Pharmacokinetic Models for Inhaled Fluticasone Propionate and Salmeterol Xinafoate to Quantify Batch-to-Batch Variability

Advair Diskus is an essential treatment for asthma and chronic obstructive pulmonary disease. It is a dry powder inhaler with a combination of fluticasone propionate (FP) and salmeterol xinafoate (SX). However, the pharmacokinetics (PK) batch-to-batch variability of the reference-listed drug (RLD) hindered its generic product development. This work developed the PK models for inhaled FP and SX that could represent potential batch variability. Two batches each of the reference and the test product (R1, R2, T1, T2) of Advair Diskus (100 μg FP/50 μg SX inhalation) were administered to 60 healthy subjects in a 4-period, 4-sequence crossover study. The failure of the bioequivalence (BE) between R1 and R2 confirmed the high between-batch variability of the RLD. Non-linear mixed effect modeling was used to estimate the population mean PK parameters for each batch. For FP, a 2-compartment model with a sequential dual zero-order absorption best described the PK profile. For SX, a 2-compartment model with a first-order absorption model best fit the data. Both models were able to capture the plasma concentration, the maximum concentration, and the total exposure (AUCinf) adequately for each batch, which could be used to simulate the BE study in the future. In vitro properties were also measured for each batch, and the batch with a higher fraction of the fine particle (diameter < 1 µm, < 2 µm) had a higher AUCinf. This positive correlation for both FP and SX could potentially assist the batch selection for the PK BE study.

A convolution-based in vitro-in vivo correlation model for methylphenidate hydrochloride delayed-release and extended-release capsule

Delayed-release and extended-release methylphenidate hydrochloride (JORNAY PM®) is a novel capsule formulation of methylphenidate hydrochloride, used to treat attention deficit hyperactivity disorder in patients 6 years and older. In this paper, we develop a Level A in vitro-in vivo correlation (IVIVC) model for extended-release methylphenidate hydrochloride to support post-approval manufacturing changes by evaluating a point-to-point correlation between the fraction of drug dissolved in vitro and the fraction of drug absorbed in vivo. Dissolution data from an in vitro study of three different release formulations: fast, medium, and slow, and pharmacokinetic data from two in vivo studies were used to develop an IVIVC model using a convolution-based approach. The time-course of the drug concentration resulting from an arbitrary dose was considered as a function of the in vivo drug absorption and the disposition and elimination processes defined by the unit impulse response function using the convolution integral. An IVIVC was incorporated in the model due to the temporal difference seen in the scatterplots of the estimated fraction of drug absorbed in vivo and the fraction of drug dissolved in vitro and Levy plots. Finally, the IVIVC model was subjected to evaluation of internal predictability. This IVIVC model can be used to predict in vivo profiles for different in vitro profiles of extended-release methylphenidate hydrochloride.

Is There a Need for a Dedicated Pharmacokinetic Trial for a Drug in Obese Populations? A Drug Prioritization Decision Tree Framework

Obesity is a growing global health concern associated with high comorbidity rates, leading to an increasing number of patients who are obese requiring medication. However, clinical trials often exclude or under-represent individuals who are obese, creating the need for a methodology to adjust labeling to ensure safe and effective dosing for all patients. To address this, we developed a 2-part decision tree framework to prioritize drugs for dedicated pharmacokinetic studies in obese subjects. Leveraging current drug knowledge and modeling techniques, the decision tree system predicts expected exposure changes and recommends labeling strategies, allowing stakeholders to prioritize resources toward the drugs most in need. In a case study evaluating 30 drugs from literature across different therapeutic areas, our first decision tree predicted the expected direction of exposure change accurately in 73% of cases. We conclude that this decision tree system offers a valuable tool to advance research in obesity pharmacology and personalize drug development for patients who are obese, ensuring safe and effective medication.

Molecular Imaging to Study Antimicrobial Pharmacokinetics In Vivo

While antimicrobials are among the most prescribed drugs, the use of some older antibiotics is not optimized for efficacy in terms of dosage, route of administration, and duration of therapy. Knowledge gaps exist regarding the heterogeneous microenvironments within different infected tissues consisting of varying bacterial loads, immune responses, and drug gradients. Positron-emission tomography-based imaging, where radiolabeled drugs are visualized within the living body, enables accurate, holistic, and real-time determination of pharmacokinetics to provide valuable, actionable data to optimize antibiotic use. Here we briefly review the concepts, history, and recent progress in the field.

Bayesian model-guided antimicrobial therapy in pediatrics

Antimicrobials have transformed the practice of medicine, making life-threatening infections treatable, but determining optimal dosing, particularly in pediatric patients, remains a challenge. The lack of pediatric data can largely be traced back to pharmaceutical companies, which, until recently, were not required to perform clinical testing in pediatrics. As a result, most antimicrobial use in pediatrics is off-label. In recent years, a concerted effort (e.g., Pediatric Research Equality Act) has been made to fill these knowledge gaps, but progress is slow and better strategies are needed. Model-based techniques have been used by pharmaceutical companies and regulatory agencies for decades to derive rational individualized dosing guidelines. Historically, these techniques have been unavailable in a clinical setting, but the advent of Bayesian-model-driven, integrated clinical decision support platforms has made model-informed precision dosing more accessible. Unfortunately, the rollout of these systems remains slow despite their increasingly well documented contributions to patient-centered care. The primary goals of this work are to 1) provide a succinct, easy-to-follow description of the challenges associated with designing and implementing dose-optimization strategies; and 2) provide supporting evidence that Bayesian-model informed precision dosing can meet those challenges. There are numerous stakeholders in a hospital setting, and our intention is for this work to serve as a starting point for clinicians who recognize that these techniques are the future of modern pharmacotherapy and wish to become champions of that movement.

The Trajectory of Pharmacometrics to Support Drug Licensing & Labeling

The field of pharmacometrics has been responsible for countless advancements within the drug development space. In recent years, we have witnessed the implementation of both new and revived analytical methods to increase clinical trial success and even supplement the need for clinical trials all together. Throughout this article we will explore the path of pharmacometrics from its inception to present day. At this point in time, the target of drug development has been the average patient, and population approaches have primarily been utilized to support just that. The challenge we are now facing involves the translation from treating the typical patient to treating the real-world patient. For this reason, it is our opinion that future development efforts should account more for the individual. With advanced pharmacometric methods and growing technological infrastructure, precision medicine can become a development priority rather than a clinician's burden.

Evaluation of acquired antithrombin deficiency in paediatric patients supported on extracorporeal membrane oxygenation

AIMS

There remains a paucity of literature regarding best practice for antithrombin (AT) monitoring, dosing and dose-response in paediatric extracorporeal membrane oxygenation (ECMO) patients.

METHODS

We conducted a retrospective cohort study at a quaternary care paediatric intensive care unit in all patients <18 years of age supported on ECMO from 1 June 2011 to 30 April 2020. Adverse events and outcomes were characterized for all ECMO runs. AT activity and replacement were characterized and compared between two clinical protocols. AT activities measured post- vs. pre-AT replacement were compared in order to characterize a dose-response relationship.

