A quantitative systems pharmacology model of plasma kallikrein-kinin system dysregulation in hereditary angioedema.

Hereditary angioedema (HAE) due to C1-inhibitor deficiency is a rare, debilitating, genetic disorder characterized by recurrent, unpredictable, attacks of edema. The clinical symptoms of HAE arise from excess bradykinin generation due to dysregulation of the plasma kallikrein-kinin system (KKS). A quantitative systems pharmacology (QSP) model that mechanistically describes the KKS and its role in HAE pathophysiology was developed based on HAE attacks being triggered by autoactivation of factor XII (FXII) to activated FXII (FXIIa), resulting in kallikrein production from prekallikrein. A base pharmacodynamic model was constructed and parameterized from literature data and ex vivo assays measuring inhibition of kallikrein activity in plasma of HAE patients or healthy volunteers who received lanadelumab. HAE attacks were simulated using a virtual patient population, with attacks recorded when systemic bradykinin levels exceeded 20 pM. The model was validated by comparing the simulations to observations from lanadelumab and plasma-derived C1-inhibitor clinical trials. The model was then applied to analyze the impact of nonadherence to a daily oral preventive therapy; simulations showed a correlation between the number of missed doses per month and reduced drug effectiveness. The impact of reducing lanadelumab dosing frequency from 300 mg every 2 weeks (Q2W) to every 4 weeks (Q4W) was also examined and showed that while attack rates with Q4W dosing were substantially reduced, the extent of reduction was greater with Q2W dosing. Overall, the QSP model showed good agreement with clinical data and could be used for hypothesis testing and outcome predictions.

Leveraging a physiologically-based quantitative translational modeling platform for designing B cell maturation antigen-targeting bispecific T cell engagers for treatment of multiple myeloma.

Bispecific T cell engagers (TCEs) are an emerging anti-cancer modality that redirects cytotoxic T cells to tumor cells expressing tumor-associated antigens (TAAs), thereby forming immune synapses to exert anti-tumor effects. Designing pharmacokinetically acceptable TCEs and optimizing their size presents a considerable protein engineering challenge, particularly given the complexity of intercellular bridging between T cells and tumor cells. Therefore, a physiologically-relevant and clinically-verified computational modeling framework is of crucial importance to understand the protein engineering trade-offs. In this study, we developed a quantitative, physiologically-based computational framework to predict immune synapse formation for a variety of molecular formats of TCEs in tumor tissues. Our model incorporates a molecular size-dependent biodistribution using the two-pore theory, extravasation of T cells and hematologic cancer cells, mechanistic bispecific intercellular binding of TCEs, and competitive inhibitory interactions by shed targets. The biodistribution of TCEs was verified by positron emission tomography imaging of [89Zr]AMG211 (a carcinoembryonic antigen-targeting TCE) in patients. Parameter sensitivity analyses indicated that immune synapse formation was highly sensitive to TAA expression, degree of target shedding, and binding selectivity to tumor cell surface TAAs over shed targets. Notably, the model suggested a "sweet spot" for TCEs' CD3 binding affinity, which balanced the trapping of TCEs in T-cell-rich organs. The final model simulations indicated that the number of immune synapses is similar (~55/tumor cell) between two distinct clinical stage B cell maturation antigen (BCMA)-targeting TCEs, PF-06863135 in an IgG format and AMG420 in a BiTE format, at their respective efficacious doses in multiple myeloma patients. This result demonstrates the applicability of the developed computational modeling framework to molecular design optimization and clinical benchmarking for TCEs, thus suggesting that this framework can be applied to other targets to provide a quantitative means to facilitate model-informed best-in-class TCE discovery and development.

Application of unbound liver-to-plasma concentration ratio to quantitative projection of cytochrome P450-mediated drug-drug interactions using physiologically based pharmacokinetic modelling approach.

