Exploring the impact of CYP2D6 and UGT2B7 gene-drug interactions, and CYP-mediated DDI on oxycodone and oxymorphone pharmacokinetics using physiologically-based pharmacokinetic modeling and simulation.

Oxycodone is one of the most commonly used opioids to treat moderate to severe pain. It is metabolized mainly by CYP3A4 and CYP2D6, while only a small fraction of the dose is excreted unchanged into the urine. Oxymorphone, the metabolite primarily formed by CYP2D6, has a 40- to 60-fold higher mu-opioid receptor affinity than the parent compound. While CYP2D6-mediated gene-drug-interactions (GDIs) and drug-drug interactions (DDIs) are well-studied, they only account for a portion of the variability in oxycodone and oxymorphone exposure. The combined impact of CYP2D6-mediated GDIs and DDIs, CYP3A4-mediated DDIs, and UGT2B7 GDIs is not fully understood yet and hard to study in head-to-head clinical trials given the relatively large number of scenarios. Instead, we propose the use of a physiologically-based pharmacokinetic model that integrates available information on oxycodone's metabolism to characterize and predict the impact of DDIs and GDIs on the exposure of oxycodone and its major, pharmacologically-active metabolite oxymorphone. To this end, we first developed and verified a PBPK model for oxycodone and its metabolites using published clinical data. The verified model was then applied to determine the dose-exposure relationship of oxycodone and oxymorphone stratified by CYP2D6 and UGT2B7 phenotypes respectively, and administered perpetrators of CYP-based drug interactions. Our simulations demonstrate that the combination of CYP2D6 UM and a UGT2B7Y (268) mutation may lead to a 2.3-fold increase in oxymorphone exposure compared to individuals who are phenotyped as CYP2D6 NM / UGT2B7 NM. The extent of oxymorphone exposure increases up to 3.2-fold in individuals concurrently taking CYP3A4 inhibitors, such as ketoconazole. Inhibition of the CYP3A4 pathway results in a relative increase in the partial metabolic clearance of oxycodone to oxymorphone. Oxymorphone is impacted to a higher extent by GDIs and DDIs than oxycodone. We predict oxymorphone exposure to be highest in CYP2D6 UMs/UGT2B7 PMs in the presence of ketoconazole (strong CYP3A4 index inhibitor) and lowest in CYP2D6 PMs/UGT2B7 NMs in the presence of rifampicin (strong CYP3A4 index inducer) covering a 55-fold exposure range.

Identification of Novel and Early Biomarkers for Cisplatin-induced Nephrotoxicity and the Nephroprotective Role of Cimetidine using a Pharmacometabolomic-based Approach Coupled with In Vitro Toxicodynamic Modeling and Simulation.

Cisplatin is widely used for the treatment of various types of cancer. However, cisplatin-induced nephrotoxicity (CIN) is frequently observed in patients receiving cisplatin therapy which poses a challenge in its clinical utility. Currently used clinical biomarkers for CIN are not adequate for early detection of nephrotoxicity, hence there is a need to identify potential early biomarkers in predicting CIN. In the current study, a combination of in vitro toxicodynamic (TD) modeling and untargeted global metabolomics approach was used to identify novel potential metabolite biomarkers for early detection of CIN. In addition, we investigated the protective role of cimetidine (CIM), an inhibitor of the organic cation transporter 2 (OCT2), in suppressing CIN. We first characterized the time-course of nephrotoxic effects of cisplatin (CIS) and the protective effects of CIM in a human pseudo-immortalized renal proximal tubule epithelial cell line (RPTEC), SA7K cell line. Secondly, we used a mathematical cell-level, in vitro TD modeling approach to quantitatively characterize the time-course effects of CIS and CIM as single agents and combination in SA7K cells. Based on the experimental and modeling results, we selected relevant concentrations of CIS and CIM for our metabolomics study. With the help of PCA (Principal Component Analysis) and PLS-DA (Projection to Latent Structure - Discriminate Analysis) analyses, we confirmed global metabolome changes for different groups (CIS, CIM, CIS+CIM vs control) in SA7K cells. Based on the criterion of a p-value ≤ 0.05 and a fold change ≥ 2 or ≤ 0.5, we identified 20 top metabolites that were significantly changed during the early phase i.e. within first 12 h of CIS treatment. Finally, pathway analysis was conducted that revealed the key metabolic pathways that were most impacted in CIN.