RESULTS

The final cohort included 191 patients with 201 ECMO runs and 2028 AT activity measurements. The median AT activity was 65% (interquartile range [IQR], 51-82) and 879 (43.3%) measurements met the criteria of deficient. The overall median AT dose and increase in AT activity were 50.6 units/kg/dose (IQR, 39.5-67.2) and 23.5% (IQR, 9.8-36.0), respectively. In the protocol that restricted AT activity measurements to clinical scenarios concerning for heparin resistance, there was significantly higher dosing in conjunction with significantly fewer overall administrations. Approximately one third of AT activity remained deficient after repletion. There was no difference in mechanical complications, reasons for discontinuation of ECMO support, time on ECMO or survival between protocols.

CONCLUSIONS

There was a high prevalence of AT deficiency in paediatric ECMO patients. An AT replacement protocol based on evaluating heparin resistance is associated with fewer AT administrations, with similar circuit and patient outcomes. Further data are needed to identify optimal dosing strategies.

Population Pharmacokinetics of Vancomycin in Pregnant Women

Objective: Vancomycin is a glycopeptide antibacterial indicated for serious gram-positive infections. Pharmacokinetics (PK) of vancomycin have not been described in pregnant women. This study aims to characterize the PK disposition of vancomycin in pregnant women based on data acquired from a database of routine hospital care for therapeutic drug monitoring to better inform dosing decisions.

Methods: In this study, plasma drug concentration data from 34 pregnant hospitalized women who were administered intravenous vancomycin was analyzed. A population pharmacokinetic (PPK) model was developed using non-linear mixed effects modeling. Model selection was based on statistical criterion, graphical analysis, and physiologic relevance. Using the final model AUC_0-24 (PK efficacy index of vancomycin) was compared with non-pregnant population.

Results: Vancomycin PK in pregnant women were best described by a two-compartment model with first-order elimination and the following parameters: clearance (inter individual variability) of 7.64 L/hr (32%), central volume of 67.35 L, inter-compartmental clearance of 9.06 L/h, and peripheral volume of 37.5 L in a typical patient with 175 ml/min creatinine clearance (CRCL) and 45 kg fat-free mass (FFM). The calculated geometric mean of AUC_0-24 for the pregnant population was 223 ug.h/ ml and 226 ug.h/ ml for the non-pregnant population.

Conclusion: Our analysis suggests that vancomycin PK in pregnant women is consistent with non-pregnant adults and the dosing regimens used for non-pregnant patients may also be applicable to pregnant patients.

Defining longer term outcomes in an ovine model of moderate perinatal hypoxia-ischemia

Hypoxic-ischemic encephalopathy (HIE) is the leading cause of neonatal morbidity and mortality worldwide. Approximately 1 million infants born with HIE each year survive with cerebral palsy (CP) and/or serious cognitive disabilities. While infants born with mild and severe HIE frequently result in predictable outcomes, infants born with moderate HIE exhibit variable outcomes that are highly unpredictable. Here, we describe an umbilical cord occlusion (UCO) model of moderate HIE with a 6-day follow-up. Near term lambs (n=27) are resuscitated after the induction of 5 minutes of asystole. Following recovery, lambs are assessed to define neurodevelopmental outcomes. At the end of this period, lambs are euthanized, and brains harvested for histological analysis. Compared with prior models that typically follow lambs for 3 days, the observation of neurobehavioral outcomes for 6 days enables identification of animals that recover significant neurological function. Approximately 35 % of lambs exhibited severe motor deficits throughout the entirety of the 6-day course and, in the most severely affected lambs, developed spastic diparesis similar to that observed in infants who survive severe neonatal HIE (severe, UCOs). Importantly, and similar to outcomes in human neonates, while initially developing significant acidosis and encephalopathy, the remainder of the lambs in this model recovered normal motor activity and exhibited normal neurodevelopmental outcomes by 6 days of life (improved, UCOi). The UCOs group exhibited gliosis and inflammation in both white and gray matter, oligodendrocyte loss, and neuronal loss and cellular death in the hippocampus and cingulate cortex. While the UCOi group exhibited more cellular death and gliosis in the parasagittal cortex and demonstrated more preserved white matter markers, along with reduced markers of inflammation and lower cellular death and neuronal loss in Ca3 of the hippocampus compared with UCOs lambs. Our large animal model of moderate HIE with prolonged follow-up will help further define pathophysiologic drivers of brain injury while enabling identification of predictive biomarkers that correlate with disease outcomes and ultimately help support development of therapeutic approaches to this challenging clinical scenario.

Accelerating the Availability of Medications to Pediatric Patients by Optimizing the Use of Extrapolation of Efficacy

Improving pediatric therapeutic development is a mission of universal importance among health authorities, pharmaceutical companies, academic institutions, and healthcare professionals. Following the passage of legislation in the United States and Europe, we witnessed the most significant advancement yet in pediatric data generation, resulting in added pediatric use information to almost 700 product labels. Tools to accelerate generation of data for the pediatric population are available for use today, and when utilized in accordance with current practices and laws, these tools could increase the amount and timeliness of pediatric information available for clinicians and patients. If we utilize the current laws that allow regulators to incentivize and require evidence generation, apply extrapolation, and utilize modeling and simulation, as well as including adolescents in the pivotal studies alongside adults as appropriate, two strategic goals could be achieved by 2030: (1) reduce the time to pediatric approval by 50%, and (2) renew pediatric labeling information for 15 priority pediatric drugs without patent and/or exclusivity.

Dynamic PET-facilitated modeling and high-dose rifampin regimens for Staphylococcus aureus orthopedic implant-associated infections

Staphylococcus aureus is a major human pathogen causing serious implant–associated infections. Combination treatment with rifampin (10 to 15 mg/kg per day), which has dose-dependent activity, is recommended to treat S. aureus orthopedic implant–associated infections. Rifampin, however, has limited bone penetration. Here, dynamic 11C-rifampin positron emission tomography (PET) performed in prospectively enrolled patients with confirmed S. aureus bone infection (n = 3) or without orthopedic infection (n = 12) demonstrated bone/plasma area under the concentration-time curve ratio of 0.14 (interquartile range, 0.09 to 0.19), exposures lower than previously thought. PET-based pharmacokinetic modeling predicted rifampin concentration-time profiles in bone and facilitated studies in a mouse model of S. aureus orthopedic implant infection. Administration of high-dose rifampin (human equipotent to 35 mg/kg per day) substantially increased bone concentrations (2 mg/liter versus <0.2 mg/liter with standard dosing) in mice and achieved higher bacterial killing and biofilm disruption. Treatment for 4 weeks with high-dose rifampin and vancomycin was noninferior to the recommended 6-week treatment of standard-dose rifampin with vancomycin in mice (risk difference, −6.7% favoring high-dose rifampin regimen). High-dose rifampin treatment ameliorated antimicrobial resistance (0% versus 38%; P = 0.04) and mitigated adverse bone remodeling (P < 0.01). Last, whole-genome sequencing demonstrated that administration of high-dose rifampin in mice reduced selection of bacterial mutations conferring rifampin resistance (rpoB) and mutations in genes potentially linked to persistence. These data suggest that administration of high-dose rifampin is necessary to achieve optimal bone concentrations, which could shorten and improve treatments for S. aureus orthopedic implant infections.