1. This study evaluated the prediction accuracy of cytochrome P450 (CYP)-mediated drug-drug interaction (DDI) using minimal physiologically-based pharmacokinetic (PBPK) modelling incorporating the hepatic accumulation factor of an inhibitor (i.e. unbound liver/unbound plasma concentration ratio [Kp,uu,liver]) based on 22 clinical DDI studies. 2. Kp,uu,liver values were estimated using three methods: (1) ratio of cell-to-medium ratio in human cryopreserved hepatocytes (C/Mu) at 37 °C to that on ice (Kp,uu,C/M), (2) multiplication of total liver/unbound plasma concentration ratio (Kp,u,liver) estimated from C/Mu at 37 °C with unbound fraction in human liver homogenate (Kp,uu,cell) and (3) observed Kp,uu,liver in rats after intravenous infusion (Kp,uu,rat). 3. PBPK model using each Kp,uu,liver projected the area under the curve (AUC) increase of substrates more accurately than the model assuming a Kp,uu,liver of 1 for the average fold error and root mean square error did. Particularly, the model with a Kp,uu,liver of 1 underestimated the AUC increase of triazolam following co-administration with CYP3A4 inhibitor itraconazole by five-fold, whereas the AUC increase projected using the model incorporating the Kp,uu,C/M, Kp,uu,cell, or Kp,uu,rat of itraconazole and hydroxyitraconazole was within approximately two-fold of the actual value. 4. The results indicated that incorporating Kp,uu,liver into the PBPK model improved the accuracy of DDI projection.

Genetic and phenotypic variation in UGT2B17, a testosterone-metabolizing enzyme, is associated with BMI in males.

OBJECTIVE: A number of candidate gene and genome-wide association studies have identified significant associations between single nucleotide polymorphisms, particularly in FTO and MC4R, and body weight. However, the association between copy number variation and body weight is less understood. Anabolic androgenic steroids, such as testosterone, can regulate body weight. In humans, UDP-glucuronosyltransferase 2B17 (UGT2B17) metabolizes testosterone to a metabolite, which is readily excreted in urine. We investigate the association between genetic and phenotypic variation in UGT2B17 and body weight. MATERIALS AND METHODS: UGT2B17 deletion was genotyped and in-vivo UGT2B17 enzymatic activity (as measured by the 3-hydroxycotinine glucuronide to free 3-hydroxycotinine ratio) was measured in 400 Alaska Native individuals and 540 African Americans. RESULTS: In Alaska Native people, UGT2B17 deletion was strongly associated with lower BMI in male individuals (P<0.001), but not in female individuals, consistent with testosterone being a male dominant steroid. The sex-specific association between UGT2B17 deletion and lower BMI was also observed in African Americans (P=0.01 in male individuals). In both populations, UGT2B17 deletion was significantly associated with lower measured in-vivo UGT2B17 activity. In male individuals, lower in-vivo UGT2B17 activity was associated with lower BMI, as observed in the sex-specific genotypic association. CONCLUSION: These data suggest that UGT2B17 deletion leads to reduced UGT2B17 activity, and lower BMI in male individuals. This is consistent with the hypothesis that reduced UGT2B17-mediated testosterone excretion results in higher testosterone levels. Future studies could confirm this hypothesis by directly measuring serum testosterone levels.

Variation in P450 oxidoreductase (POR) A503V and flavin-containing monooxygenase (FMO)-3 E158K is associated with minor alterations in nicotine metabolism, but does not alter cigarette consumption.

The rates of nicotine metabolism differ widely, even after controlling for genetic variation in the major nicotine-metabolizing enzyme, CYP2A6. Genetic variants in an additional nicotine-metabolizing enzyme, flavin-containing monooxygenase (FMO)-3, and an obligate microsomal CYP-supportive enzyme, cytochrome P450 oxidoreductase (POR), were investigated. We examined the impact of FMO3 E158K and POR A503V before and after stratifying by CYP2A6 metabolism group. In 130 nonsmokers of African descent who received 4 mg oral nicotine, FMO3 158K trended toward slower nicotine metabolism in reduced CYP2A6 metabolizers (P=0.07) only, whereas POR 503V was associated with faster CYP2A6 activity (nicotine metabolite ratio) in normal (P=0.03), but not reduced, CYP2A6 metabolizers. Neither FMO3 158K nor POR 503V significantly altered the nicotine metabolic ratio (N=659), cigarette consumption (N=667), or urine total nicotine equivalents (N=418) in smokers of African descent. Thus, FMO3 E158K and POR A503V are minor sources of nicotine metabolism variation, insufficient to appreciably alter smoking.

Novel CYP2A6 variants identified in African Americans are associated with slow nicotine metabolism in vitro and in vivo.

