, as compared to aripiprazole, was associated with a 22% increased risk of liver injury in patients 75 years and younger. Our study suggests that patients receiving quetiapine AAP should be monitored for liver enzyme elevations frequently during therapy initiation. Patients with comorbidities including alcohol abuse, hypertension, obesity, and hyperlipidemia were also found to be at higher risk and these patients should be monitored closely for liver injury. Further prospective real-world studies are warranted to substantiate these findings.

Available for download on Friday, December 03, 2021

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