Characterization of Drug-Drug Interactions on the Pharmacokinetic Disposition of Busulfan in Pediatric Patients during Hematopoietic Stem Cell Transplantation Conditioning

AIM

The study objective was to develop a population pharmacokinetic model for busulfan to comprehensively examine drug-drug interactions (DDIs) in pediatric patients undergoing hematopoietic stem cell transplantation. Currently, there is limited evidence to substantiate potential DDIs with busulfan.

METHODS

This retrospective study population was comprised of 250 patients receiving, on average, 0.8 mg/kg intravenous busulfan as pretreatment. All model analyses were conducted using non-linear mixed effects modeling in Pumas v2.0. The metabolic pathways of primary interest were glutathione conjugation and cytochrome P450 activity. Concomitant medications were categorized as CYP inhibitors, inducers, or GST depleters and included in the model as conditional covariates. A bootstrap simulation and visual predictive check were conducted to qualify the final model.

RESULTS

The final one-compartment model incorporates covariates of weight and age in relation to their effects on both total body clearance and volume of distribution. The estimated typical values of clearance and volume were 1.138 L/hr (CI: 1.095 - 1.179 L/hr) and 3.527 L (CI: 3.418 - 3.621 L), respectively. No significant changes in clearance were observed when medications that alter proposed hepatic and metabolic pathways of busulfan were coadministered.

CONCLUSION

To the best of our knowledge, this is the largest single center study of busulfan in children and the first to quantify the maturation effect of both clearance and volume. This study could not demonstrate a difference in busulfan clearance when comparing patients who received medications that alter the GST, CYP3A4, or CYP2C9 pathway to those who did not.

Understanding the Role of Pharmacometrics-Based Clinical Decision Support Systems in Pediatric Patient Management: A Case Study Using Lyv Software

Pharmacometrics could play a key role in shifting pediatric pharmacotherapy from dosing for an average patient to individualizing dosing. Clinicians can have these quantitative tools at their disposal without requiring significant training through the development of clinical decision support systems with easy-to-use interfaces that have a back-end analysis engine or pharmacometric model that uses extensive electronic health record data to predict an individualized dose for each patient. There has been increased development of these clinical decision support systems recently, and for these tools to make the proper breakthrough into clinical practice, it is of utmost importance to perform rigorous testing to ensure adequate predictive performance. In this article, we walk through the components of a decision support tool and the testing required to determine its robustness using an example of a decision support tool we developed for vancomycin dosing in pediatrics.

Application of a plasmin generation assay to define pharmacodynamic effects of tranexamic acid in women undergoing cesarean delivery

Essentials Tranexamic acid (TXA) is an antifibrinolytic drug used to reduce bleeding. Assaying plasmin generation (PG) in plasma detects clinically relevant TXA levels in vitro and ex vivo. 3.1-16.2 µg/mL TXA half-maximally inhibits PG in plasma from women undergoing cesarean delivery. PG velocity shows the strongest dose-relationship at low TXA concentrations (≤10 µg/mL). ABSTRACT: Background Tranexamic acid (TXA) is used to reduce bleeding. TXA inhibits plasmin(ogen) binding to fibrin and reduces fibrinolysis. TXA antifibrinolytic activity is typically measured by clot lysis assays; however, effects on plasmin generation (PG) are unclear due to a lack of tools to measure PG in plasma. Aims Develop an assay to measure PG kinetics in human plasma. Determine effects of TXA on PG and compare with fibrinolysis measured by rotational thromboelastometry (ROTEM). Methods We characterized effects of plasminogen, tissue plasminogen activator, fibrinogen, and α2 -antiplasmin on PG in vitro. We also studied effects of TXA on PG in plasma from 30 pregnant women administered intravenous TXA (5, 10, or 15 mg/kg) during cesarean delivery. PG was measured by calibrated fluorescence. PG parameters were compared with TXA measured by mass spectrometry and ROTEM of whole blood. Results The PG assay is specific for plasmin and sensitive to tissue plasminogen activator, fibrin(ogen), and α2 -antiplasmin. Addition of TXA to plasma in vitro dose dependently prolonged the clot lysis time and delayed and reduced PG. For all doses of TXA administered intravenously, the PG assay detected delayed time-to-peak (≤3 hours) and reduced the velocity, peak, and endogenous plasmin potential (≤24 hours) in plasma samples obtained after infusion. The PG time-to-peak, velocity, and peak correlated significantly with TXA concentration and showed less variability than the ROTEM lysis index at 30 minutes or maximum lysis. Conclusions The PG assay detects pharmacologically relevant concentrations of TXA administered in vitro and in vivo, and demonstrates TXA-mediated inhibition of PG in women undergoing cesarean delivery.

A Pharmacokinetic and Pharmacodynamic Investigation of an ε-Aminocaproic Acid Regimen Designed for Cardiac Surgery With Cardiopulmonary Bypass

OBJECTIVE

To investigate the pharmacokinetics and pharmacodynamics of an ε-aminocaproic acid (EACA) regimen designed for cardiac surgery with cardiopulmonary bypass (CPB).

DESIGN

Prospective observational study requiring blood sampling to measure EACA concentrations and fibrinolysis markers (fibrinogen, D-dimer, α₂-antiplasmin, and tissue plasminogen activator-plasminogen activator inhibitor [tPA-PAI-1] complex).

SETTING

Single-center, tertiary medical center.

PARTICIPANTS

Patients who underwent cardiac surgery with CPB between 2018 and 2019 for aortic or mitral valve replacement/repair or coronary artery bypass grafting. Previous sternotomy patients were included.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

The pharmacokinetics of EACA, during CPB, were described by a 3-compartment disposition model. EACA concentrations were greater than 130 mg/L in all patients after CPB and in most patients during CPB. The D-dimer level trended up and reached a peak median level of 1.35 mg/L of fibrinogen equivalence units (FEU) at 15 minutes after protamine administration. The median change in D-dimer (ΔD-dimer) from baseline to 15 minutes after protamine was 0.34 (-0.48 to 3.81) mg/L FEU. ΔD-dimer did not correlate with EACA concentration intraoperatively, urine output, body weight, glomerular filtration rate, cell salvage volume, and ultrafiltration volume. The median 24-hour chest tube output was 445 (180-1,011) mL.

CONCLUSION

This regimen provided maximum EACA concentrations near the time of protamine administration, with a total perioperative dose of 15 g. Most patients had EACA concentrations greater than the target during CPB. ΔD-dimer did not correlate with EACA concentration. The median 24-hour chest tube output compared well to similar studies that used higher doses of EACA.

