Pharmacokinetics, Efficacy, and Safety of a SARS-CoV-2 Antibody Treatment in Pediatric Participants: An Open-Label Addendum of a Placebo-Controlled, Randomized Phase 2/3 Trial

INTRODUCTION

Bamlanivimab and etesevimab (BAM + ETE) are monoclonal antibodies (mAbs) effective in reducing COVID-19-related hospitalizations and all-cause mortality in adult participants at increased risk for severe disease. We present pharmacokinetic (PK), efficacy, and safety results from pediatric participants (< 18 years of age) with COVID-19 who were treated with BAM + ETE.

METHODS

In an addendum to the phase 2/3 BLAZE-1 clinical trial (NCT04427501), pediatric participants received open-label weight-based dosing (WBD, n = 94) based on exposure-matching to the authorized dose of BAM + ETE in adult participants. For efficacy and safety assessments, placebo (n = 14) and BAM + ETE (n = 20)-treated adolescent participants (> 12 to < 18 years of age) from the BLAZE-1 trial were included in the overall pediatric population (N = 128). All participants had mild to moderate COVID-19 upon enrollment and ≥ 1 risk factor for severe COVID-19. The primary objective was to characterize the PK of BAM and ETE in the WBD population.

RESULTS

The median age of the participants was 11.2 years, 46.1% were female, 57.9% were Black/African American, and 19.7% were Hispanic/Latino. The area under the curve for BAM and ETE in the WBD population was similar to that previously observed in adults. There were no COVID-19-related hospitalizations or deaths. All adverse events (AE) except one were mild or moderate, with one participant reporting a serious AE.

CONCLUSION

WBD in pediatric participants achieved similar drug exposures compared to adult participants that received the authorized BAM + ETE dose. The pediatric efficacy and safety data were consistent with adults receiving mAbs for COVID-19.

TRIAL REGISTRATION NUMBER

NCT04427501.

Optimization of trial duration to predict long-term HbA1c change with therapy: A pharmacometrics simulation-based evaluation

Glycated hemoglobin (HbA1c) is the main biomarker of diabetes drug development. However, because of its delayed turnover, trial duration is rarely shorter than 12 weeks, and being able to predict long-term HbA1c with precision using data from shorter studies would be beneficial. The feasibility of reducing study duration was therefore investigated in this study, assuming a model-based analysis. The aim was to investigate the predictive performance of 24- and 52-week extrapolations using data from up to 4, 6, 8 or 12 weeks, with six previously published pharmacometric models of HbA1c. Predictive performance was assessed through simulation-based dose-response predictions and model averaging (MA) with two hypothetical drugs. Results were consistent across the methods of assessment, with MA supporting the results derived from the model-based framework. The models using mean plasma glucose (MPG) or nonlinear fasting plasma glucose (FPG) effect, driving the HbA1c formation, showed good predictive performance despite a reduced study duration. The models, using the linear effect of FPG to drive the HbA1c formation, were sensitive to the limited amount of data in the shorter studies. The MA with bootstrap demonstrated strongly that a 4-week study duration is insufficient for precise predictions of all models. Our findings suggest that if data are analyzed with a pharmacometric model with MPG or FPG with a nonlinear effect to drive HbA1c formation, a study duration of 8 weeks is sufficient with maintained accuracy and precision of dose-response predictions.

PK/PD modeling links accelerated resolution of COVID‐19‐related clinical symptoms to SARS‐CoV‐2 viral load reduction in patients following treatment with Bamlanivimab alone or Bamlanivimab and Etesevimab together

