Detecting bliss synergy in in vivo combination studies with a tumor kinetic model.

Linear models are generally reliable methods for analyzing tumor growth in vivo, with drug effectiveness being represented by the steepness of the regression slope. With immunotherapy, however, not all tumor growth follows a linear pattern, even after log transformation. Tumor kinetics models are mechanistic models that describe tumor proliferation and tumor killing macroscopically, through a set of differential equations. In drug combination studies, although an additional drug-drug interaction term can be added to such models, however, the drug interactions suggested by tumor kinetics models cannot be translated directly into synergistic effects. We have developed a novel statistical approach that simultaneously models tumor growth in control, monotherapy, and combination therapy groups. This approach makes it possible to test for synergistic effects directly and to compare such effects among different studies.

Therapeutic outcomes, assessments, risk factors and mitigation efforts of immunogenicity of therapeutic protein products.

Therapeutic protein products (TPPs) are of considerable value in the treatment of a variety of diseases, including cancer, hemophilia, and autoimmune diseases. The success of TPP mainly results from prolonged half-life, increased target specificity and decreased intrinsic toxicity compared with small molecule drugs. However, unwanted immune responses against TPP, such as generation of anti-drug antibody, can impact both drug efficacy and patient safety, which has led to requirements for increased monitoring in regulatory studies and clinical practice, termination of drug development, or even withdrawal of marketed products. We present an overview of current knowledge on immunogenicity of TPP and its impact on efficacy and safety. We also discuss methods for measurement and prediction of immunogenicity and review both product-related and patient-related risk factors that affect its development, and efforts that may be taken to mitigate it. Lastly, we discuss gaps in knowledge and technology and what is needed to fill these.

Mechanistic understanding of translational pharmacokinetic-pharmacodynamic relationships in nonclinical tumor models: a case study of orally available novel inhibitors of anaplastic lymphoma kinase.

The orally available novel small molecules PF06463922 [(10R)-7-amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(metheno)pyrazolo[4,3-h][2,5,11]benzoxadiazacyclotetradecine-3-carbonitrile] and PF06471402 [(10R)-7-amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(azeno)pyrazolo[4,3-h][2,5,11]benzoxadiazacyclo-tetradecine-3-carbonitrile] are second-generation anaplastic lymphoma kinase (ALK) inhibitors targeted to both naïve and resistant patients with non-small cell lung cancer (NSCLC) to the first-generation ALK inhibitor crizotinib. The objectives of the present study were to characterize and compare the pharmacokinetic-pharmacodynamic (PKPD) relationships of PF06463922 and PF06471402 for target modulation in tumor and antitumor efficacy in athymic mice implanted with H3122 NSCLC cells expressing a crizotinib-resistant echinoderm microtubule-associated protein-like 4 (EML4)-ALK mutation, EML4-ALK(L1196M). Furthermore, the PKPD relationships for these ALK inhibitors were evaluated and compared between oral administration and subcutaneous constant infusion (i.e., between different pharmacokinetic [PK] profiles). Oral and subcutaneous PK profiles of these ALK inhibitors were adequately described by a one-compartment PK model. An indirect response model extended with a modulator fit the time courses of PF06463922- and PF06471402-mediated target modulation (i.e., ALK phosphorylation) with an estimated unbound EC50,in vivo of 36 and 20 nM, respectively, for oral administration, and 100 and 69 nM, respectively, for subcutaneous infusion. A drug-disease model based on the turnover concept fit tumor growth curves inhibited by PF06463922 and PF06471402 with estimated unbound tumor stasis concentrations of 51 and 27 nM, respectively, for oral administration, and 116 and 70 nM, respectively, for subcutaneous infusion. Thus, the EC50,in vivo to EC60,in vivo estimates for ALK inhibition corresponded to the concentrations required tumor stasis in all cases, suggesting that the pharmacodynamic relationships of target modulation to antitumor efficacy were consistent among the ALK inhibitors, even when the PK profiles with different administration routes were considerably different.