Exposure-Response Analysis to Assess the Concentration-QTc Relationship of Psilocybin/Psilocin

Psilocybin is being developed for treating major depressive disorder. Psilocybin is readily dephosphorylated to psilocin upon absorption. The potential for psilocin proarrhythmic effect was assessed using a concentration-QTc interval (C-QTc) analysis from an open-label single ascending dose study of psilocybin. Psilocybin doses ranged from 0.3 to 0.6 mg/kg. This trial showed a significant but shallow C-QTc relationship. At the clinical dose of 25 mg, the mean psilocin maximum concentration is 18.7 ng/mL, and the associated mean (upper 90% confidence interval of mean) QTcF change is 2.1 (6.6) milliseconds. Given the short half-life of psilocin of about 4 hours, there would be no accumulation after monthly oral doses used in clinical trials. The upper limit of the 90% confidence interval of the model-predicted mean ΔQTcF crossed 10 milliseconds at a psilocin concentration of 31.1 ng/mL. At a supraclinical psilocin maximum concentration of about 60 ng/mL, ΔQTcF remains low, with a mean (upper limit of the 90% confidence interval) of 9.1 (17.9) milliseconds. This analysis enabled the characterization of the C-QTc relationship and prediction of QTc prolongation at the expected clinical and possible higher psilocybin doses.

Dynamic imaging in patients with tuberculosis reveals heterogeneous drug exposures in pulmonary lesions

Tuberculosis (TB) is the leading cause of death from a single infectious agent, requiring at least 6 months of multidrug treatment to achieve cure¹. However, the lack of reliable data on antimicrobial pharmacokinetics (PK) at infection sites hinders efforts to optimize antimicrobial dosing and shorten TB treatments². In this study, we applied a new tool to perform unbiased, noninvasive and multicompartment measurements of antimicrobial concentration-time profiles in humans³. Newly identified patients with rifampin-susceptible pulmonary TB were enrolled in a first-in-human study⁴ using dynamic [¹¹C]rifampin (administered as a microdose) positron emission tomography (PET) and computed tomography (CT). [¹¹C]rifampin PET-CT was safe and demonstrated spatially compartmentalized rifampin exposures in pathologically distinct TB lesions within the same patients, with low cavity wall rifampin exposures. Repeat PET-CT measurements demonstrated independent temporal evolution of rifampin exposure trajectories in different lesions within the same patients. Similar findings were recapitulated by PET-CT in experimentally infected rabbits with cavitary TB and confirmed using postmortem mass spectrometry. Integrated modeling of the PET-captured concentration-time profiles in hollow-fiber bacterial kill curve experiments provided estimates on the rifampin dosing required to achieve cure in 4 months. These data, capturing the spatial and temporal heterogeneity of intralesional drug PK, have major implications for antimicrobial drug development.

Noninvasive 11C-rifampin positron emission tomography reveals drug biodistribution in tuberculous meningitis

Tuberculous meningitis (TBM) is a devastating form of tuberculosis (TB), and key TB antimicrobials, including rifampin, have restricted brain penetration. A lack of reliable data on intralesional drug biodistribution in infected tissues has limited pharmacokinetic (PK) modeling efforts to optimize TBM treatments. Current methods to measure intralesional drug distribution rely on tissue resection, which is difficult in humans and generally limited to a single time point even in animals. In this study, we developed a multidrug treatment model in rabbits with experimentally induced TBM and performed serial noninvasive dynamic ¹¹C-rifampin positron emission tomography (PET) over 6 weeks. Area under the curve brain/plasma ratios were calculated using PET and correlated with postmortem mass spectrometry. We demonstrate that rifampin penetration into infected brain lesions is limited, spatially heterogeneous, and decreases rapidly as early as 2 weeks into treatment. Moreover, rifampin concentrations in the cerebrospinal fluid did not correlate well with those in the brain lesions. First-in-human ¹¹C-rifampin PET performed in a patient with TBM confirmed these findings. PK modeling predicted that rifampin doses (≥30 mg/kg) were required to achieve adequate intralesional concentrations in young children with TBM. These data demonstrate the proof of concept of PET as a clinically translatable tool to noninvasively measure intralesional antimicrobial distribution in infected tissues.

Population Pharmacokinetic Modeling of Gentamicin in Pediatrics

The primary objective of this work was to characterize the pharmacokinetics (PK) of gentamicin across the whole pediatric age spectrum from premature neonates to young adults with a single model by identifying significant clinical predictors. A nonlinear mixed-effect population PK model was developed with retrospective therapeutic drug-monitoring data. A total of 6459 drug concentration measurements from 3370 hospitalized patients were collected for model building (n = 2357) and evaluation (n = 1013). In agreement with previously reported models, a 2-compartment model with first-order elimination best described the drug PK. Patient-specific factors significantly impacting gentamicin clearance included fat-free mass, postmenstrual age, and serum creatinine (SCr). Based on our model, the deviation of the individual SCr from the age-dependent expected mean SCr value (SCrM) can result in a 40% lower clearance in a patient with renal impairment than that in a patient with normal kidney function, with SCrM:SCr ratios between 0.16 and 3.2 in this study. Consistent with the known age-dependent changes of the proportion of extracellular water in body weight, the inclusion of the impact of extracellular water maturation on the central volume of distribution was found to improve the model fitting significantly. In comparison with other published models, model evaluation suggested the developed model was the least biased and physiologically most representative. These results will be used to inform individualized initial dosing strategies and serve as a prior PK model for Bayesian updating and forecasting as individual clinical observations become available.

Could Postnatal Age-Related Uridine Diphosphate Glucuronic Acid Be a Rate-Limiting Factor in the Metabolism of Morphine During the First Week of Life?

Neonates experience dramatic changes in the disposition of drugs after birth as a result of enzyme maturation and environmental adjustment, challenging therapeutic decision making. In this research, we establish postnatal age, postmenstrual age, and body weight as physiologically reasonable predictors of morphine's clearance in neonates. By integrating knowledge of bilirubin, morphine, and other drugs metabolized by glucuronidation pathways from previously published studies, we hypothesize that uridine diphosphate glucuronic acid, a postnatal age-dependent sugar, plays an important role in the metabolism of morphine during the first week of life. This finding can be extended to other drugs metabolized by uridine diphosphate glucuronosyltransferase pathways in neonates and thus has important clinical implications for the use of drugs in this population.

Preservation of myocardial contractility during acute hypoxia with OMX-CV, a novel oxygen delivery biotherapeutic

The heart exhibits the highest basal oxygen (O₂) consumption per tissue mass of any organ in the body and is uniquely dependent on aerobic metabolism to sustain contractile function. During acute hypoxic states, the body responds with a compensatory increase in cardiac output that further increases myocardial O₂ demand, predisposing the heart to ischemic stress and myocardial dysfunction. Here, we test the utility of a novel engineered protein derived from the heme-based nitric oxide (NO)/oxygen (H-NOX) family of bacterial proteins as an O₂ delivery biotherapeutic (Omniox-cardiovascular [OMX-CV]) for the hypoxic myocardium. Because of their unique binding characteristics, H-NOX–based variants effectively deliver O₂ to hypoxic tissues, but not those at physiologic O₂ tension. Additionally, H-NOX–based variants exhibit tunable binding that is specific for O₂ with subphysiologic reactivity towards NO, circumventing a significant toxicity exhibited by hemoglobin (Hb)-based O₂ carriers (HBOCs). Juvenile lambs were sedated, mechanically ventilated, and instrumented to measure cardiovascular parameters. Biventricular admittance catheters were inserted to perform pressure-volume (PV) analyses. Systemic hypoxia was induced by ventilation with 10% O₂. Following 15 minutes of hypoxia, the lambs were treated with OMX-CV (200 mg/kg IV) or vehicle. Acute hypoxia induced significant increases in heart rate (HR), pulmonary blood flow (PBF), and pulmonary vascular resistance (PVR) (p < 0.05). At 1 hour, vehicle-treated lambs exhibited severe hypoxia and a significant decrease in biventricular contractile function. However, in OMX-CV–treated animals, myocardial oxygenation was improved without negatively impacting systemic or PVR, and both right ventricle (RV) and left ventricle (LV) contractile function were maintained at pre-hypoxic baseline levels. These data suggest that OMX-CV is a promising and safe O₂ delivery biotherapeutic for the preservation of myocardial contractility in the setting of acute hypoxia.