Application of a patient-centered reverse translational systems-based approach to understand mechanisms of an adverse drug reaction of immune checkpoint inhibitors.

Immunotherapy became a key pillar of cancer therapeutics with the approvals of ipilimumab, nivolumab, and pembrolizumab, which inhibit either cytotoxic T-lymphocyte antigen-4 (CTLA-4) or programmed death-1 (PD-1) that are negative regulators of T-cell activation. However, boosting T-cell activation is often accompanied by autoimmunity, leading to adverse drug reactions (ADRs), including high grade 3-4 colitis and its severe complications whose prevalence may reach 14% for combination checkpoint inhibitors. In this research, we investigated how mechanistic differences between anti-CTLA-4 (ipilimumab) and anti-PD-1 (nivolumab and pembrolizumab) affect colitis, a general class toxicity. The data analytical platform Molecular Health Effect was utilized to map population ADR data from the US Food and Drug Administration (FDA) Adverse Event Reporting System to chemical and biological databases for hypothesis generation regarding the underlying molecular mechanisms causing colitis. Disproportionality analysis was used to assess the statistical relevance between adverse events of interest and molecular causation. We verified that the anti-CTLA-4 drug is associated with an approximately three-fold higher proportional reporting ratio associated with colitis than those of the anti-PD-1 drugs. The signal of the molecular mechanisms, including signaling pathways of inflammatory cytokines, was statistically insignificant to test the hypothesis that the severer rate of colitis associated with ipilimumab would be due to a greater magnitude of T-cell activation as a result of earlier response of the anti-CTLA-4 drug in the immune response. This patient-centered systems-based approach provides an exploratory process to better understand drug pair adverse events at pathway and target levels through reverse translation from postmarket surveillance safety reports.

Pharmacodynamic Modeling to Evaluate the Impact of Cimetidine, an OCT2 Inhibitor, on the Anticancer Effects of Cisplatin.

Despite potent anticancer activity, the clinical utilization of cisplatin is limited due to nephrotoxicity. As Organic Cation Transporter 2 (OCT2) has been shown to be one of the key transporters involved in the uptake of cisplatin into renal proximal tubules, OCT2 inhibitors such as cimetidine have been explored to suppress cisplatin-induced nephrotoxicity. Nonetheless, the impact of OCT2 inhibition or cimetidine on the anti-cancer effects of cisplatin has not been extensively examined. The main objective of the present study was to quantitatively characterize the anticancer effects of cisplatin and cimetidine and determine their nature of interactions in two cancer cell lines, OCT2-negative hepatocellular carcinoma (HCC) cell line, Huh7, and OCT2-positive breast cancer cell line, MDA-MB-468. First, we determined the static concentration-response curves of cisplatin and cimetidine as single agents. Next, with the help of three-dimensional (3D) response surface analyses and a competitive interaction model, we determined their nature of interactions at static concentrations to be modestly synergistic or additive in Huh7 and antagonistic in MDA-MB-468. These results were consistent with the cell-level pharmacodynamic (PD) modeling analysis which leveraged the time-course effects of drugs as single agents and drug combinations. Our developed PD model can be further used to design future preclinical studies to further investigate the cisplatin and cimetidine combinations in different in vitro and in vivo cancer models.

A clinical population pharmacokinetic/pharmacodynamic model for BIIB059, a monoclonal antibody for the treatment of systemic and cutaneous lupus erythematosus.