Translational pharmacokinetic-pharmacodynamic modeling for an orally available novel inhibitor of anaplastic lymphoma kinase and c-Ros oncogene 1.

An orally available macrocyclic small molecule, PF06463922 [(10R)-7-amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(metheno)pyrazolo[4,3-h][2,5,11]benzoxadiazacyclotetradecine-3-carbonitrile], is a selective inhibitor of anaplastic lymphoma kinase (ALK) and c-Ros oncogene 1 (ROS1). The objectives of the present study were to characterize the pharmacokinetic-pharmacodynamic relationships of PF06463922 between its systemic exposures, pharmacodynamic biomarker (target modulation), and pharmacologic response (antitumor efficacy) in athymic mice implanted with H3122 non-small cell lung carcinomas expressing echinoderm microtubule-associated protein-like 4 (EML4)-ALK mutation (EML4-ALK(L1196M)) and with NIH3T3 cells expressing CD74-ROS1. In these nonclinical tumor models, PF06463922 was orally administered to animals with EML4-ALK(L1196M) and CD74-ROS1 at twice daily doses of 0.3-20 and 0.01-3 mg/kg per dose, respectively. Plasma concentration-time profiles of PF06463922 were adequately described by a one-compartment pharmacokinetic model. Using the model-simulated plasma concentrations, a pharmacodynamic indirect response model with a modulator sufficiently fit the time courses of target modulation (i.e., ALK phosphorylation) in tumors of EML4-ALK(L1196M)-driven models with EC50,in vivo of 36 nM free. A drug-disease model based on an indirect response model reasonably fit individual tumor growth curves in both EML4-ALK(L1196M)- and CD74-ROS1-driven models with the estimated tumor stasis concentrations of 51 and 6.2 nM free, respectively. Thus, the EC60,in vivo (52 nM free) for ALK inhibition roughly corresponded to the tumor stasis concentration in an EML4-ALK(L1196M)-driven model, suggesting that 60% ALK inhibition would be required for tumor stasis. Accordingly, we proposed that the EC60,in vivo for ALK inhibition corresponding to the tumor stasis could be considered a minimum target efficacious concentration of PF06463922 for cancer patients in a phase I trial.

A review of quantitative modeling of B cell responses to antigenic challenge.

A key role of B cells in the mammalian immune response is the generation of antibodies that serve to protect the organism against antigenic challenges. The same process may also be detrimental in the context of autoimmunity. Several modeling approaches have been applied to this aspect of the immune response, from predicting potential epitopes to describing B cells progress through developmental models and simulating antibody production. Here we review some of the modeling techniques, and summarize models that describe different activation mechanisms for B cells, including T cell dependent and independent models. We focus on viral infection as a prototype system, and briefly describe case studies in other disease areas such as bacterial infection and oncology. We single out aspects of the B cell response for which there are current knowledge gaps. We outline areas in need of further research in modeling applications to ultimately produce a "B cell module" for a complete immune response model.

Characterisation of cotadutide's dual GLP-1/glucagon receptor agonistic effects on glycaemic control using an in vivo human glucose regulation quantitative systems pharmacology model.