While hemoglobin is the primary oxygen delivery molecule used to maintain tissue oxygenation in metazoans, many organisms have other heme-containing proteins that can bind oxygen and other diatomic gases. Here, we tested whether a member of the H-NOX family of heme-containing proteins found in the thermostable bacterium Thermoanaerobacter tengcongensis can be engineered to deliver oxygen to severely hypoxic tissues in large mammals. This class of molecules has the advantage of high oxygen affinity and minimal nitric oxide reactivity. We demonstrate that these molecules can effectively deliver oxygen to a lamb heart with induced severe hypoxia, without overexposing the animal to oxygen or triggering systemic vascular reactivity. These molecules thus represent a novel class of oxygen delivery biotherapeutics to specifically target hypoxic tissue beds without the toxicity concerns of hemoglobin-based oxygen carriers. As tissue hypoxia is a central feature of many disease processes, this therapeutic approach may have broad clinical applicability.

Sorafenib Dose Recommendation in Acute Myeloid Leukemia Based on Exposure-FLT3 Relationship

Sorafenib administered at the approved dose continuously is not tolerated long-term in patients with acute myeloid leukemia (AML). The purpose of this study was to optimize the dosing regimen by characterizing the sorafenib exposure-response relationship in patients with AML. A one-compartment model with a transit absorption compartment and enterohepatic recirculation described the exposure. The relationship between sorafenib exposure and target modulation of kinase targets (FMS-like tyrosine kinase 3 (FLT3)-ITD and extracellular signal-regulated kinase (ERK)) were described by an inhibitory maximum effect (Emax ) model. Sorafenib could inhibit FLT3-ITD activity by 100% with an IC50 of 69.3 ng/mL and ERK activity by 84% with an IC50 of 85.7 ng/mL (both adjusted for metabolite potency). Different dosing regimens utilizing 200 or 400 mg at varying frequencies were simulated based on the exposure-response relationship. Simulations demonstrate that a 200 mg twice daily (b.i.d.) dosing regimen showed similar FLT3-ITD and ERK inhibitory activity compared with 400 mg b.i.d. and is recommended in further clinical trials in patients with AML.

Bayesian Forecasting Tool to Predict the Need for Antidote in Acute Acetaminophen Overdose

STUDY OBJECTIVE

Acetaminophen (APAP) overdose is the leading cause of acute liver injury in the United States. Patients with elevated plasma acetaminophen concentrations (PACs) require hepatoprotective treatment with N-acetylcysteine (NAC). These patients have been primarily risk-stratified using the Rumack-Matthew nomogram. Previous studies of acute APAP overdoses found that the nomogram failed to accurately predict the need for the antidote. The objectives of this study were to develop a population pharmacokinetic (PK) model for APAP following acute overdose and evaluate the utility of population PK model-based Bayesian forecasting in NAC administration decisions.

DESIGN, PATIENTS AND MEASUREMENTS

Limited APAP concentrations from a retrospective cohort of acute overdosed subjects from the Maryland Poison Center were used to develop the population PK model and to investigate the effect of type of APAP products and other prognostic factors. The externally validated population PK model was used a prior for Bayesian forecasting to predict the individual PK profile when one or two observed PACs were available. The utility of Bayesian forecasted APAP concentration-time profiles inferred from one (first) or two (first and second) PAC observations were also tested in their ability to predict the observed NAC decisions.

MAIN RESULTS

A one-compartment model with first-order absorption and elimination adequately described the data with single activated charcoal and APAP products as significant covariates on absorption and bioavailability. The Bayesian forecasted individual concentration-time profiles had acceptable bias (6.2% and 9.8%) and accuracy (40.5% and 41.9%) when either one or two PACs were considered, respectively. The sensitivity and negative predictive value of the Bayesian forecasted NAC decisions using one PAC were 84% and 92.6%, respectively.

CONCLUSION

The population PK analysis provided a platform for acceptably predicting an individual's concentration-time profile following acute APAP overdose with at least one PAC, and the individual's covariate profile, and can potentially be used for making early NAC administration decisions.

Exposure-response analysis after subcutaneous administration of RBP-7000, a once-a-month long-acting Atrigel formulation of risperidone

AIMS

A new, long-acting, subcutaneous (SC) formulation of risperidone (RBP-7000) has been developed for the treatment of schizophrenia to address issues of non-adherence associated with oral risperidone treatment. The objective of this work was to establish an exposure-response relationship between total active moiety (AM) plasma exposure (risperidone + 9-hydroxy-risperidone) and Positive and Negative Syndrome Scale (PANSS) or Clinical Global Impression severity (CGI-S) scores using data from a registration trial.

METHODS

This was a Phase 3 randomized, double-blind, placebo-controlled, multicenter study in 354 patients to evaluate the efficacy, safety and tolerability of RBP-7000 (90 mg and 120 mg). Non-linear mixed effects modelling was used to develop an integrated population pharmacokinetic/pharmacodynamic (PK/PD) model that included a joint PK model for risperidone and 9-hydroxy-risperidone with placebo and drug-effect models to establish the relation between total AM exposure and PANSS or CGI-S scores.

RESULTS

CYP2D6 poor and intermediate metabolizers had lower formation rates of 9-hydroxy-risperidone (94% and 76% lower, respectively) compared to the extensive CYP2D6 metabolizers. The maximum placebo-corrected relative decrease in PANSS score from baseline following RBP-7000 treatment was 5.4%, half of which could be achieved at plasma concentrations of 4.6 ng ml^-1 of the total AM. A proportional odds model for the CGI-S score related the total AM plasma concentration to the probability of improving/worsening scores over time.

CONCLUSIONS

Exposure-response analysis was established between total AM concentrations and PANSS and CGI-S scores, with good precision in parameter estimates. CYP2D6 phenotype on risperidone metabolism was the only identified covariate.

Allometry Is a Reasonable Choice in Pediatric Drug Development

Pharmacokinetics (PK) plays a key role in bridging drug efficacy and safety from adults to pediatric patients. The principal purpose of projecting dosing in pediatrics is to guide trial design, not to waive the study per se. This research was designed to evaluate whether the allometric scaling (AS) approach is a satisfactory method to design PK studies in pediatric patients aged 2 years and older. We systematically evaluated drugs that had pediatric label information updated from 1998 to 2015. Only intravenous (IV) or oral administration drugs with available PK information in both children and adults from FDA-approved labels were included. The allometric scaling approach was used to extrapolate adult clearance to pediatric clearance. The relative difference between the observed and the allometric scaling approach-predicted clearance was summarized and used to evaluate the predictive power of the allometric scaling approach. A total of 36 drugs eliminated by a metabolic pathway and 10 drugs by the renal pathway after intravenous (IV) or oral administration were included. Regardless of the administration route, elimination pathway, and age group, the allometric scaling approach can predict clearance in pediatric patients within a 2-fold difference; 18 of the included drugs were predicted within a 25% difference, and 31 drugs within a 50% difference. The allometric scaling approach can adequately design PK studies in pediatric subjects 2 years and older.