The relationship between severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) viral load reduction and disease symptom resolution remains largely undefined for coronavirus disease 2019 (COVID‐19). While the vaccine‐derived immunity takes time to develop, neutralizing monoclonal antibodies offer immediate, passive immunity to patients with COVID‐19. Bamlanivimab and etesevimab are two potent neutralizing monoclonal antibodies directed to the receptor binding domain of the spike protein of SARS‐CoV‐2. This study aims to describe the relationship between viral load and resolution of eight common COVID‐19‐related symptoms in patients following treatment with neutralizing monoclonal antibodies (bamlanivimab alone or bamlanivimab and etesevimab together), in a phase II clinical trial. Corresponding pharmacokinetics (PKs), viral load, and COVID‐19‐related symptom data were modeled using Nonlinear Mixed Effects Modeling to describe the time‐course of eight COVID‐19‐related symptoms in an ordered categorical manner (none, mild, moderate, and severe), following administration of bamlanivimab or bamlanivimab and etesevimab together to participants with COVID‐19. The PK/pharmacodynamic (PD) models characterized the exposure‐viral load‐symptom time course of the eight preselected COVID‐19‐related symptoms. Baseline viral load (BVL), change in viral load from baseline, and time since the onset of symptoms, demonstrated statistically significant effects on symptom score probabilities. Higher BVL generally indicated an increased probability of symptom severity. The severity of symptoms decreased over time, partially driven by the decrease in viral load. The effect of increasing time resulting in decreased severity of symptoms was over and above the effect of decreasing viral load. Administration of bamlanivimab alone or together with etesevimab results in a faster time to resolution of COVID‐19‐related symptoms compared to placebo.

A Quantitative Modeling and Simulation Framework to Support Candidate and Dose Selection of Anti-SARS-CoV-2 Monoclonal antibodies to Advance Bamlanivimab into a First-in-Human Clinical Trial

Neutralizing monoclonal antibodies (mAb), novel therapeutics for the treatment of coronavirus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2), have been urgently researched from the start of the pandemic. The selection of the optimal mAb candidate and therapeutic dose were expedited using open‐access in silico models. The maximally effective therapeutic mAb dose was determined through two approaches; both expanded on innovative, open‐science initiatives. A physiologically‐based pharmacokinetic (PBPK) model, incorporating physicochemical properties predictive of mAb clearance and tissue distribution, was used to estimate mAb exposure that maintained concentrations above 90% inhibitory concentration of in vitro neutralization in lung tissue for up to 4 weeks in 90% of patients. To achieve fastest viral clearance following onset of symptoms, a longitudinal SARS‐CoV‐2 viral dynamic model was applied to estimate viral clearance as a function of drug concentration and dose. The PBPK model‐based approach suggested that a clinical dose between 175 and 500 mg of bamlanivimab would maintain target mAb concentrations in the lung tissue over 28 days in 90% of patients. The viral dynamic model suggested a 700 mg dose would achieve maximum viral elimination. Taken together, the first‐in‐human trial (NCT04411628) conservatively proceeded with a starting therapeutic dose of 700 mg and escalated to higher doses to evaluate the upper limit of safety and tolerability. Availability of open‐access codes and application of novel in silico model‐based approaches supported the selection of bamlanivimab and identified the lowest dose evaluated in this study that was expected to result in the maximum therapeutic effect before the first‐in‐human clinical trial.

Development and Verification of a Body Weight-Directed Disease Trial Model for Glucose Homeostasis

Weight loss has been associated with improvement in insulin sensitivity. It is consequently a cornerstone in the management of type 2 diabetes mellitus (T2DM). However, the strictly quantitative relationship between weight loss, insulin sensitivity, and clinically relevant glucose homeostasis biomarkers as well as changes therein as T2DM progresses is not yet fully understood. Therefore, the objective of our research was to establish a body weight-directed disease trial model for glucose homeostasis. To that end, we conducted a model-based meta-analysis using time course data of body weight loss (following lifestyle change or surgical procedure) and corresponding improvement of insulin sensitivity expressed as the Matsuda index. Changes in body weight were best described by a sigmoidal E_max model, whereas changes in the Matsuda index were best described by a linear model with a slope of 3.49. Once developed and verified, the model-based meta-analysis was linked to a disease-drug trial model for T2DM previously developed by our group to characterize and predict the impact of weight loss on clinically relevant glucose homeostasis biomarkers. The joint model was then used to conduct clinical trial simulations, which showed that weight loss can greatly improve clinically relevant glucose homeostasis biomarkers in T2DM patients.