BACKGROUND AND PURPOSE: Cotadutide is a dual GLP-1 and glucagon receptor agonist with balanced agonistic activity at each receptor designed to harness the advantages on promoting liver health, weight loss and glycaemic control. We characterised the effects of cotadutide on glucose, insulin, GLP-1, GIP, and glucagon over time in a quantitative manner using our glucose dynamics systems model (4GI systems model), in combination with clinical data from a multiple ascending dose/Phase 2a (MAD/Ph2a) study in overweight and obese subjects with a history of Type 2 diabetes mellitus (NCT02548585). EXPERIMENTAL APPROACH: The cotadutide PK-4GI systems model was calibrated to clinical data by re-estimating only food related parameters. In vivo cotadutide efficacy was scaled based on in vitro potency. The model was used to explore the effect of weight loss on insulin sensitivity and predict the relative contribution of the GLP-1 and glucagon receptor agonistic effects on glucose. KEY RESULTS: Cotadutide MAD/Ph2a clinical endpoints were successfully predicted. The 4GI model captured a positive effect of weight loss on insulin sensitivity and showed that the stimulating effect of glucagon on glucose production counteracts the GLP-1 receptor-mediated decrease in glucose, resulting in a plateau for glucose decrease around a 200-µg cotadutide dose. CONCLUSION AND IMPLICATIONS: The 4GI quantitative systems pharmacology model was able to predict the clinical effects of cotadutide on glucose, insulin, GLP-1, glucagon and GIP given known in vitro potency. The analyses demonstrated that the quantitative systems pharmacology model, and its successive refinements, will be a valuable tool to support the clinical development of cotadutide and related compounds.

Application of target-mediated drug disposition model to small molecule heat shock protein 90 inhibitors.

Replacement of hydrogen with fluorine within three pairs of structurally similar small molecule inhibitors of heat shock protein 90 (HSP90) resulted in differences in inhibition constants (K(i)) in vitro as well as marked differences in rat intravenous pharmacokinetic profiles. The difference in pharmacokinetic profiles between lower and higher affinity inhibitors (LAIs and HAIs, respectively) was characterized by remarkably different estimates for steady-state volumes of distribution (V(ss): 1.8-2.0 versus 10-13 l/kg) with comparable clearance estimates (3.2-3.5 l/h per kilogram). When the observed V(ss) estimates were compared with the values predicted with the tissue-composition-based model, the observed V(ss) estimates for HAIs were 4- to 8-fold larger than the predicted values, whereas the V(ss) values for LAIs were comparable. Accordingly, a negative relationship between in vitro HSP90 K(i) versus in vivo V(ss) estimates was observed among these inhibitors. We therefore hypothesized that pharmacokinetic profiles of these inhibitors could be characterized by a target-mediated drug disposition (TMDD) model. In vivo equilibrium dissociation constant (K(D)) estimates for HAIs due to target binding by TMDD model with rapid binding approximation were 1-6 nM (equivalent to 0.3-2 nM free drug), which appeared comparable to the in vitro K(i) estimates (2-3 nM). In vivo KD values of LAIs were not accurately determined by the TMDD model, likely due to nonspecific binding-dependent tissue distribution obscuring TMDD profiles. Overall, these results suggest that the observed large Vss estimates for potent HSP90 inhibitors are likely due to pharmacological target binding.

Pharmacokinetic/pharmacodynamic modeling of crizotinib for anaplastic lymphoma kinase inhibition and antitumor efficacy in human tumor xenograft mouse models.

Crizotinib [Xalkori; PF02341066; (R)-3-[1-(2,6-dichloro-3-fluoro-phenyl)-ethoxy]-5-(1-piperidin-4-yl-1H-pyrazol-4-yl)-pyridin-2-ylamine] is an orally available dual inhibitor of anaplastic lymphoma kinase (ALK) and hepatocyte growth factor receptor. The objectives of the present studies were to characterize: 1) the pharmacokinetic/pharmacodynamic relationship of crizotinib plasma concentrations to the inhibition of ALK phosphorylation in tumors, and 2) the relationship of ALK inhibition to antitumor efficacy in human tumor xenograft models. Crizotinib was orally administered to athymic nu/nu mice implanted with H3122 non-small-cell lung carcinomas or severe combined immunodeficient/beige mice implanted with Karpas299 anaplastic large-cell lymphomas. Plasma concentration-time courses of crizotinib were adequately described by a one-compartment pharmacokinetic model. A pharmacodynamic link model reasonably fit the time courses of ALK inhibition in both H3122 and Karpas299 models with EC(50) values of 233 and 666 ng/ml, respectively. A tumor growth inhibition model also reasonably fit the time course of individual tumor growth curves with EC(50) values of 255 and 875 ng/ml, respectively. Thus, the EC(50) for ALK inhibition approximately corresponded to the EC(50) for tumor growth inhibition in both xenograft models, suggesting that >50% ALK inhibition would be required for significant antitumor efficacy (>50%). Furthermore, based on the observed clinical pharmacokinetic data coupled with the pharmacodynamic parameters obtained from the present nonclinical xenograft mouse model, >70% ALK inhibition was projected in patients with non-small-cell lung cancer who were administered the clinically recommended dosage of crizotinib, twice-daily doses of 250 mg (500 mg/day). The result suggests that crizotinib could sufficiently inhibit ALK phosphorylation for significant antitumor efficacy in patients.