A population pharmacokinetic/pharmacodynamic (popPK/PD) model for BIIB059 (anti-blood dendritic cell antigen 2 [anti-BDCA2]), a humanized immunoglobulin G1 monoclonal antibody currently under development for the treatment of SLE and CLE, is presented. BIIB059 binds BDCA2, a plasmacytoid dendritic cell (pDC)-specific receptor that inhibits the production of IFN-I and other inflammatory mediators when ligated. Phase 1 PK and PD data of healthy adult volunteers (HV, n = 87) and SLE subjects (n = 22) were utilized for the development of the popPK/PD model. The data included single and multiple dosing of intravenous and subcutaneous BIIB059. BDCA2 internalization (PD marker) was measured for all subjects by monitoring reduction of BDCA2 on pDC cell surface and used for development of the popPD model. A two-compartment popPK model with linear plus non-linear elimination was found to best describe BIIB059 PK. BDCA2 levels were best captured using an indirect response model with stimulation of the elimination of BDCA2. Clearance in SLE subjects was 25% higher compared to HV (6.87 vs 5.52 mL/h). Bodyweight was identified as only other covariate on clearance and central volume. The estimates of EC50 and Emax were 0.35 µg/mL and 8.92, respectively. No difference in EC50 and Emax was observed between SLE and HV. The popPK/PD model described the data accurately, as evaluated by pcVPCs and bootstrap. The presented popPK/PD model for BIIB059 provides valuable insight into the dynamics and dose-response relationship of BIIB059 for the treatment of SLE and CLE and was used to guide dose selection for the Phase 2 clinical study (NCT02847598).

A Semi-Mechanistic Population Pharmacokinetic Model of Nusinersen: An Antisense Oligonucleotide for the Treatment of Spinal Muscular Atrophy.

A pharmacokinetic (PK) model was developed for nusinersen, an antisense oligonucleotide (ASO) that is the first approved treatment for spinal muscular atrophy (SMA). The model was built with data from 92 nonhuman primates (NHPs) following intrathecal doses (0.3-7 mg) and characterized the PK in cerebrospinal fluid (CSF), plasma, total spinal cord, brain, and pons. The estimated volumes were 13.6, 937, 4.5, 53.8, and 2.11 mL, respectively. Global sensitivity analysis demonstrated that the CSF-to-plasma drug distribution rate (0.09 hour-1 ) is a major determinant of the maximum nusinersen concentration in central nervous system (CNS) tissues. Physiological age-based and body weight-based allometric scaling was implemented with exponent values of -0.08 and 1 for the rate constants and the volume of distribution, respectively. Simulations of the scaled model were in agreement with clinical observations from 52 pediatric phase I PK profiles. The developed model can be used to guide the design of clinical trials with ASOs.

To Take or Not to Take With Meals? Unraveling Issues Related to Food Effects Labeling for Oral Antineoplastic Drugs.

There has been controversy regarding whether bioavailability of certain oral oncology drugs should be maximized by taking these medications with food, irrespective of label instructions in the dosing and administration section. To provide insight into this controversy, we conducted an in-depth analysis for oral antineoplastic drugs approved by the Food and Drug Administration in 2000-2016 and identified important issues influencing food labeling decisions. Furthermore, a case study involving sonidegib, a drug approved for locally advanced basal cell carcinoma with a significant food effect on exposure, was used to demonstrate the consequences of failure to adhere to food label recommendations using drug-specific population pharmacokinetic and exposure-toxicity models. In 2000-2009, 80% (4 out of 5) of all approved oral antineoplastics with increased bioavailability in the fed state were labeled as "take on empty stomach." In contrast, we found that in 2010-2016 there is a greater diversity in food recommendations for drugs with increased bioavailability in the fed state. Currently, many oral oncology drugs are given with food to maximize their bioavailability; however, as seen from our case study of sonidegib, failure to fully adhere to label recommendations to either take with food or not could lead to adverse consequences in terms of safety and efficacy.

Development and validation of a LC-MS/MS assay for quantification of cisplatin in rat plasma and urine.