Simulation-Based Evaluation of Dose-Titration Algorithms for Rapid-Acting Insulin in Subjects with Type 2 Diabetes Mellitus Inadequately Controlled on Basal Insulin and Oral Antihyperglycemic Medications

BACKGROUND

The purpose of this prospective, model-based simulation approach was to evaluate the impact of various rapid-acting mealtime insulin dose-titration algorithms on glycemic control (hemoglobin A1c [HbA1c]).

METHODS

Seven stepwise, glucose-driven insulin dose-titration algorithms were evaluated with a model-based simulation approach by using insulin lispro. Pre-meal blood glucose readings were used to adjust insulin lispro doses. Two control dosing algorithms were included for comparison: no insulin lispro (basal insulin+metformin only) or insulin lispro with fixed doses without titration.

RESULTS

Of the seven dosing algorithms assessed, daily adjustment of insulin lispro dose, when glucose targets were met at pre-breakfast, pre-lunch, and pre-dinner, sequentially, demonstrated greater HbA1c reduction at 24 weeks, compared with the other dosing algorithms. Hypoglycemic rates were comparable among the dosing algorithms except for higher rates with the insulin lispro fixed-dose scenario (no titration), as expected. The inferior HbA1c response for the "basal plus metformin only" arm supports the additional glycemic benefit with prandial insulin lispro.

CONCLUSIONS

Our model-based simulations support a simplified dosing algorithm that does not include carbohydrate counting, but that includes glucose targets for daily dose adjustment to maintain glycemic control with a low risk of hypoglycemia.

Dose-finding results in an adaptive, seamless, randomized trial of once-weekly dulaglutide combined with metformin in type 2 diabetes patients (AWARD-5)

AIMS

AWARD-5 was an adaptive, seamless, double-blind study comparing dulaglutide, a once-weekly glucagon-like peptide-1 (GLP-1) receptor agonist, with placebo at 26 weeks and sitagliptin up to 104 weeks. The study also included a dose-finding portion whose results are presented here.

METHODS

Type 2 diabetes (T2D) patients on metformin were randomized 3 : 1 : 1 to seven dulaglutide doses, sitagliptin (100 mg), or placebo. A Bayesian algorithm was used for randomization and dose selection. Patients were adaptively randomized to dulaglutide doses using available data on the basis of a clinical utility index (CUI) of glycosylated haemoglobin A1c (HbA1c) versus sitagliptin at 52 weeks and weight, pulse rate (PR) and diastolic blood pressure (DBP) versus placebo at 26 weeks. The algorithm randomly assigned patients until two doses were selected.

RESULTS

Dulaglutide 1.5 mg was determined to be the optimal dose. Dulaglutide 0.75 mg met criteria for the second dose. Dulaglutide 1.5 mg showed the greatest Bayesian mean change from baseline (95% credible interval) in HbA1c versus sitagliptin at 52 weeks -0.63 (-0.98 to -0.20)%. Dulaglutide 2.0 mg showed the greatest placebo-adjusted mean change in weight [-1.99 (-2.88 to -1.20) kg] and in PR [0.78 (-2.10 to 3.80) bpm]. Dulaglutide 1.5 mg showed the greatest placebo-adjusted mean change in DBP [-0.62 (-3.40 to 2.30) mmHg].

CONCLUSIONS

The Bayesian algorithm allowed for an efficient exploration of a large number of doses and selected dulaglutide doses of 1.5 and 0.75 mg for further investigation in this trial.

