Browsing by Subject "Population pharmacokinetics"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Application of Clinical Pharmacology in Rare Diseases and Non-suicidal Self-injury
    (2022-08) Sahasrabudhe, Siddhee
    The overall objectives of this dissertation are twofold (1) to develop N-acetylcysteine (NAC) as a repurposed adjunctive treatment for two rare diseases -childhood cerebral adrenoleukodystrophy (cALD), and Gaucher disease type 1 (GD1); and a psychiatric behavior called non-suicidal self-injury (NSSI) and (2) to explore in-silico approaches to improve dosing flexibility and safety associated with the use of eliglustat in the treatment of GD1. A rare disease is a condition that affects not more than 200,000 people in the US. The regulatory definition of rare diseases varies across the globe. Few regulatory agencies further classify rare diseases that affect an even smaller fraction of patients as ultrarare diseases, such a classification does not exist per the US-FDA. There are about 7,000 rare diseases of which for approximately 5,000 conditions there are no approved pharmacological treatments. In cALD, hematopoietic stem cell transplant (HSCT) is practiced as a standard of care regimen for pediatric patients with radiological evidence of cerebral disease when the symptoms are still mild, and the risk-to-benefit ratio is favorable. Only the individual components such as medications (e.g., cytotoxic drugs, antibiotics) and procedures (e.g., use of radiation) that encompass HSCT have been approved by the FDA, largely in reference to other diseases (e.g., cancer, infectious diseases)—thus, there is variability in HSCT practice across different clinics. Due to the oxidative stress and inflammation caused by the underlying disease and enhanced by the procedures such as radiation as part of HSCT, a supporting treatment that can alleviate post-transplant complications, and improve prognosis is desired. For treatment of GD1, there are 5 approved products in the US, however, the patients continue to suffer worsening and sporadic symptoms related to pain and fatigue—thought to emerge from unresolved inflammation. A safe and effective adjunctive treatment that can address the unabated underlying pathophysiology leading to symptom manifestation can be of immense importance to enhance patient care. There are no FDA-approved pharmacological treatments for NSSI, a common adolescent mental health problem manifested as self-inflicted harmful behavior. Owing to the shared underlying pathophysiology of oxidative stress and inflammation in these three diseases, this dissertation investigated the hypothesis that an antioxidant and anti-inflammatory agent N-acetylcysteine (NAC) would be of clinical benefit in patients with these diseases. This dissertation specifically studied clinical pharmacology aspects of NAC in patients with cALD, GD1, and NSSI including characterization of pharmacokinetics (PK), pharmacodynamics, variability in biomarkers at baseline, and implications for optimum NAC dose and the design of future clinical studies. The steady-state pharmacokinetics of IV NAC were studied following 70mg/kg doses on three occasions in pediatric patients with inherited metabolic disorders (IMDs, e.g., cALD). The objective was to identify if the NAC dose would need to be adjusted relative to the transplant day from a PK standpoint (chapter 3). The PK and pharmacodynamics following oral doses of NAC in patients with NSSI were assessed for dose optimization and to identify the biological signature of NAC in these patients (chapter 4). I also explored the longitudinal biological variability in fifteen oxidative stress and inflammation biomarkers to assess candidate biomarkers with a smaller extent of variability to aid the design of a prospective clinical trial of NAC in patients with GD1 (chapter 5). Finally, for eliglustat, a first-line oral substrate reduction therapy for adult patients with GD1 the drug-drug interactions (DDI) were simulated to identify situations where lower eliglustat doses would improve safety from a QT prolongation perspective (chapter 6) The objectives of chapter 3 were to (1) characterize NAC PK in patients with IMDs undergoing HSCT using population PK modeling and (2) evaluate the impact of the HSCT process on NAC PK parameters. Eighteen pediatric patients with IMDs who underwent HSCT were included in a population PK analysis using nonlinear mixed-effects modeling. NAC clearance (CL) and volume of distribution (V) were explored on 3 occasions: –7, +7, and +21 days relative to the transplant. Additionally, the effect of transplant procedure on NAC disposition was explored by accounting for between-occasion variability. We found that a 2-compartment model adequately described the PK of total NAC. Additionally, HSCT did not change CL and V1 significantly, and analysis across occasions did not reveal any trends. PK parameter estimates were in general comparable to those reported previously in different populations. These results suggest that the dosing of NAC does not