Population Pharmacokinetics of an Intranasally Administered Combination of Oxymetazoline and Tetracaine in Healthy Volunteers

The primary objective of the current investigation was to establish the pharmacokinetic characteristics of oxymetazoline and tetracaine's primary metabolite, para-butylaminobenzoic acid (PBBA), after the intranasal administration of oxymetazoline/tetracaine. Thirty-six subjects contributing a total of 1791 plasma concentration results from 2 open-label trials were utilized. Model development was achieved using data from the second trial (N = 24) in which 0.3 mg oxymetazoline/18 mg tetracaine was administered. External model validation utilized data from the first trial (N = 12), which included doses of 0.3 mg oxymetazoline/18 mg tetracaine and 0.6 mg oxymetazoline/36 mg tetracaine. Oxymetazoline and PBBA dispositions were described by a 2-compartment model with first-order absorption. An allometric model for body weight was included on volumes and clearances to describe unexplained between-subject variability. The final oxymetazoline parameter estimates were k_a 4.41 h^-1 ; peripheral volume 418 L; clearance 66.4 L/h; central volume 6.97 L; and intercompartmental clearance 419 L/h for a 70-kg subject. The final PBBA parameter estimates were k_a 8.51 h^-1 ; peripheral volume 32.0 L; clearance 16.7 L/h; central volume 29.8 L; and intercompartmental clearance 2.43 L/h for a 70-kg subject. Between-subject variability ranged from 14% to 39% for oxymetazoline and from 10% to 94% for PBBA.

Challenges in developing drugs for pediatric CNS disorders: A focus on psychopharmacology

Many psychiatric and behavioral disorders manifest in childhood (attention deficit hyperactivity disorder, obsessive compulsive disorder, anxiety, depression, schizophrenia, autism spectrum disorder, etc.) and the opportunity for intervening early may attenuate full development of the disorder and lessen long term disability. Yet, pediatric drug approvals for CNS indications are limited, and pediatric testing generally occurs only after establishing adult efficacy, more as an afterthought rather than with the initial goal of developing the medication for a pediatric CNS indication. With pharmaceutical companies decreasing funding of their neuroscience research divisions overall, the prospects for moving promising investigational drugs forward into pediatrics will only decline. The goal of this review is to highlight important challenges around pediatric drug development for psychiatric disorders, specifically during clinical development, and to present opportunities for filling these gaps, using new strategies for de-risking investigational drugs in new clinical trial designs/models. We will first present the current trends in pediatric drug efficacy testing in academic research and in industry trials, we will then discuss the regulatory landscape of pediatric drug testing, including policies intended to support and encourage more testing. Obstacles that remain will then be presented, followed by new designs, funding opportunities and considerations for testing investigational drugs safely.

Genetics-based pediatric warfarin dosage regimen derived using pharmacometric bridging

BACKGROUND

Warfarin dosage regimens using CYP2C9 and VKORC1 polymorphisms have been extensively studied in adults and is included in US Food and Drug Administration-approved warfarin labeling. However, no dosage algorithm is available for pediatric patients.

OBJECTIVE

To derive a genetics-based pediatric dosge regimen for warfarin, including starting dose and titration scheme.

METHODS

A model-based approach was developed based on a previously validated warfarin dosage model in adults, with subsequent comparison to pediatric data from pediatric warfarin dose, genotyping, and international normalized ratio (INR) results. The adult model was based on a previously established model from the CROWN (CReating an Optimal Warfarin dosing Nomogram) trial. Pediatric warfarin data were obtained from a study conducted at the Children's Hospital of Los Angeles with 26 subjects. Variant alleles of CYP2C9 (rs1799853 or *2, and rs1057910 or *3) and the VKORC1 single nucleotide polymorphism (SNP) rs9923231 (-1639 G>A) were assessed, where the rs numbers are reference SNP identification tags assigned by the National Center for Biotechnology Information.

RESULTS

A pediatric warfarin model was derived using the previously validated model and clinical pharmacology considerations. The model was validated, and clinical trial simulation and stochastic modeling were used to optimize pediatric dosage and titration. The final dosage regimen was optimized based on simulations targeting a high (≥60%) proportion of INRs within the therapeutic range by week 2 of warfarin therapy while minimizing INRs >3.5 or <2.

CONCLUSIONS

The proposed pediatric warfarin dosage scheme based on individual CYP2C9 (alleles *1,*2,*3) and VKORC1 rs9923231 (-1639 G>A) genotypes may offer improved dosage compared to current treatment strategies, especially in patients with variant CYP2C9 and VKORC1 alleles. This pilot study provides the foundation for a larger prospective evaluation of genetics-based warfarin dosage in pediatric patients.

Considerations in Analyzing Single-Trough Concentrations Using Mixed-Effects Modeling

The purpose of this study was to assess the effect of trial design and data analysis choices on the bias and precision of pharmacokinetic (PK) parameter estimation. NONMEM was used to simulate and analyze plasma concentrations collected according to a dense (five samples) or sparse (single-trough samples) sampling scheme for a one-compartment open model with intravenous administration. The results indicated that the bias on estimates of CL with only single-trough data was 17% compared to less than 1% for only dense data. The estimates of CL were improved by fixing all other parameters and estimating only mean and variance of CL (-11% to 1.4%, depending on the estimation method). Adding dense data led to further improvements (-2.3% to 0.3%, depending on further improvements). In these cases, first-order conditional estimation (FOCE) methods resulted in better estimates of CL than first-order (FO) methods. These steps also improved the Bayesian estimates of CL. These studies support the following recommendations: (1) avoid collecting single-trough concentrations unless there is reasonable knowledge about the PK of the drug; (2) if collecting single-trough concentrations is inevitable, avoid estimating all parameters when modeling single-trough concentration data; (3) use prior information by modeling the single-trough concentration data along with dense data from other studies; and (4) use Bayes estimates if the PK model and its parameters are known with reasonable certainty.

The Role of SN-38 Exposure,UGT1A1*28Polymorphism, and Baseline Bilirubin Level in Predicting Severe Irinotecan Toxicity

Irinotecan, an anticancer drug, is associated with severe and potentially fatal diarrhea and neutropenia. The objective of this analysis was to evaluate the role of SN-38 exposure, the active metabolite of irinotecan, UGT1A1 genotypes, and baseline bilirubin on the maximum decrease (nadir) in absolute neutrophil counts following irinotecan. This analysis extended the work of a previous study that examined the effect of UGT1A1 genotypes on the incidence of severe neutropenia in 86 advanced cancer patients following irinotecan treatment. Regression analysis showed that the absolute neutrophil count nadir depended on SN-38 exposure (AUC) and UGT1A1*28 homozygous 7/7 genotype. An increased SN-38 AUC and the 7/7 genotype were significantly associated with a lower absolute neutrophil count nadir (R2 = .49). An alternate model suggested that higher baseline bilirubin and the 7/7 genotype were also significantly associated with a lower absolute neutrophil count nadir, although with a lower coefficient of determination (R2 = .31). Based on these findings and other reports, the irinotecan label was modified to indicate the role of UGT1A1*28 polymorphism in the metabolism of irinotecan and the associated increased risk of severe neutropenia. The label modifications also included recommendations for lower starting doses of irinotecan in patients homozygous for the UGT1A1*28 (7/7) polymorphism.