Till date, no analytical method published to detect Cisplatin has been validated according to the U.S. Food and Drug Administration (FDA) guidance using liquid chromatography mass spectrometry (LC-MS/MS). We report, a validated LC-MS/MS method for quantitative determination of cisplatin in rat plasma and urine according to FDA guidlines. Cisplatin is a platinum containing compound used for the treatment of different types of cancers. Quantitative determination of cisplatin has been carried out using atomic absorption spectroscopy, high pressure liquid chromatography with phosphorescence, ultra-violet detection, or with inductively coupled plasma mass spectrometry. Few LC-MS/MS methods have been reported for the analysis of cisplatin either for direct quantification or indirect by derivatizing with organic compounds but none of the reported methods have validated the method. The developed and validated assay presented here is a highly sensitive LC-MS/MS method developed and validated for the quantitative determination of cisplatin following derivatization with diethyldithiocarbamate (DDTC) in order to detect platinum (Pt) of cisplatin, suitable for pharmacokinetic studies in rats and to further use it to study human toxicology. Chromatographic separation was achieved using a Poroshell 120 EC-C18 column (3×50mm, 2.7µm) with a binary gradient mobile phase. Quantification was performed on a triple quadruple with electrospray ionization and detection was performed using multiple reaction monitoring. The method has a limit of detection of 1ng/mL, and the quantifiable range was 3-3000ng/mL in rat plasma and urine. The method was accurate and precise with an accuracy and precision for intra-day and inter-day of ±20% for lower limit of quantitation and of ±15% for low, mid and high quality control samples. This method was successfully applied to study the pharmacokinetic profile of cisplatin in rat plasma and urine given a range of doses from 0.5 to 3.5mg/kg.

Systems pharmacology to predict drug safety in drug development.

Ensuring that drugs are safe and effective is a very high priority for drug development and the US Food and Drug Administration review process. This is especially true today because of faster approval times and smaller clinical trials, especially in oncology and rare diseases. In light of these trends, systems pharmacology is seen as an essential strategy to understand and predict adverse drug events during drug development by analyzing interactions between drugs and multiple targets rather than the traditional "one-drug-one-target" approach. This commentary offers an overview of the current trends and challenges of using systems pharmacology to reduce the risks of unintended adverse events.

Osteonecrosis of the Jaw in the United States Food and Drug Administration's Adverse Event Reporting System (FAERS).

Osteonecrosis of the jaw (ONJ) is a serious adverse drug event that was initially reported with intravenous bisphosphonates (BPs) and more recently with other classes of drugs such as receptor activator of NF-κB ligand (RANKL) inhibitor, antiangiogenic agents, and mammalian target of rapamycin (m-TOR) inhibitors. The purpose of this study is to analyze the ONJ cases and the associated drugs in the US Food and Drug Administration's adverse event reporting system (FAERS). The FAERS database was queried for the adverse drug events reported from the first quarter of 2010 to the first quarter of 2014. The reporting odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each queried drug. A total of 17,119 unique ONJ cases were identified. In the overall analysis, the drugs with the highest reporting ORs were BPs: pamidronate (OR = 498.9), zoledronate (OR = 171.7), and alendronate (OR = 63.6), whereas denosumab had lower ORs than all the BPs except for etidronate. The antiangiogenic and m-TOR inhibitors had the lowest ORs. In cancer patients who were treated for prevention of skeletal-related events (SREs), the reporting ORs for zoledronate and denosumab were 125.2 and 4.9, respectively. In patients with osteoporosis, the ORs were 1.1 (1.0-1.18) for zoledronate and 0.63 (0.56-0.70) for denosumab, respectively. Our analysis of the FAERS database showed that the intravenous BPs were associated with the highest risk for ONJ, RANKL inhibitor was associated with risk comparable to BPs used for osteoporosis such as etidronate, and the antiangiogenic agents and m-TOR inhibitors were associated with the lowest risk for ONJ. The high risk for ONJ with zoledronate and denosumab was mainly observed in those who were treated for prevention of SREs, whereas there was limited evidence for such risk in those who were treated for osteoporosis.