need to be altered following HSCT. The study detailed in chapter 4 was a randomized, double-blind study comparing two doses of NAC against the placebo. The objectives of chapter 4 were (1) to assess the effect of 4-weeks-treatment with NAC on percent change observed in four candidate biomarkers of oxidative stress (total glutathione (GSH), redox ratio (GSH/GSSG), catalase, and heme oxygenase (HO-1)) and (2) to assess the differences in NAC exposure between the 5.4g/day (HIGH dose) and 3.6 g/day (LOW dose) group at the steady-state. The exposure was compared using steady-state trough concentration of NAC and the partial area under the curve (AUC0-2) following the last dose of either HIGH or LOW NAC. Our results suggest that there was no discernable relationship between NAC dose and response. In addition to the high prevalence of placebo response; there was large variability in response in all three groups dampening the statistical significance of differences across groups. In chapter 5 our objective was to estimate plausible baseline values of fifteen biomarkers of interest along with the extent of the inherent variability; both intra-subject and inter-subject, observed in their repeated measurements over three months in participants with GD1 on stable standard-of-care therapy (N=13), treatment-naïve participants with GD1 (N=5) and in age- and gender-matched healthy volunteers (N=18). We utilized Bland-Altman plots for visual comparison of the biological variability among the three measurements. We also report group-wise means and the percentage of coefficient of variation (%CV) for the biomarkers. Qualitatively, we show specific markers (IL-1Ra, IL-8, and MIP-1b) to be consistently altered in GD1, irrespective of therapy status, highlighting the need for adjunctive therapies that can target and modulate these biomarkers. The objectives of chapter 6 were (1) to develop and validate the eliglustat physiologically based PK model (PBPK) with and without drug interactions, (2) to simulate untested DDI scenarios, and (3) to explore potential dosing flexibility using lower doses of eliglustat (commercially not available, compounding of eliglustat capsules is not recommended). Published physicochemical properties and PK information of eliglustat was utilized for the development and validation of the eliglustat PBPK model. Then, as model-based simulations, we illustrated eliglustat exposure as a victim of interaction when co-administered with an anti-depressant and exploratory COVID medication fluvoxamine. Second, we showed that lower eliglustat doses (21mg, 42mg QD) may benefit patients in a co-administration setting with ketoconazole, a strong metabolism inhibitor for eliglustat. NAC has been used for various indications since the 1960s, however systematic studies investigating NAC’s clinical pharmacology and biomarkers of response have been lacking. This dissertation attempts to bridge those knowledge gaps and makes the better design of future NAC clinical trials possible. Research presented in this dissertation can also serve as a prototype for ad-hoc studies that can be undertaken to answer new clinical questions. DDI simulations and possible mitigation strategies for eliglustat represent an example of the impact of clinical pharmacology techniques such as PBPK modeling and simulations.
  • Thumbnail Image
    Item
    Application of pharmacometrics for covariate selection and dose optimization of tacrolimus in adult kidney transplant recipients
    (2012-12) Passey, Chaitali
    In spite of rigorous dose adjustments by way of therapeutic drug monitoring, a large proportion of kidney transplant recipients are unable to achieve the target tacrolimus trough concentrations. This is attributed to the narrow therapeutic window of the drug (10-15 ng/mL) and large inter-individual variability in pharmacokinetic parameter such as clearance. There is a need for development of clinical dosing models that can help prospectively predict the dose for an individual, especially in the critical period immediately post-transplant. Therefore, we established and quantified the effect of clinical and genetic factors on tacrolimus clearance (CL/F) using a large population of adult kidney transplant recipients. Tacrolimus troughs (n=11823) from 681 transplant recipients over the first 6-months post-transplant were analyzed using non-linear mixed effects modeling approach in NONMEM®. The troughs were characterized by a steady state infusion model. Covariates were analyzed using a forward selection (p<0.0.1) backward elimination (p<0.001) approach. We formulated an equation that predicts the CL/F of an individual based on the days post-transplant, presence of the highly influential CYP3A5*1 genotype, transplant at a steroid sparing center, age and concomitant use of a calcium channel blocker at the time of trough collection. The CL/F was seen to decrease with increasing days post transplant, transplant at a steroid sparing center and use of a calcium channel blocker. Transplant recipients with the CYP3A5*1/*3 and *1/*1 