The effects of LY2405319, an FGF21 analog, in obese human subjects with type 2 diabetes

Fibroblast growth factor 21 (FGF21) is a recently discovered metabolic regulator. Exogenous FGF21 produces beneficial metabolic effects in animal models; however, the translation of these observations to humans has not been tested. Here, we studied the effects of LY2405319 (LY), a variant of FGF21, in a randomized, placebo-controlled, double-blind proof-of-concept trial in patients with obesity and type 2 diabetes. Patients received placebo or 3, 10, or 20 mg of LY daily for 28 days. LY treatment produced significant improvements in dyslipidemia, including decreases in low-density lipoprotein cholesterol and triglycerides and increases in high-density lipoprotein cholesterol and a shift to a potentially less atherogenic apolipoprotein concentration profile. Favorable effects on body weight, fasting insulin, and adiponectin were also detected. However, only a trend toward glucose lowering was observed. These results indicate that FGF21 is bioactive in humans and suggest that FGF21-based therapies may be effective for the treatment of selected metabolic disorders.

Drug delivery trends in clinical trials and translational medicine: growth in biologic molecule development and impact on rheumatoid arthritis, Crohn's disease, and colitis

There are 94,709 clinical trials across 179 countries. Approximately half (47,467) are related to the three categories within the scope of the free online resource "Drug Delivery Trends in Clinical Trials and Translational Medicine," which are (1) drug delivery technology and systems, (2) biological molecule platforms, and (3) pharmacokinetic and pharmacodynamic interactions. In this commentary, trends in biological molecule platforms and their impacts are discussed. The sales of top 15 biologic drugs have reached over $63 billion in 2010. In the past 10 years, major pharmaceutical companies have acquired biological molecule platforms and have become integrated biopharmaceutical companies, highlighting the role of biotechnology in driving new therapeutic product development. The top three products--Remicade, Enbrel, and Humira--indicated for arthritis and colitis and targeted to tumor necrosis factor-alpha (TNF-α), each generated over $6 billion in annual sales. In addition to TNF-α, biologic candidates targeted to other inflammatory molecules are in clinical development, partly driven by commercial interests and medical need. Although clinical experience indicates that all the anti-TNF-α molecular platforms are effective for rheumatoid arthritis, Crohn's disease, and colitis, whether the new agents can provide additional relief or cures remains to be seen.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 3: comparative assessement of prediction methods of human clearance

The objective of this study was to evaluate the performance of various allometric and in vitro-in vivo extrapolation (IVIVE) methodologies with and without plasma protein binding corrections for the prediction of human intravenous (i.v.) clearance (CL). The objective was also to evaluate the IVIVE prediction methods with animal data. Methodologies were selected from the literature. Pharmaceutical Research and Manufacturers of America member companies contributed blinded datasets from preclinical and clinical studies for 108 compounds, among which 19 drugs had i.v. clinical pharmacokinetics data and were used in the analysis. In vivo and in vitro preclinical data were used to predict CL by 29 different methods. For many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. In addition, 66 methods of predicting oral (p.o.) area under the curve (AUCp.o. ) were evaluated for 107 compounds using rational combinations of i.v. CL and bioavailability (F), and direct scaling of observed p.o. CL from preclinical species. Various statistical and outlier techniques were employed to assess the predictability of each method. Across methods, the maximum success rate in predicting human CL for the 19 drugs was 100%, 94%, and 78% of the compounds with predictions falling within 10-fold, threefold, and twofold error, respectively, of the observed CL. In general, in vivo methods performed slightly better than IVIVE methods (at least in terms of measures of correlation and global concordance), with the fu intercept method and two-species-based allometry (rat-dog) being the best performing methods. IVIVE methods using microsomes (incorporating both plasma and microsomal binding) and hepatocytes (not incorporating binding) resulted in 75% and 78%, respectively, of the predictions falling within twofold error. IVIVE methods using other combinations of binding assumptions were much less accurate. The results for prediction of AUCp.o. were consistent with i.v. CL. However, the greatest challenge to successful prediction of human p.o. CL is the estimate of F in human. Overall, the results of this initiative confirmed predictive performance of common methodologies used to predict human CL.