Impact of pharmacometric analyses on new drug approval and labelling decisions: a review of 198 submissions between 2000 and 2008

Pharmacometric analyses have become an increasingly important component of New Drug Application (NDA) and Biological License Application (BLA) submissions to the US FDA to support drug approval, labelling and trial design decisions. Pharmacometrics is defined as a science that quantifies drug, disease and trial information to aid drug development, therapeutic decisions and/or regulatory decisions. In this report, we present the results of a survey evaluating the impact of pharmacometric analyses on regulatory decisions for 198 submissions during the period from 2000 to 2008. Pharmacometric review of NDAs included independent, quantitative analyses by FDA pharmacometricians, even when such analysis was not conducted by the sponsor, as well as evaluation of the sponsor's report. During 2000-2008, the number of reviews with pharmacometric analyses increased dramatically and the number of reviews with an impact on approval and labelling also increased in a similar fashion. We also present the impact of pharmacometric analyses on selection of paediatric dosing regimens, approval of regimens that had not been directly studied in clinical trials and provision of evidence of effectiveness to support a single pivotal trial. Case studies are presented to better illustrate the role of pharmacometric analyses in regulatory decision making.

Bayesian quantitative disease-drug-trial models for Parkinson's disease to guide early drug development

The problem we have faced in drug development is in its efficiency. Almost a half of registration trials are reported to fail mainly because pharmaceutical companies employ one-size-fits-all development strategies. Our own experience at the regulatory agency suggests that failure to utilize prior experience or knowledge from previous trials also accounts for trial failure. Prior knowledge refers to both drug-specific and nonspecific information such as placebo effect and the disease course. The information generated across drug development can be systematically compiled to guide future drug development. Quantitative disease-drug-trial models are mathematical representations of the time course of biomarker and clinical outcomes, placebo effects, a drug's pharmacologic effects, and trial execution characteristics for both the desired and undesired responses. Applying disease-drug-trial model paradigms to design a future trial has been proposed to overcome current problems in drug development. Parkinson's disease is a progressive neurodegenerative disorder characterized by bradykinesia, rigidity, tremor, and postural instability. A symptomatic effect of drug treatments as well as natural rate of disease progression determines the rate of disease deterioration. Currently, there is no approved drug which claims disease modification. Regulatory agency has been asked to comment on the trial design and statistical analysis methodology. In this work, we aim to show how disease-drug-trial model paradigm can help in drug development and how prior knowledge from previous studies can be incorporated into a current trial using Parkinson's disease model as an example. We took full Bayesian methodology which can allow one to translate prior information into probability distribution.

Pharmacometrics 2020

This special issue of the Journal of Clinical Pharmacology is dedicated to pharmacometrics, covering topics related to methodological research, application to decisions, standardization, PhRMA survey, and growth strategy. Innovative methodological and technological advances in analyzing disease, drug, and trial data have equipped pharmacometricians with the know-how to influence high-level decisions, which in turn creates more pharmacometric opportunities. Pharmacometrics is revolutionizing drug development and regulatory decision making. To sustain the success and growth of this field, we need to up the ante. Strategic goals for pharmacometric groups in industry, regulatory agencies, and academia are proposed in this report. These goals should be of significance to all stakeholders who have a vested interest in drug development and therapeutics. The future of pharmacometrics depends on how well we all can deliver on the strategic goals.

Exposure-response of posaconazole used for prophylaxis against invasive fungal infections: evaluating the need to adjust doses based on drug concentrations in plasma

The purpose of this article is to report the exposure-response (E-R) relationship of posaconazole oral suspension (POS) for prophylaxis against invasive fungal infections (IFIs), on the basis of the US Food and Drug Administration (FDA) clinical pharmacology review of two randomized, active-controlled clinical studies. Posaconazole average steady state plasma concentrations (C(avg)) ranged from 22 to 3,650 ng/ml after administration of POS 200 mg three times daily (t.i.d.). In a double-blind, randomized clinical trial, the quartile ranges of C(avg) with midpoint values of 289, 736, 1,239, and 2,607 ng/ml had clinical failure rates of 44, 21, 18, and 18%, respectively, indicating an inverse association between C(avg) and clinical failure rate. There were no significant relationships between C(avg) and posaconazole-related major adverse events. Determining posaconazole concentrations in plasma will aid in assessing the need for either POS dose adjustment (e.g., increasing the POS dose) or switching to another systemic antifungal drug, thereby improving the effectiveness of prophylaxis against IFIs.

Leveraging prior quantitative knowledge in guiding pediatric drug development: a case study

The manuscript presents the FDA's focus on leveraging prior knowledge in designing informative pediatric trial through this case study. In developing written request for Drug X, an anti-hypertensive for immediate blood pressure (BP) control, the sponsor and FDA conducted clinical trial simulations (CTS) to design trial with proper sample size and support the choice of dose range. The objective was to effectively use prior knowledge from adult patients for drug X, pediatric data from Corlopam (approved for a similar indication) trial and general experience in developing anti-hypertensive agents. Different scenarios governing the exposure response relationship in the pediatric population were simulated to perturb model assumptions. The choice of scenarios was based on the past observation that pediatric population is less responsive and sensitive compared with adults. The conceptual framework presented here should serve as an example on how the industry and FDA scientists can collaborate in designing the pediatric exclusivity trial. Using CTS, inter-disciplinary scientists with the sponsor and FDA can objectively discuss the choice of dose range, sample size, endpoints and other design elements. These efforts are believed to yield plausible trial design, qrational dosing recommendations and useful labeling information in pediatrics.

Biomarkers in clinical drug development

The primary purpose of this Commentary is to complement the description of biomarkers given in this issue in the Pharmaceutical Research and Manufacturers of America report by Lathia et al. I offer several examples of the use of biomarkers that highlight their value in drug development and regulatory decision making.

Endpoints and analyses to discern disease-modifying drug effects in early Parkinson's disease

Parkinson's disease is an age-related degenerative disorder of the central nervous system that often impairs the sufferer's motor skills and speech, as well as other functions. Symptoms can include tremor, stiffness, slowness of movement, and impaired balance. An estimated four million people worldwide suffer from the disease, which usually affects people over the age of 60. Presently, there is no precedent for approving any drug as having a modifying effect (i.e., slowing or delaying) for disease progression of Parkinson's disease. Clinical trial designs such as delayed start and withdrawal are being proposed to discern symptomatic and protective effects. The current work focused on understanding the features of delayed start design using prior knowledge from published and data submitted to US Food and Drug Administration (US FDA) as part of drug approval or protocol evaluation. Clinical trial simulations were conducted to evaluate the false-positive rate, power under a new statistical analysis methodology, and various scenarios leading to patient discontinuations from clinical trials. The outcome of this work is part of the ongoing discussion between the US FDA and the pharmaceutical industry on the standards required for demonstrating disease-modifying effect using delayed start design.