OBJECTIVE: Nicotine, the main addictive ingredient in tobacco, is metabolically inactivated to cotinine primarily by the hepatic enzyme CYP2A6. Considerable genetic variation in the CYP2A6 gene results in large variation in the rates of nicotine metabolism, which in turn alters smoking behaviours (e.g. amount of cigarettes smoked, risk for dependence and success in smoking cessation). The aim of this study was to identify and characterize novel variants in CYP2A6. MATERIALS AND METHODS: The CYP2A6 gene from African American phenotypically slow nicotine metabolizers was sequenced and seven novel variants were identified [CYP2A6*39 (V68M), CYP2A6*40 (I149M), CYP2A6*41 (R265Q), CYP2A6*42 (I268T), CYP2A6*43 (T303I), CYP2A6*44 (E390K), CYP2A6*44 (L462P)]. Variants were introduced into a bi-cistronic cDNA expression construct containing CYP2A6 and P450 oxidoreductase and assessed for protein expression, enzymatic activity and stability as evaluated using western blotting and nicotine metabolism. Genotyping assays were developed and allelic frequencies were assessed in 534 African Americans. RESULTS: The variants showed significantly lower protein expression (P<0.001) when compared with the wild-type as well as reduced metabolism of nicotine to cotinine when controlling for cDNA expression using P450 oxidoreductase (P<0.001). The variants also showed reduced stability at 37°C. Allelic frequencies ranged from 0.1 to 0.6% with a collective genotype frequency of 3.2%; the impact in vitro correlated significantly with in-vivo activity (R(2)=0.40-0.48, P<0.05). Together, those with a novel variant had significantly lower nicotine metabolism in vivo than those without genetic variants (P<0.01). CONCLUSION: Here, we identified a number of novel variants with reduced/loss of CYP2A6 activity, increasing our understanding of CYP2A6 genetic variability.

Gene variants in CYP2C19 are associated with altered in vivo bupropion pharmacokinetics but not bupropion-assisted smoking cessation outcomes.

Bupropion is used clinically to treat depression and to promote smoking cessation. It is metabolized by CYP2B6 to its active metabolite hydroxybupropion, yet alterations in CYP2B6 activity have little impact on bupropion plasma levels. Furthermore, less than 10% of a bupropion dose is excreted as urinary bupropion and its characterized metabolites hydroxybupropion, threohydrobupropion, and erythrohydrobupropion, suggesting that alternative metabolic pathways may exist. In vitro data suggested CYP2C19 could metabolize bupropion. The current study investigated the impact of functional CYP2C19 genetic variants on bupropion pharmacokinetics and treatment outcomes. In 42 healthy volunteers, CYP2C19*2 (a reduced activity allele) was associated with higher bupropion area under the plasma concentration-time curve (AUC), but similar hydroxybupropion AUC. The mean bupropion AUC was 771 versus 670 hours⋅ng/ml in individuals with and without CYP2C19*2, respectively (P = 0.017). CYP2C19*2 was also associated with higher threohydrobupropion and erythrohydrobupropion AUC (P < 0.005). Adjusting for CYP2B6 genotype did not alter these associations, and CYP2C19 variants did not alter the utility of the hydroxybupropion/bupropion ratio as a measure of CYP2B6 activity. Finally, in a clinical trial of 540 smokers, CYP2C19 genotype was not associated with smoking cessation outcomes, supporting the hypothesis that bupropion response is mediated by hydroxybupropion, which is not altered by CYP2C19. In conclusion, our study reports the first in vivo evidence that reduced CYP2C19 activity significantly increases the steady-state exposure to bupropion and its reductive metabolites threohydrobupropion and erythrohydrobupropion. These pharmacokinetic changes were not associated with differences in bupropion's ability to promote smoking cessation in smokers, but may influence the side effects and toxicity associated with bupropion.

Alaska Native smokers and smokeless tobacco users with slower CYP2A6 activity have lower tobacco consumption, lower tobacco-specific nitrosamine exposure and lower tobacco-specific nitrosamine bioactivation.