The status of pharmacometrics in pregnancy: highlights from the 3(rd) American conference on pharmacometrics.

Physiological changes during pregnancy may alter drug pharmacokinetics. Therefore, mechanistic understanding of these changes and, ultimately, clinical studies in pregnant women are necessary to determine if and how dosing regimens should be adjusted. Because of the typically limited number of patients who can be recruited in this patient group, efficient design and analysis of these studies is of special relevance. This paper is a summary of a conference session organized at the American Conference of Pharmacometrics in April 2011, around the topic of applying pharmacometric methodology to this important problem. The discussion included both design and analysis of clinical studies during pregnancy and in silico predictions. An overview of different pharmacometric methods relevant to this subject was given. The impact of pharmacometrics was illustrated using a range of case examples of studies around pregnancy.

A novel integrated QSP model of in vivo human glucose regulation to support the development of a glucagon/GLP-1 dual agonist.

Glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1RAs) and dual GLP-1/glucagon receptor agonists improve glycaemic control and cause significant weight loss in patients with type 2 diabetes.1 These effects are driven in part by augmenting glucose-stimulated insulin release (incretin effect), reducing caloric intake and delayed gastric emptying. We developed and externally validated a novel integrated quantitative systems pharmacology (QSP) model to gain quantitative insight into the relative contributions and mechanisms of drugs modulating glucose regulatory pathways. This model (4GI model) incorporates known feedback mechanisms among glucose, GLP-1, glucagon, glucose-dependent insulinotropic peptide (GIP), and insulin after glucose provocation (i.e., food intake) and drug intervention utilizing published nonpharmacological and pharmacological (liraglutide, a GLP-1RA) data. The resulting model accurately describes the aforementioned mechanisms and independently predicts the effects of the GLP-1RAs (dulaglutide and semaglutide) on system dynamics. Therefore, the validated 4GI model represents a quantitative decision-making tool to support the advancement of novel therapeutics and combination strategies modulating these pathways.

Step-by-step comparison of ordinary differential equation and agent-based approaches to pharmacokinetic-pharmacodynamic models.

Mathematical models in oncology aid in the design of drugs and understanding of their mechanisms of action by simulation of drug biodistribution, drug effects, and interaction between tumor and healthy cells. The traditional approach in pharmacometrics is to develop and validate ordinary differential equation models to quantify trends at the population level. In this approach, time-course of biological measurements is modeled continuously, assuming a homogenous population. Another approach, agent-based models, focuses on the behavior and fate of biological entities at the individual level, which subsequently could be summarized to reflect the population level. Heterogeneous cell populations and discrete events are simulated, and spatial distribution can be incorporated. In this tutorial, an agent-based model is presented and compared to an ordinary differential equation model for a tumor efficacy model inhibiting the pERK pathway. We highlight strengths, weaknesses, and opportunities of each approach.

Pharmacokinetic-pharmacodynamic modeling of biomarker response and tumor growth inhibition to an orally available heat shock protein 90 inhibitor in a human tumor xenograft mouse model.