Clinical pharmacokinetics and pharmacodynamics of clopidogrel.

Acute coronary syndromes (ACS) remain life-threatening disorders, which are associated with high morbidity and mortality. Dual antiplatelet therapy with aspirin and clopidogrel has been shown to reduce cardiovascular events in patients with ACS. However, there is substantial inter-individual variability in the response to clopidogrel treatment, in addition to prolonged recovery of platelet reactivity as a result of irreversible binding to P2Y12 receptors. This high inter-individual variability in treatment response has primarily been associated with genetic polymorphisms in the genes encoding for cytochrome (CYP) 2C19, which affect the pharmacokinetics of clopidogrel. While the US Food and Drug Administration has issued a boxed warning for CYP2C19 poor metabolizers because of potentially reduced efficacy in these patients, results from multivariate analyses suggest that additional factors, including age, sex, obesity, concurrent diseases and drug-drug interactions, may all contribute to the overall between-subject variability in treatment response. However, the extent to which each of these factors contributes to the overall variability, and how they are interrelated, is currently unclear. The objective of this review article is to provide a comprehensive update on the different factors that influence the pharmacokinetics and pharmacodynamics of clopidogrel and how they mechanistically contribute to inter-individual differences in the response to clopidogrel treatment.

Clinical implementation of genetic testing in medicine: a US regulatory science perspective.

Heterogeneity of treatment effects in unselected patient populations has stimulated various strategic approaches to reduce variability and uncertainty and improve individualization of drug selection and dosing. The rapid growth of DNA sequencing and related technologies has ramped up progress in interpreting germline and somatic mutations and has begun to reshape medicine, especially in oncology. Over the past decade, regulatory agencies realized that they needed to be proactive and not reactive if personalized medicine was to become a reality. The US Food and Drug Administration, in particular, took steps to nurture the field through peer-reviewed publications, co-sponsoring public workshops and issuing guidance for industry. The following two major approaches to personalized medicine were taken: (i) encouragement of de novo co-development of drug-genetic test combinations by industry; and (ii) retrospective assessment of legacy genetic data for the purpose of updating drug labels. The former strategy has been more successful in getting new targeted therapies to the marketplace with successful adoption, while the latter, as evidenced by the low adoption rate of pharmacogenetic testing, has been less successful. This reflection piece makes clear that several important things need to happen to make personalized medicine diffuse in more geographical areas and among more therapeutic specialties. The debate over clinical utility of genetic tests needs to be resolved with consensus on evidentiary standards. Physicians, as gatekeepers of prescription medicines, need to increase their knowledge of genetics and the application of the information to patient care. An infrastructure needs to be developed to make access to genetic tests and decision-support tools available to primary practitioners and specialists outside major medical centres and metropolitan areas.

Translational biomarkers: from preclinical to clinical a report of 2009 AAPS/ACCP Biomarker Workshop.

There have been some successes in qualifying biomarkers and applying them to drug development and clinical treatment of various diseases. A recent success is illustrated by a collaborative effort among the US Food and Drug Administration, the European Medicines Agency, and the pharmaceutical industry to provide a set of seven preclinical kidney toxicity biomarkers for drug development. Other successes include, but are not limited to, clinical biomarkers for cancer treatment and clinical management of heart transplant patients. The value of fully qualified surrogate endpoints in facilitating successful drug development is undisputed, especially for diseases in which the traditional clinical outcome can only be assessed in large, multi-year trials. Emerging biomarkers, including chemical genomic or imaging biomarkers, and measurement of circulating tumor cells hold great promise for early diagnosis of disease and as prognostic tests for managing treatment of chronic diseases such as osteoarthritis, Alzheimer disease, cardiovascular disease, and cancer. To advance the success of treating and managing these diseases, efforts are needed to establish the temporal relationship between changes in inflammatory or imaging biomarkers with the progression of the chronic disease, and in the case of cancer, between the extent of circulating cancer cells and tumor progression or remission.