Quantitative disease, drug, and trial models

Quantitative disease-drug-trial models allow learning from prior experience and summarize the knowledge in a ready to apply format. Employing these models to plan future development is proposed as a powerful solution to improve pharmaceutical R&D productivity. The disease and trial models are, to a large extent, independent of the product, but the drug model is not. The goals are to apply the disease and trial models to future development and regulatory decisions, and publicly share them. We propose working definitions of these models, describe the various subcomponents, provide examples, and discuss the challenges and potential solutions for developing such models. Building useful disease-drug-trial models is a challenging task and cannot be achieved by any single organization. It requires a consorted effort by industry, academic, and regulatory scientists. We also describe the strategic goals of the FDA Pharmacometrics group.

Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004-2006

The End-of-Phase 2A meetings are proposed to identify opportunities to make innovative medical products available sooner and to increase the quality of drug applications through early meetings between sponsors and the FDA. This article summarizes the overall experience across 11 pilot End-of-Phase 2A meetings since 2004. Four case studies are presented in more detail to demonstrate the various issues and methods encountered at these meetings. Overall, industry and FDA scientists ranked these meetings to be "very helpful" (average score of 4 on a scale of 1 to 5). In almost all the instances the sponsors changed their drug development plans subsequent to these extensive quantitative analyses-based meetings. A draft Guidance is being developed to be issued in 2008, and we hope this initiative will be resourced by then.

Optimising piperacillin/tazobactam dosing in paediatrics

Piperacillin/tazobactam, an intravenous antibacterial combination product, has recently been approved for paediatric (age 2 months to 17 years) use in the USA. The purpose of this analysis is to describe the basis for the dosing recommendations in this age group. Pharmacokinetic (PK) parameters and demographic covariates from 53 children enrolled in two paediatric studies were used in the analysis. Individual drug clearance (CL) values calculated by non-compartmental methods were available. The influence of demographic covariates on CL was investigated by non-linear regression. The analysis identified CL to be dependent on body weight. CL was also found to be influenced by age in paediatric patients<or=2 years, which is consistent with the expectation based on maturation of renal function. The population PK analysis and simulations, utilising comparable adult exposures as a basis to explore optimal dosing, resulted in the following dosing recommendations: for paediatric patients>or=9 months, a dose of 100/12.5 mg/kg every 8h showed exposures similar to adults; for paediatric patients aged 2-9 months, the dose of 100/12.5 mg/kg should be reduced by a factor of 0.8 (i.e. 80/10 mg/kg), likely due to immature renal function. Based upon this analysis, dosing recommendations for paediatric patients down to 2 months of age were incorporated in the labelling. No data were available to allow additional recommendations for paediatric patients<2 months of age to be made.

Pharmacometrics at FDA: evolution and impact on decisions

Drug development and regulatory decisions are driven by information that is compiled primarily from clinical trials and other supportive experiments, but also through clinical experience in the post-market period. The wisdom of these decisions determines the efficiency of drug development, the decision to approve the drug, and the resultant drug product quality including guidance on how to use the product known as the label. Although the decisions are usually simple in nature (e.g., trial design and project progression at the company, product and labeling approval at the Food and Drug Administration (FDA)), the information informing the decision is complex and diverse.

Approval summary: sunitinib for the treatment of imatinib refractory or intolerant gastrointestinal stromal tumors and advanced renal cell carcinoma

PURPOSE

To describe the Food and Drug Administration (FDA) review and approval of sunitinib malate (Sutent). Sunitinib received regular approval for the treatment of gastrointestinal stromal tumor (GIST) after disease progression or intolerance to imatinib mesylate (Gleevec). Additionally, sunitinib received accelerated approval for the treatment of advanced renal cell carcinoma.

EXPERIMENTAL DESIGN

For the GIST indication, FDA reviewed data from a randomized, placebo-controlled trial with supportive evidence from a single-arm study. For the advanced renal cell carcinoma indication, FDA reviewed data from two single-arm studies of patients with cytokine-refractory metastatic renal cell carcinoma.

RESULTS

In patients with imatinib refractory or intolerant GIST, time-to-tumor progression of sunitinib-treated patients was superior to that of placebo-treated patients. Median time-to-tumor progression of sunitinib-treated patients was 27.3 weeks, compared with 6.4 weeks for placebo-treated patients (P < 0.0001). Partial responses were observed in 6.8% of sunitinib-treated patients. In patients with metastatic renal cell carcinoma, partial responses were observed in 25.5% (95% confidence interval, 17.5, 34.9) and 36.5% (95% confidence interval, 24.7, 49.6) of patients treated with sunitinib. Median response durations were 27.1 and 54 weeks. The most common adverse events attributed to sunitinib included diarrhea, mucositis, skin abnormalities, and altered taste. Reductions in left ventricular ejection fraction and severe hypertension were also more common in sunitinib-treated patients.

CONCLUSIONS

On January 26, 2006, the FDA approved sunitinib for the treatment of patients with imatinib refractory or intolerant GIST. Accelerated approval was granted for the treatment of advanced renal cell carcinoma.

Population pharmacokinetic-based dosing of intravenous busulfan in pediatric patients

The objective of this study was to characterize the pharmacokinetics (PK) of intravenous busulfan in pediatric patients and provide dosing recommendations. Twenty-four pediatric patients were treated with intravenous busulfan, 1.0 or 0.8 mg/kg for ages < or = 4 years or > 4 years, respectively, 4 times a day for 4 days. Dense PK sampling was performed. Body weight, age, gender, and body surface area were explored for effects on PK, and Monte Carlo simulations were performed to assess different dosing regimens. The PK of intravenous busulfan was described by a 1-compartment model with clearance of 4.04 L/h/20 kg and volume of distribution of 12.8 L/20 kg. Simulations indicated that the mg/kg and mg/m2 regimens were similar and achieved the desired target exposure in approximately 60% of patients. This model suggests that patients < or = 12 kg should be dosed at 1.1 mg/kg and those > 12 kg dosed at 0.8 mg/kg. Therapeutic drug monitoring and dose adjustment will further improve therapeutic targeting.

Impact of Pharmacometric Reviews on New Drug Approval and Labeling Decisions—a Survey of 31 New Drug Applications Submitted Between 2005 and 2006

Exploratory analyses of data pertaining to pharmacokinetic, pharmacodynamic, and disease progression are often referred to as the pharmacometrics (PM) analyses. The objective of the current report is to assess the role of PM, at the Food and Drug Administration (FDA), in drug approval and labeling decisions. We surveyed the impact of PM analyses on New Drug Applications (NDAs) reviewed over 15 months in 2005-2006. The survey focused on both the approval and labeling decisions through four perspectives: clinical pharmacology primary reviewer, their team leader, the clinical team member, and the PM reviewer. A total of 31 NDAs included a PM review component. Review of NDAs involved independent quantitative evaluation by FDA pharmacometricians. PM analyses were ranked as important in regulatory decision making in over 85% of the 31 NDAs. Case studies are presented to demonstrate the applications of PM analysis.