Nicotine, the psychoactive ingredient in tobacco, is metabolically inactivated by CYP2A6 to cotinine. CYP2A6 also activates procarcinogenic tobacco-specific nitrosamines (TSNA). Genetic variation in CYP2A6 is known to alter smoking quantity and lung cancer risk in heavy smokers. Our objective was to investigate how CYP2A6 activity influences tobacco consumption and procarcinogen levels in light smokers and smokeless tobacco users. Cigarette smokers (n = 141), commercial smokeless tobacco users (n = 73) and iqmik users (n = 20) were recruited in a cross-sectional study of Alaska Native people. The participants' CYP2A6 activity was measured by both endophenotype and genotype, and their tobacco and procarcinogen exposure biomarker levels were also measured. Smokers, smokeless tobacco users and iqmik users with lower CYP2A6 activity had lower urinary total nicotine equivalents (TNE) and (methylnitrosamino)-1-(3)pyridyl-1-butanol (NNAL) levels (a biomarker of TSNA exposure). Levels of N-nitrosonornicotine (NNN), a TSNA metabolically bioactivated by CYP2A6, were higher in smokers with lower CYP2A6 activities. Light smokers and smokeless tobacco users with lower CYP2A6 activity reduce their tobacco consumption in ways (e.g. inhaling less deeply) that are not reflected by self-report indicators. Tobacco users with lower CYP2A6 activity are exposed to lower procarcinogen levels (lower NNAL levels) and have lower procarcinogen bioactivation (as indicated by the higher urinary NNN levels suggesting reduced clearance), which is consistent with a lower risk of developing smoking-related cancers. This study demonstrates the importance of CYP2A6 in the regulation of tobacco consumption behaviors, procarcinogen exposure and metabolism in both light smokers and smokeless tobacco users.

Pharmacogenetics of drug dependence: role of gene variations in susceptibility and treatment.

Drug dependency is a highly prevalent mental health disorder that imposes a significant burden on those directly affected, health care systems, and society in general. There is substantial heritability in the susceptibility to drug addiction, which indicates that there are genetic risk factors. Variation in the human genome is abundant and can directly affect drug dependency phenotypes, for example, by altering the function of a gene product or by altering gene expression. Pharmacogenetic studies can assess the effects of genetic variation on the risk for a particular phenotype (e.g., being an alcoholic). In addition, pharmacogenetic variability in treatment efficacy and adverse reactions can be investigated to identify particular genetic variants associated with altered responses. This review highlights examples of genetic variations that are important in the development and maintenance of specific drug dependencies as well as those that affect the response to treatment.

Influence of CYP2B6 genetic variants on plasma and urine concentrations of bupropion and metabolites at steady state.

BACKGROUND: Bupropion, an antidepressant and smoking cessation medication, is metabolized to hydroxybupropion (HB), an active metabolite, primarily by CYP2B6. OBJECTIVES: To compare plasma concentrations of bupropion and metabolites at steady state in healthy volunteers with and without CYP2B6 genetic variants. METHODS: In a genotype-guided study of 42 healthy individuals, we measured the plasma and urine concentrations of bupropion and its metabolites, HB, threohydrobupropion, and erythrohydrobupropion after 7 days of sustained-release bupropion dosing. RESULTS: CYP2B6*6 and *18 gene variants were associated with ~33% reduced concentrations of HB, with no effects on concentrations of bupropion or other metabolites. We could account for 50% of the variation in HB concentrations in a model including genotype and sex. CONCLUSION: As HB is active and its steady-state concentrations are more than 10 times higher than bupropion, CYP2B6 variants are likely to affect pharmacological activity. Because of the large individual variation within the genotype group, the use of therapeutic drug monitoring for dose optimization may be necessary.

CYP2A6 and CYP2B6 genetic variation and its association with nicotine metabolism in South Western Alaska Native people.

OBJECTIVES: Alaska Native (AN) people have a high prevalence of tobacco use and associated morbidity and mortality when compared with the general USA population. Variations in the CYP2A6 and CYP2B6 genes, encoding enzymes responsible for nicotine metabolic inactivation and procarcinogen activation, have not been characterized in AN and may contribute toward the increased risk. METHODS: AN people (n=400) residing in the Bristol Bay region of South Western Alaska were recruited for a cross-sectional study on tobacco use. They were genotyped for CYP2A6*1X2A, *1X2B, *1B, *2, *4, *7, *8, *9, *10, *12, *17, *35 and CYP2B6*4, *6, *9 and provided plasma and urine samples for the measurement of nicotine and metabolites. RESULTS: CYP2A6 and CYP2B6 variant frequencies among the AN Yupik people (n=361) were significantly different from those in other ethnicities. Nicotine metabolism [as measured by the plasma and urinary ratio of metabolites trans-3'-hydroxycotinine to cotinine (3HC/COT)] was significantly associated with CYP2A6 (P<0.001), but not CYP2B6 genotype (P=0.95) when controlling for known covariates. It was noteworthy that the plasma 3HC/COT ratios were high in the entire Yupik people, and among the Yupik CYP2A6 wild-type participants, they were substantially higher than those in previously characterized racial/ethnic groups (P<0.001 vs. Caucasians and African Americans). CONCLUSION: Yupik AN people have a unique CYP2A6 genetic profile that associated strongly with in-vivo nicotine metabolism. More rapid CYP2A6-mediated nicotine and nitrosamine metabolism in the Yupik people may modulate the risk of tobacco-related diseases.