LY2189265, a long-acting glucagon-like peptide-1 analogue, showed a dose-dependent effect on insulin secretion in healthy subjects

AIM

To assess the safety, tolerability, pharmacokinetics, pharmacodynamics and potential immunogenicity of single, escalating subcutaneous injections of a once-weekly glucagon-like peptide-1 analogue in healthy subjects.

METHODS

This phase 1, three-period, crossover, double-blind, placebo-controlled study investigated single, escalating subcutaneous doses of LY2189265 (LY) ranging from 0.1 to 12 mg; approximately six subjects were randomized to each dose. Parameters of safety, including adverse events, were assessed. The pharmacokinetic profile was assessed over 14 days. Pharmacodynamic parameters (glucose and insulin concentrations) were measured following a step-glucose infusion (day 3) and as part of an oral glucose tolerance test (OGTT) (day 5).

RESULTS

LY was generally well tolerated with some increase in gastrointestinal symptoms with escalating doses. There were small dose-dependent increases in pulse rate with doses ≥1.0 mg and diastolic blood pressure with doses ≥3.0 mg. The half-life of LY was approximately 90 h, with C(max) occurring between 24 and 48 h in most subjects. Evidence of increase in glucose-dependent insulin secretion and suppression of serum glucose excursions were observed during an OGTT at all doses compared to placebo; no episodes of hypoglycaemia occurred. No subjects developed antibodies to LY2189265.

CONCLUSIONS

LY showed an acceptable safety profile and exhibited the expected glucagon-like peptide-1 pharmacological effects on glucose suppression and insulin secretion with a half-life that supports once-weekly dosing.

A 5-week study of the pharmacokinetics and pharmacodynamics of LY2189265, a novel, long-acting glucagon-like peptide-1 analogue, in patients with type 2 diabetes

AIM

To investigate the safety, tolerability, pharmacokinetics and pharmacodynamics of LY2189265 (LY), a novel, long-acting glucagen-like peptide-1 analogue, administered once weekly to subjects with type 2 diabetes.

METHODS

This was a placebo-controlled, parallel-group, subject- and investigator-blind study of LY in subjects (N = 43) with type 2 diabetes mellitus controlled with diet and exercise alone or with a single oral antidiabetic medication. Subjects taking metformin or thiazolidinediones continued on their therapy. Subjects receiving sulfonylurea, acarbose, repaglinide or nateglinide were switched to metformin prior to enrollment. Subjects received five once-weekly doses of 0.05, 0.3, 1, 3, 5 or 8 mg. Effects on glucose, insulin and C-peptide concentrations were determined during fasting and following standard test meals. The pharmacokinetics of LY and its effects on HBA1c, glucagon, body weight, gastric emptying and safety parameters were assessed.

RESULTS

Once-weekly administration of LY significantly reduced (p < 0.01) fasting plasma glucose, 2-h post-test meal postprandial glucose and area under the curve (AUC) of glucose after test meals at doses ≥1 mg. These effects were seen after the first dose and were sustained through the weekly dosing cycle. Most doses produced statistically significant increases in insulin and C-peptide AUC when normalized for glucose AUC. Statistically significant reductions in HBA1c were observed for all dose groups except 0.3 mg. The most commonly reported adverse effects (AEs) were nausea (35 events), headache (20 events), vomiting (18 events) and diarrhoea (8 events).