PF04942847 [2-amino-4-{4-chloro-2-[2-(4-fluoro-1H-pyrazol-1-yl)ethoxy]-6-methylphenyl}-N-(2,2-difluoropropyl)-5,7-dihydro-6H-pyrrolo[3,4-d]pyrimidine-6-carboxamide] was identified as an orally available, ATP-competitive, small-molecule inhibitor of heat shock protein 90 (HSP90). The objectives of the present study were: 1) to characterize the pharmacokinetic-pharmacodynamic relationship of the plasma concentrations of PF04942847 to the inhibition of HSP90-dependent protein kinase, AKT, as a biomarker and 2) to characterize the relationship of AKT degradation to tumor growth inhibition as a pharmacological response (antitumor efficacy). Athymic mice implanted with MDA-MB-231 human breast cancer cells were treated with PF04942847 once daily at doses selected to encompass ED(50) values. Plasma concentrations of PF04942847 were adequately described by a two-compartment pharmacokinetic model. A time delay (hysteresis) was observed between the plasma concentrations of PF04942847 and AKT degradation; therefore, a link model was used to account for the hysteresis. The model reasonably fit the time courses of AKT degradation with the estimated EC(50) of 18 ng/ml. For tumor growth inhibition, the signal transduction model reasonably fit the inhibition of individual tumor growth curves with the estimated EC(50) of 7.3 ng/ml. Thus, the EC(50) for AKT degradation approximately corresponded to the EC(50) to EC(80) for tumor growth inhibition, suggesting that 50% AKT degradation was required for significant antitumor efficacy (50-80%). The consistent relationship between AKT degradation and antitumor efficacy was also demonstrated by applying an integrated signal transduction model for linking AKT degradation to tumor growth inhibition. The present results will be helpful in determining the appropriate dosing regimen and guiding dose escalation to achieve efficacious systemic exposure in the clinic.

Ketorolac tromethamine: stereo-specific pharmacokinetics and single-dose use in postoperative infants aged 2-6 months.

OBJECTIVE: We determined the postoperative pharmacokinetics (PK), safety, and analgesic effects of ketorolac in 14 infants (aged <6 months) receiving a single intravenous (IV) administration of racemic ketorolac or placebo. BACKGROUND: Information on the PK of ketorolac in infants is limited. Unblinded studies suggest ketorolac may be useful in infants. METHODS: This double-blinded, placebo-controlled study enrolled 14 infants (aged <6 months) postoperatively. At 6-18 h after surgery, infants were randomized to receive placebo, 0.5 mg·kg(-1), or 1 mg·kg(-1) ketorolac IV. All infants received morphine sulfate as needed for pain control. Blood was collected up to 12-h postdosing. Analysis used noncompartmental and compartmental population modeling methods. RESULTS: In addition to noncompartmental and empirical Bayes PK modeling, data were integrated with a previously studied data set comprising 25 infants and toddlers (aged 6-18 months). A two-compartmental model described the comprehensive data set. The population estimates of the R (+) isomer were (%CV): central volume of distribution 1130 (10%) ml, peripheral volume of distribution 626 (25%) ml, and clearance from the central compartment 7.40 (8%) ml·min(-1). Those of the S (-) isomer were 1930 (15%) ml, 319 (58%) ml, and 39.5 (13%) ml·min(-1). Typical elimination half-lives were 191 and 33 min, respectively. There was a trend for increased clearance and central volume with increasing age and weight. The base model suggested that clearance of the S (-) isomer was weakly related to age; however, when body size adjustment was added to the model, no covariates were significant. Safety assessment showed no changes in renal or hepatic function tests, surgical drain output, or continuous oximetry between groups. Cumulative morphine administration showed large inter-patient variability and was not different between groups. CONCLUSION: Stereo-isomer-specific clearance of ketorolac in infants (aged 2-6 months) shows rapid elimination of the analgesic S (-) isomer as reported in infants aged 6-18 months. No adverse effects were seen after a single IV ketorolac dose.

Pharmacokinetic-Pharmacodynamic Modelling of Systemic IL13 Blockade by Monoclonal Antibody Therapy: A Free Assay Disguised as Total.