Cannabinoid receptor stimulation increases motivation for nicotine and nicotine seeking.

The cannabinoid system appears to play a critical facilitative role in mediating the reinforcing effects of nicotine and relapse to nicotine-seeking behaviour in abstinent subjects based on the actions of cannabinoid (CB) receptor antagonists. However, the effects of CB receptor stimulation on nicotine self-administration and reinstatement have not been systematically studied. Here, we studied the effects of WIN 55,212-2, a CB1/2 agonist, on intravenous nicotine self-administration under fixed-ratio (FR) and progressive-ratio (PR) schedules of reinforcement in rats. The effects of WIN 55,212-2 on responding for food under similar schedules were also studied. In addition, the effects of WIN 55,212-2 on nicotine- and cue-induced reinstatement of nicotine seeking were also studied, as well as the effects of WIN 55,212-2 on nicotine discrimination. WIN 55,212-2 decreased nicotine self-administration under the FR schedule. However, co-administration of WIN 55,212-2 with nicotine decreased responding for food, which suggests that this effect was non-selective. In contrast, WIN 55,212-2 increased both nicotine self-administration and responding for food under the PR schedule, produced dose-dependent reinstatement of nicotine seeking, and enhanced the reinstatement effects of nicotine-associated cues. Some of these effects were reversed by the CB1 antagonist rimonabant, but not by the CB2 antagonist AM630. In the drug discrimination tests between saline and 0.4 mg/kg nicotine, WIN 55,212-2 produced no nicotine-like discriminative effects but significantly potentiated discriminative stimulus effects of nicotine at the low dose through a CB1-receptor-dependent mechanism. These findings indicate that cannabinoid CB1-receptor stimulation increases the reinforcing effects of nicotine and precipitates relapse to nicotine-seeking behaviour in abstinent subjects. Thus, modulating CB1-receptor signalling might have therapeutic value for treating nicotine dependence.

Applications of Quantitative System Pharmacology Modeling to Model-Informed Drug Development.

Significant advances in analytical technologies have dramatically improved our ability to deconvolute disease biology at molecular, cellular, and tissue levels. Quantitative system pharmacology (QSP) modeling is a computational framework to systematically integrate pharmaceutical properties of a drug candidate with scientific understanding of that deeper disease etiology, target expression, genetic variability, and human physiological processes, thus enabling more insightful drug development decisions related to efficacy and safety. In this chapter, we discuss the key attributes of QSP models in comparison to traditional models. We discuss a recommended four-step process to construct a QSP model to support drug development decisions. A number of illustrative QSP examples related to high-value drug development questions and decisions impacting target identification, lead generation and optimization, first in human studies, and clinical dose and schedule optimization are covered in the chapter. The future perspectives of QSP in the context of potential regulatory acceptance are also discussed.

Functional characterization of novel rare CYP2A6 variants and potential implications for clinical outcomes.

CYP2A6 activity, phenotyped by the nicotine metabolite ratio (NMR), is a predictor of several smoking behaviors, including cessation and smoking-related disease risk. The heritability of the NMR is 60-80%, yet weighted genetic risk scores (wGRSs) based on common variants explain only 30-35%. Rare variants (minor allele frequency <1%) are hypothesized to explain some of this missing heritability. We present two targeted sequencing studies where rare protein-coding variants are functionally characterized in vivo, in silico, and in vitro to examine this hypothesis. In a smoking cessation trial, 1687 individuals were sequenced; characterization measures included the in vivo NMR, in vitro protein expression, and metabolic activity measured from recombinant proteins. In a human liver bank, 312 human liver samples were sequenced; measures included RNA expression, protein expression, and metabolic activity from extracted liver tissue. In total, 38 of 47 rare coding variants identified were novel; characterizations ranged from gain-of-function to loss-of-function. On a population level, the portion of NMR variation explained by the rare coding variants was small (~1%). However, upon incorporation, the accuracy of the wGRS was improved for individuals with rare protein-coding variants (i.e., the residuals were reduced), and approximately one-third of these individuals (12/39) were re-assigned from normal to slow metabolizer status. Rare coding variants can alter an individual's CYP2A6 activity; their integration into wGRSs through precise functional characterization is necessary to accurately assess clinical outcomes and achieve precision medicine for all. Investigation into noncoding variants is warranted to further explain the missing heritability in the NMR.