CONCLUSIONS

LY showed improvement in fasting and postprandial glycaemic parameters when administered once weekly in subjects with type 2 diabetes. The pharmacokinetics and safety profiles also support further investigation of this novel agent.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 1: goals, properties of the PhRMA dataset, and comparison with literature datasets

This study is part of the Pharmaceutical Research and Manufacturers of America (PhRMA) initiative on predictive models of efficacy, safety, and compound properties. The overall goal of this part was to assess the predictability of human pharmacokinetics (PK) from preclinical data and to provide comparisons of available prediction methods from the literature, as appropriate, using a representative blinded dataset of drug candidates. The key objectives were to (i) appropriately assemble and blind a diverse dataset of in vitro, preclinical in vivo, and clinical data for multiple drug candidates, (ii) evaluate the dataset with empirical and physiological methodologies from the literature used to predict human PK properties and plasma concentration-time profiles, (iii) compare the predicted properties with the observed clinical data to assess the prediction accuracy using routine statistical techniques and to evaluate prediction method(s) based on the degree of accuracy of each prediction method, and (iv) compile and summarize results for publication. Another objective was to provide a mechanistic understanding as to why one methodology provided better predictions than another, after analyzing the poor predictions. A total of 108 clinical lead compounds were collected from 12 PhRMA member companies. This dataset contains intravenous (n = 19) and oral pharmacokinetic data (n = 107) in humans as well as the corresponding preclinical in vitro, in vivo, and physicochemical data. All data were blinded to protect the anonymity of both the data and the company submitting the data. This manuscript, which is the first of a series of manuscripts, summarizes the PhRMA initiative and the 108 compound dataset. More details on the predictability of each method are reported in companion manuscripts.

PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach

The objective of this study was to evaluate the performance of the Wajima allometry (Css -MRT) approach published in the literature, which is used to predict the human plasma concentration-time profiles from a scaling of preclinical species data. A diverse and blinded dataset of 108 compounds from PhRMA member companies was used in this evaluation. The human intravenous (i.v.) and oral (p.o.) pharmacokinetics (PK) data were available for 18 and 107 drugs, respectively. Three different scenarios were adopted for prediction of human PK profiles. In the first scenario, human clearance (CL) and steady-state volume of distribution (Vss ) were predicted by unbound fraction corrected intercept method (FCIM) and Øie-Tozer (OT) approaches, respectively. Quantitative structure activity relationship (QSAR)-based approaches (TSrat-dog ) based on compound descriptors together with rat and dog data were utilized in the second scenario. Finally, in the third scenario, CL and Vss were predicted using the FCIM and Jansson approaches, respectively. For the prediction of oral pharmacokinetics, the human bioavailability and absorption rate constant were assumed as the average of preclinical species. Various statistical techniques were used for assessing the accuracy of the simulation scenarios. The human CL and Vss were predicted within a threefold error range for about 75% of the i.v. drugs. However, the accuracy in predicting key p.o. PK parameters appeared to be lower with only 58% of simulations falling within threefold of observed parameters. The overall ability of the Css -MRT approach to predict the curve shape of the profile was in general poor and ranged between low to medium level of confidence for most of the predictions based on the selected criteria.

Drug delivery trends in clinical trials and translational medicine: evaluation of pharmacokinetic properties in special populations

In spite of the recent advances in technology to optimize the absorption, distribution, metabolism and elimination (ADME) properties of new and promising medicinal products to reduce clinical failures, the investigation of drug disposition in the pediatric and elderly populations continues to be under evaluated. With the increasing prevalence of aging populations world-wide, there is a growing concern from health care providers, regulators and the general public that drug delivery is still less than optimal for the vulnerable patient populations likely to be more sensitive to adverse effects of the new investigational drugs. This review of the ClinicalTrials.gov database revealed a rapidly increasing number of clinical trials and a trend towards wider inclusion criteria of the elderly population in clinical trials over the past 10 years. However, when we summarized trials by drug delivery, biological platforms, and disease categories, less than 10% of these trials included pharmacokinetic evaluation in elderly subjects greater than 65 years of age, and less than 4% included pharmacokinetic evaluation in children less than 17 years of age. Across the various disease areas, the percentage of trials that included pharmacokinetic evaluation in the children and elderly has remained low and is consistently less than the studies that included the younger 18 to 65 age group. Therefore, it is not known whether the right information is being generated from the growing number of clinical trials to guide optimal dosing recommendations in special patient populations.