A sequential pharmacokinetic (PK) and pharmacodynamic (PD) model was built with Nonlinear Mixed Effects Modelling based on data from a first-in-human trial of a novel biologic, MEDI7836. MEDI7836 is a human immunoglobulin G1 lambda (IgG1λ-YTE) monoclonal antibody, with an Fc modification to reduce metabolic clearance. MEDI7836 specifically binds to, and functionally neutralizes interleukin-13. Thirty-two healthy male adults were enrolled into a dose-escalation clinical trial. Four active doses were tested (30, 105, 300, and 600 mg) with 6 volunteers enrolled per cohort. Eight volunteers received placebo as control. Following single subcutaneous administration (SC), individual time courses of serum MEDI7836 concentrations, and the resulting serum IL13 modulation in vivo, were quantified. A binding pharmacokinetic-pharmacodynamic (PK-PD) indirect response model was built to characterize the exposure-driven modulation of the target over time by MEDI7836. While the validated bioanalytical assay specification quantified the level of free target (i.e., a free IL13 assay), emerging clinical data suggested dose-dependent increase in systemic IL13 concentration over time, indicative of a total IL13 assay. The target time course was modelled as a linear combination of free target and a percentage of the drug-target complex to fit the clinical data. This novel PK-PD modelling approach integrates independent knowledge about the assay characteristics to successfully elucidate apparently complex observations.

IVGTT glucose minimal model covariate selection by nonlinear mixed-effects approach.

Population approaches, traditionally employed in pharmacokinetic-pharmacodynamic studies, have shown value also in the context of glucose-insulin metabolism models by providing more accurate individual parameters estimates and a compelling statistical framework for the analysis of between-subject variability (BSV). In this work, the advantages of population techniques are further explored by proposing integration of covariates in the intravenous glucose tolerance test (IVGTT) glucose minimal model analysis. A previously published dataset of 204 healthy subjects, who underwent insulin-modified IVGTTs, was analyzed in NONMEM, and relevant demographic information about each subject was employed to explain part of the BSV observed in parameter values. Demographic data included height, weight, sex, and age, but also basal glycemia and insulinemia, and information about amount and distribution of body fat. On the basis of nonlinear mixed-effects modeling, age, visceral abdominal fat, and basal insulinemia were significant predictors for SI (insulin sensitivity), whereas only age and basal insulinemia were significant for P2 (insulin action). The volume of distribution correlated with sex, age, percentage of total body fat, and basal glycemia, whereas no significant covariate was detected to explain variability in SG (glucose effectiveness). The introduction of covariates resulted in a significant shrinking of the unexplained BSV, especially for SI and P2 and considerably improved the model fit. These results offer a starting point for speculation about the physiological meaning of the relationships detected and pave the way for the design of less invasive and less expensive protocols for epidemiological studies of glucose-insulin metabolism.

Measurement of human surfactant protein-B turnover in vivo from tracheal aspirates using targeted proteomics.

We describe a method to measure protein synthesis and catabolism in humans without prior purification and use the method to measure the turnover of surfactant protein-B (SP-B). SP-B, a lung-specific, hydrophobic protein essential for fetal-neonatal respiratory transition, is present in only picomolar quantities in tracheal aspirate samples and difficult to isolate for dynamic turnover studies using traditional in vivo tracer techniques. Using infusion of [5,5,5-(2)H(3)] leucine and a targeted proteomics method, we measured both the quantity and kinetics of SP-B tryptic peptides in tracheal aspirate samples of symptomatic newborn infants. The fractional synthetic rate (FSR) of SP-B measured using the most abundant proteolytic fragment, a 10 amino acid peptide from the carboxy-terminus of proSP-B (SPTGEWLPR), from the circulating leucine pool was 0.035 +/- 0.005 h(-1), and the fractional catabolic rate was 0.044 +/- 0.003 h(-1). This technique permits high-throughput and sensitive measurement of turnover of low abundance proteins with minimal sample preparation.