Does sex alter the relationship between CYP2B6 variation, hydroxybupropion concentration and bupropion-aided smoking cessation in African Americans? A moderated mediation analysis.

BACKGROUND AND AIMS: CYP2B6, a genetically variable enzyme, converts bupropion to its active metabolite hydroxybupropion. CYP2B6 activity and bupropion-aided cessation differ between women and men. The aim of this study was to determine whether genetically normal (versus reduced) CYP2B6 activity increases bupropion-aided cessation in African American smokers via higher hydroxybupropion concentration, and whether this differs by sex. DESIGN AND SETTING: Secondary analysis of a smoking cessation clinical trial (NCT00666978). PARTICIPANTS/CASES: African American light smokers (≤ 10 cigarettes/day). INTERVENTIONS: Participants were treated with bupropion for 7 weeks. MEASUREMENTS: Participants with detectable bupropion and/or hydroxybupropion concentrations were divided into normal (n = 64) and reduced (n = 109) CYP2B6 activity groups based on the presence of decreased-function CYP2B6*6 and CYP2B6*18 alleles. Biochemically verified smoking cessation was assessed at week 3, end of treatment (7 weeks) and follow-up (26 weeks). FINDINGS: Normal (versus reduced) CYP2B6 activity was associated with increased cessation at week 7, which was mediated by higher hydroxybupropion concentration [odds ratio (OR) = 1.25, 95% confidence interval (CI) = 1.03, 1.78]; this mediation effect persisted at week 26 (OR = 1.23, 95% CI = 1.02, 1.70). The mediation effect was similar in women (n = 116; OR = 1.33, 95% CI = 1.01, 2.30) and men (n = 57; OR = 1.33, 95% CI = 0.92, 3.87). Moreover, sex did not appear to moderate the mediation effect, although this should be tested in a larger sample. CONCLUSIONS: In African American light smokers with verified early bupropion use, genetically normal CYP2B6 activity appears to be indirectly associated with greater smoking cessation success in a relationship mediated by higher hydroxybupropion concentration. The mediating effect of higher hydroxybupropion concentration on smoking cessation persists beyond the active treatment phase and does not appear to differ by sex.

Physiologically-Based Pharmacokinetic Modeling in Renal and Hepatic Impairment Populations: A Pharmaceutical Industry Perspective.

The predictive performance of physiologically-based pharmacokinetics (PBPK) models for pharmacokinetics (PK) in renal impairment (RI) and hepatic impairment (HI) populations was evaluated using clinical data from 29 compounds with 106 organ impairment study arms were collected from 19 member companies of the International Consortium for Innovation and Quality in Pharmaceutical Development. Fifty RI and 56 HI study arms with varying degrees of organ insufficiency along with control populations were evaluated. For RI, the area under the curve (AUC) ratios of RI to healthy control were predicted within twofold of the observed ratios for > 90% (N = 47/50 arms). For HI, > 70% (N = 43/56 arms) of the hepatically impaired to healthy control AUC ratios were predicted within twofold. Inaccuracies, typically overestimation of AUC ratios, occurred more in moderate and severe HI. PBPK predictions can help determine the need and timing of organ impairment study. It may be suitable for predicting the impact of RI on PK of drugs predominantly cleared by metabolism with varying contribution of renal clearance. PBPK modeling may be used to support mild impairment study waivers or clinical study design.

Quantitative Systems Pharmacology Approaches for Immuno-Oncology: Adding Virtual Patients to the Development Paradigm.