Desipramine, substrate for CYP2D6 activity: population pharmacokinetic model and design elements of drug-drug interaction trials

AIMS

To develop a population pharmacokinetic model to describe the pharmacokinetics of desipramine in healthy subjects, after oral administration of a 50mg dose. Additional objectives were to develop a semi-mechanistic population pharmacokinetic model for desipramine, which allowed simulation of CYP2D6-mediated inhibition, when using desipramine as a probe substrate, and to evaluate certain study design elements, such as duration of desipramine pharmacokinetic sampling, required sample size and optimal pharmacokinetic sampling schedule for intermediate, extensive and ultrarapid metabolizers of CYP2D6 substrates.

RESULTS

The mean population estimates of the first order absorption rate constant (k(a) ), apparent clearance (CL/F) and apparent volume of distribution at steady state (V(ss) /F) were 0.15h(-1) , 111 lh(-1) and 2950 l, respectively. Further, using the proposed semi-mechanistic hepatic intrinsic clearance model with Bayesian inference, mean population desipramine hepatic intrinsic clearance was estimated to be 262 lh(-1) with between-subject variability of 84%. d-optimal PK sampling times for intermediate metabolizers were calculated to be approximately 0.25, 24, 75 and 200h. Similar sampling times were found for ultrarapid and extensive metabolizers except that the second d-optimal sample was earlier at 14 and 19h, respectively, compared with 24h for intermediate metabolizers. This difference in sampling times between the three genotypes can be attributed to the different intrinsic clearances and elimination rates.

CONCLUSIONS

A two compartment population pharmacokinetic model best described desipramine disposition. The semi-mechanistic population model developed is suitable to describe the pharmacokinetic behaviour of desipramine for the dose routinely used in drug-drug interaction (DDI) studies. Based on this meta-analysis of seven trials, a sample size of 21 subjects in cross-over design is appropriate for assessing CYP2D6 interaction with novel compounds.

Drug delivery trends in clinical trials and translational medicine: Updated analysis of ClinicalTrials.gov database

While the number of clinical trials has continued to grow by about 20% in the past six months, no corresponding growth in product approval by the food and drug administration is seen or anticipated in the near future. Late-stage clinical failures due to lack of efficacy or toxicity continues to be a challenge. The optimization of absorption, distribution, metabolism and elimination (ADME) has improved drug candidate selection and reduced early clinical failure. The current challenge is how to avoid late stage clinical failures. Expanded knowledge of drug target distribution, pharmacokinetics and validated biomarkers will allow implementation of appropriate drug delivery and clinical trial designs to reduce drug exposure to off-target organs such as the liver and kidney and could reduce potential untoward effects. In essence, integration of drug delivery and targeting to reduce exposure in off-target tissues in the preclinical and clinical program may hold the key to increasing the odds of success in drug development. In this update, we briefly review data on clinical trials pertinent to drug delivery in the current regulatory environment. It also provides our analysis on the emerging trends in second generation antibody therapeutics in drug delivery and targeting.

A new probabilistic rule for drug-dug interaction prediction

An innovative probabilistic rule is proposed to predict the clinical significance or clinical insignificance of DDI. This rule is coupled with a hierarchical Bayesian model approach to summarize substrate/inhibitor's PK models from multiple published resources. This approach incorporates between-subject and between-study variances into DDI prediction. Hence, it can predict both population-average and subject-specific AUCR. The clinically significant DDI, weak DDI, and clinically insignificant inhibitions are decided by the probabilities of predicted AUCR falling into three intervals, (-infinity, 1.25), (1.25, 2), and (2, infinity). The main advantage of this probabilistic rule to predict clinical significance of DDI over the deterministic rule is that the probabilistic rule considers the sample variability, and the decision is independent of sampling variation; while deterministic rule based decision will vary from sample to sample. The probabilistic rule proposed in this paper is best suited for the situation when in vivo PK studies and models are available for both the inhibitor and substrate. An early decision on clinically significant or clinically insignificant inhibition can avoid additional DDI studies. Ketoconazole and midazolam are used as an interaction pair to illustrate our idea. AUCR predictions incorporating between-subject variability always have greater variances than population-average AUCR predictions. A clinically insignificant AUCR at population-average level is not necessarily true when considering between-subject variability. Additional simulation studies suggest that predicted AUCRs highly depend on the interaction constant K(i) and dose combinations.