genotypes had a CL/F that was 70% and 100% higher, respectively, than those with the CYP3A5*3/*3 genotype. The dose required in order to achieve a particular target trough can be prospectively determined from this equation. The above equation was validated in a separate cohort of adult kidney transplant recipients. The equation was assessed by predictive performance in 795 transplant recipients (n=13,968 troughs) receiving tacrolimus using bias and precision. Assessment was done for the initial troughs as well as for all troughs over the entire 6 months. The equation has low bias (0.2 ng/ml) and good precision (within ± 20% for a typical trough of 10 ng/mL) in predicting initial troughs and could be safely used to predict initial doses. This is critical as an accurate initial dose will help the recipient to get to therapeutic range faster and reduce the number of out-of-range troughs. For all the troughs, over the 6 months post-transplant, the equation did better than a basic model with no covariates but had higher bias and imprecision than the prediction of initial troughs. We were presented with 119 single nucleotide polymorphisms (SNP) in this study. Due to software limitations and impracticalities associated with such a large number of covariates, we developed and validated a novel "winnowing method" of covariate selection that is able to test and select SNPs in combination. This method uses random selection, repetitions of generalized additive modeling in the R statistical package and post-hoc estimates from NONMEM®. The salient feature of this method is the creation of an index, ranging from 0-1, that defines the relative importance of the SNP when tested in a combination. With this method, we were able to select 26 SNPs out of the 119 SNPs, which included the well-established CYP3A5*1 SNP. We validated this method using a simulated dataset. In the validation dataset, the winnowing method was able to select all the important SNPs. The type I and type II error rates were 9% and 0% respectively. Although NONMEM® is the oldest and most widely used population pharmacokinetics software, several other software packages are now becoming available such as the Phoenix® NLMETM. One desirable feature in this new software package is a graphical user interface and menu-driven covariate selection options. Therefore, we compared these two software packages in terms of covariates selected and predictive performance using both clinical and simulated data. For the tacrolimus data, NONMEM® predictions had lower bias and imprecision as compared to Phoenix® NLMETM. For the clinical data, NONMEM® predictions had higher bias but were more precise than the Phoenix® NLMETM predictions.>
  • Thumbnail Image
    Item
    Methadone population pharmacokinetics: toward understanding the dose-response relationship in the treatment of opiate addiction
    (2013-01) Bart, Gavin Bryce-Samuel
    Methadone is a synthetic opiate agonist that is highly effective in the treatment of opiate addiction. When given as a long-term therapy, methadone maintenance reduces morbidity and mortality associated with opiate addiction. It is thus considered an “essential” medication by the World Health Organization. The benefits of methadone maintenance in the treatment of opiate addiction are well established. Predicting treatment response for a given individual, however, remains difficult. While methadone dose is generally associated with treatment outcome, large interstudy and interindividual variability in plasma concentrations of methadone have made it difficult to link dose response to pharmacokinetic parameters. This thesis explores characteristics of methadone maintained patients and develops a population pharmacokinetic model that identifies variables associated with methadone pharmacokinetic parameters. Chapter 1 provides a general review of the three Food and Drug Administration approved pharmacotherapeutic agents for the treatment of opiate dependence. Chapter 2 reviews the clinical pharmacology of methadone as used in the treatment of opiate dependence. Chapter 3 introduces us to the Hmong and their paradoxically exceptional treatment outcome in methadone maintenance on lower doses of methadone than their non-Hmong counterparts. This retrospective study helps form the hypothesis that their better treatment outcome is related to greater methadone exposure.The results of this population pharmacokinetic study and the psychosocial differences between Hmong and non-Hmong are presented in Chapters 4 and 5, respectively. We found that the lower methadone dose requirement is explained by higher apparent bioavailability of methadone in Hmong. Other influences on methadone pharmacokinetics, more specifically clearance, include age, body mass index, and single nucleotide polymorphisms in the ABCB1 and CYP2B6 genes. While the potential for culture to influence methadone treatment outcome is acknowledged, there remain sufficient grounds to hypothesize a significant biological (i.e., pharmacokinetic and/or pharmacodynamic) influence.