Cellular signaling identifiability analysis: a case study.

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology.

Opportunities for Quantitative Translational Modeling in Oncology.

A 2-day meeting was held by members of the UK Quantitative Systems Pharmacology Network () in November 2018 on the topic of Translational Challenges in Oncology. Participants from a wide range of backgrounds were invited to discuss current and emerging modeling applications in nonclinical and clinical drug development, and to identify areas for improvement. This resulting perspective explores opportunities for impactful quantitative pharmacology approaches. Four key themes arose from the presentations and discussions that were held, leading to the following recommendations: Evaluate the predictivity and reproducibility of animal cancer models through precompetitive collaboration. Apply mechanism of action (MoA) based mechanistic models derived from nonclinical data to clinical trial data. Apply MoA reflective models across trial data sets to more robustly quantify the natural history of disease and response to differing interventions. Quantify more robustly the dose and concentration dependence of adverse events through mathematical modelling techniques and modified trial design.

Pharmacogenomic trial design: use of a PK/PD model to explore warfarin dosing interventions through clinical trial simulation.

OBJECTIVE: Variants of two genes, CYP2C9 and VKORC1, explain approximately one third of variability in warfarin maintenance dose requirements. However, the clinical utility of using this information in addition to clinical and demographic data ('pharmacogenomic-guidance') is unclear, as few comparative clinical trials have been conducted to date. The objective of this study was to explore the incremental effect of pharmacogenomic-guided warfarin dosing under various conditions using clinical trial simulation. METHODS: We used an existing pharmacokinetic/pharmacodynamic model to perform clinical trial simulations of pharmacogenomic-guided versus standard of care warfarin therapy. The primary outcome was the percentage of patient time spent in therapeutic range over the first month of therapy. We assessed the influence of the frequency of INR monitoring, and the use of a loading dose and dose increase delay in patients with CYP2C9 variants. RESULTS: Pharmacogenomic guidance resulted in a 3-4 percentage point absolute increase in time spent in therapeutic range over the first month of therapy compared with standard of care. The improvement in time in range was greater when the frequency of INR monitoring in both arms was assumed to be lower. The absolute difference increased to 6-8 percentage points with the use of a loading dose and dose increase delay in patients with a CYP2C9 variant. CONCLUSION: Our initial results imply that pharmacogenomic-guided warfarin dosing may be more useful in settings with less intensive patient follow-up, and when adjustments are made for slower therapeutic response in patients with a CYP2C9 variant. Further pharmacokinetic/pharmacodynamic model development may be useful for warfarin pharmacogenomic trial design.

Effects of cranberry juice on pharmacokinetics of beta-lactam antibiotics following oral administration.

Cranberry juice consumption is often recommended along with low-dose oral antibiotics for prophylaxis for recurrent urinary tract infection (UTI). Because multiple membrane transporters are involved in the intestinal absorption and renal excretion of beta-lactam antibiotics, we evaluated the potential risk of pharmacokinetic interactions between cranberry juice and the beta-lactams amoxicillin (amoxicilline) and cefaclor. The amoxicillin-cranberry juice interaction was investigated in 18 healthy women who received on four separate occasions a single oral test dose of amoxicillin at 500 mg and 2 g with or without cranberry juice cocktail (8 oz) according to a crossover design. A parallel cefaclor-cranberry juice interaction study was also conducted in which 500 mg cefaclor was administered with or without cranberry juice cocktail (12 oz). Data were analyzed by noncompartmental methods and nonlinear mixed-effects compartmental modeling. We conclude that the concurrent use of cranberry juice has no significant effect on the extent of oral absorption or the renal clearance of amoxicillin and cefaclor. However, delays in the absorption of amoxicillin and cefaclor were observed. These results suggest that the use of cranberry juice at usual quantities as prophylaxis for UTI is not likely to alter the pharmacokinetics of these two oral antibiotics.