Drug development in oncology commonly exploits the tools of molecular biology to gain therapeutic benefit through reprograming of cellular responses. In immuno-oncology (IO) the aim is to direct the patient's own immune system to fight cancer. After remarkable successes of antibodies targeting PD1/PD-L1 and CTLA4 receptors in targeted patient populations, the focus of further development has shifted toward combination therapies. However, the current drug-development approach of exploiting a vast number of possible combination targets and dosing regimens has proven to be challenging and is arguably inefficient. In particular, the unprecedented number of clinical trials testing different combinations may no longer be sustainable by the population of available patients. Further development in IO requires a step change in selection and validation of candidate therapies to decrease development attrition rate and limit the number of clinical trials. Quantitative systems pharmacology (QSP) proposes to tackle this challenge through mechanistic modeling and simulation. Compounds' pharmacokinetics, target binding, and mechanisms of action as well as existing knowledge on the underlying tumor and immune system biology are described by quantitative, dynamic models aiming to predict clinical results for novel combinations. Here, we review the current QSP approaches, the legacy of mathematical models available to quantitative clinical pharmacologists describing interaction between tumor and immune system, and the recent development of IO QSP platform models. We argue that QSP and virtual patients can be integrated as a new tool in existing IO drug development approaches to increase the efficiency and effectiveness of the search for novel combination therapies.

A Minimal Physiologically-Based Pharmacokinetic Model Demonstrates Role of the Neonatal Fc Receptor (FcRn) Competition in Drug-Disease Interactions With Antibody Therapy.

Disease trajectories following antibody therapy can have a significant impact on the pharmacokinetics of the antibody. Although this phenomenon can often be explained by reduced target-expressing cells, other mechanisms may play a role. We use a novel minimal physiologically-based pharmacokinetic model to evaluate an alternative drug-disease interaction mechanism involving competitive inhibition of neonatal Fc receptor (FcRn)-mediated Immunoglobulin G recycling by paraproteins. The model is validated with clinical data from the anti-FcRn antibody M281 and is used to conduct a scenario test to quantify the interaction among M-protein, the characteristic paraprotein of multiple myeloma (MM), and the anti-CD38 antibody daratumumab indicated for MM treatment. Simulations predict up to a 3.6-fold increase in daratumumab half-life following M-protein reduction, which lends credence to the hypothesis that FcRn competition in MM can manifest as time-dependent reduction of clearance for daratumumab. This model can inform optimal dosing strategies for antibodies in MM and other pathologies of paraprotein excess.

A Citrulline-Based Translational Population System Toxicology Model for Gastrointestinal-Related Adverse Events Associated With Anticancer Treatments.

Gastrointestinal (GI)-related adverse events (AEs) are commonly observed in the clinic during cancer treatments. Citrulline is a potentially translatable biomarker of GI AEs. In this study, irinotecan-induced citrulline changes were studied for a range of doses and schedules in rats. A translational system toxicology model for GI AEs using citrulline was then developed based on new experimental data and parameters from a literature intestinal cell dynamic model. With the addition of feedback-development and tolerance-development mechanisms, the model well captured the plasma citrulline profiles after irinotecan treatment in rats. Subsequently, the model was translated to humans and predicted the observed GI AE dynamics in humans including dose-scheduling effect using the cytotoxic and feedback parameters estimated in rats with slight calibrations. This translational toxicology model could be used for other antineoplastic drugs to simulate various clinical dosing scenarios before human studies and mitigate potential GI AEs.

C57BL/6 Substrain Differences in Pharmacological Effects after Acute and Repeated Nicotine Administration.

Tobacco smoking is the major cause of disability and death in the United States and around the world. In addition, tobacco dependence and addiction express themselves as complex behaviors involving an interplay of genetics, environment, and psychological state. Mouse genetic studies could potentially elucidate the novel genes and/or gene networks regulating various aspects of nicotine dependence. Using the closely related C57BL/6 (B6) mice substrains, recent reports have noted phenotypic differences within C57BL/6J (B6J) and C57BL/6N (B6N) mice for some drugs of abuse: alcohol, opiates, and cocaine. However, the differences in nicotine's effects have not yet been described in these substrains. We examined the phenotypic differences in these substrains following the acute and repeated administration of nicotine in several pharmacological measures, including locomotion (after acute and repeated exposure), body temperature, nociception, and anxiety-like behaviors. We report substrain differences in the pharmacological effects of acute and repeated nicotine administration in the B6 substrains. Overall, we show enhanced nicotine sensitivity to locomotion, hypothermia, antinociception, and anxiety-like behaviors in the B6J mouse substrain compared to B6N. In the repeated administration paradigm, both the B6N and B6J substrains showed no sensitized locomotor responses after repeated exposure to nicotine at the two doses tested. This study thus provides evidence that the B6 mouse substrains may be useful for genetic studies to elucidate some of the genetic variants involved in tobacco dependence and addiction.