Cancer pharmacogenomics and pharmacoepidemiology: setting a research agenda to accelerate translation.

Recent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled "Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation" on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.

Food and oral antineoplastics: more than meets the eye.

Food can alter the bioavailability of orally administered drugs. Description of food effects in product labels and information about administration in relation to food are influenced by a variety of factors. Because food effects can change drug efficacy and toxicity, it is important that physicians and patients be aware of them.

Voluntary exploratory data submissions to the US FDA and the EMA: experience and impact.

Heterogeneity in the underlying mechanisms of disease processes and inter-patient variability in drug responses are major challenges in drug development. To address these challenges, biomarker strategies based on a range of platforms, such as microarray gene-expression technologies, are increasingly being applied to elucidate these sources of variability and thereby potentially increase drug development success rates. With the aim of enhancing understanding of the regulatory significance of such biomarker data by regulators and sponsors, the US Food and Drug Administration initiated a programme in 2004 to allow sponsors to submit exploratory genomic data voluntarily, without immediate regulatory impact. In this article, a selection of case studies from the first 5 years of this programme - which is now known as the voluntary exploratory data submission programme, and also involves collaboration with the European Medicines Agency - are discussed, and general lessons are highlighted.

Understanding the genetic basis for adverse drug effects: the calcineurin inhibitors.

The calcineurin inhibitors-cyclosporine and tacrolimus-are the mainstay of immunosuppressive therapy in solid organ transplantation. These drugs produce severe adverse drug effects (ADEs) such as nephrotoxicity, posttransplantation diabetes mellitus, and hypertension. Accumulated evidence suggests that the development of type 2 diabetes, hypertension, and renal failure may be associated with specific DNA genotypes. In this review, the genes involved with the development of these disease processes are compared with those implicated in calcineurin inhibitor-induced ADEs. The renin-angiotensin system genes, cytokine-encoding genes, and plasminogen activator inhibitor type 1 genes have been implicated in calcineurin inhibitor-induced nephrotoxicity, as well as in development of renal failure. A number of genes are implicated in contributing to diabetes, and these include the vitamin D receptor gene, VDR; hepatocyte nuclear factor genes, HNF; transcription factor 7-like 2 gene, TCF7L2; angiotensin-converting enzyme gene, ACE; cytokines; peroxisome proliferator-activated receptor gamma gene, PPARG; and others. Studies have suggested that the VDR, PPARG, HNF1A, and adenosine 5'-triphosphate-binding cassette ABCC8 (which encodes the sulfonylurea receptor) genes are associated with calcineurin inhibitor-induced diabetes. The genes encoding for the angiotensin-converting enzyme, endothelial constitutive nitric oxide synthase, and cytochrome P450 3A isoenzyme have been involved in the development of hypertension and in calcineurin inhibitor-induced hypertension. The genetic study of disease states can be the stepping stones for thoroughly understanding the genetic basis of ADEs. Gene polymorphisms are implicated in the development of diseases and corresponding disease-like ADEs. The disease-associated genes provide candidate genes for exploring ADEs and may provide genomic biomarkers for assessing the risk for developing severe calcineurin inhibitor-related ADEs as well as for developing preventive strategies.

Application of pharmacogenomics in clinical pharmacology.

Many factors can affect a patient's response to a drug. These include intrinsic factors such as age, gender, race/ethnicity, genetics, disease states, organ dysfunctions, and other physiological changes, including pregnancy, lactation, and extrinsic factors such as smoking, diet (food, juice, dietary supplements), and concomitant medications (ICH E5, 1998 and 2004). The interplay of genotypes of the enzymes, transporters and receptors, among other factors (such as concomitant medications and disease states), can affect the risk/benefit ratio for individual patients. This commentary discusses when the genomic information should be obtained during drug development and when it is to be assimilated into labeling and standards of care that can be used to "individualize" drug therapy and become one of the pillars of "personalized medicine."