Stochastic prediction of CYP3A-mediated inhibition of midazolam clearance by ketoconazole

Conventional methods to forecast CYP3A-mediated drug-drug interactions have not employed stochastic approaches that integrate pharmacokinetic (PK) variability and relevant covariates to predict inhibition in terms of probability and uncertainty. Empirical approaches to predict the extent of inhibition may not account for nonlinear or non-steady-state conditions, such as first-pass effects or accumulation of inhibitor concentration with multiple dosing. A physiologically based PK model was developed to predict the inhibition of CYP3A by ketoconazole (KTZ), using midazolam (MDZ) as the substrate. The model integrated PK models of MDZ and KTZ, in vitro inhibition kinetics of KTZ, and the variability and uncertainty associated with these parameters. This model predicted the time- and dose-dependent inhibitory effect of KTZ on MDZ oral clearance. The predictive performance of the model was validated using the results of five published KTZ-MDZ studies. The model improves the accuracy of predicting the inhibitory effect of increasing KTZ dosing on MDZ PK by incorporating a saturable KTZ efflux from the site of enzyme inhibition in the liver. The results of simulations using the model supported the KTZ dose of 400 mg once daily as the optimal regimen to achieve maximum inhibition by KTZ. Sensitivity analyses revealed that the most influential variable on the prediction of inhibition was the fractional clearance of MDZ mediated by CYP3A. The model may be used prospectively to improve the quantitative prediction of CYP3A inhibition and aid the optimization of study designs for CYP3A-mediated drug-drug interaction studies in drug development.

Predictions of the In Vivo Clearance of Drugs from Rate of Loss Using Human Liver Microsomes for Phase I and Phase II Biotransformations

PURPOSE

The utility of in vitro metabolism to accurately predict the clearance of hepatically metabolized drugs was evaluated. Three major goals were: (1) to optimize substrate concentration for the accurate prediction of clearance by comparing to Km value, (2) to prove that clearance of drugs by both oxidation and glucuronidation may be predicted by this method, and (3) to determine the effects of nonspecific microsomal binding and plasma protein binding.

METHODS

The apparent Km values for five compounds along with scaled intrinsic clearances and predicted hepatic clearances for eight compounds were determined using a substrate loss method. Nonspecific binding to both plasma and microsomal matrices were also examined in the clearance calculations.

RESULTS

The Km values were well within the 2-fold variability expected for between laboratory comparisons. Using both phase I and/or phase II glucuronidation incubation conditions, the predictions of in vivo clearance using the substrate loss method were shown to correlate with published human clearance values. Of particular interest, for highly bound drugs (>95% plasma protein bound), the addition of a plasma protein binding term increased the accuracy of the prediction of in vivo clearance.

CONCLUSIONS

The substrate loss method may be used to accurately predict hepatic clearance of drugs.

Pharmacokinetics/Pharmacodynamics and the stages of drug development: role of modeling and simulation

Pharmacokinetic (PK) and pharmacodynamic (PD) modeling and simulation (M&S) are well-recognized powerful tools that enable effective implementation of the learn-and-confirm paradigm in drug development. The impact of PK/PD M&S on decision making and drug development risk management is dependent on the question being asked and on the availability and quality of data accessible at a particular stage of drug development. For instance, M&S methodologies can be used to capture uncertainty and use the expected variability in PK/PD data generated in preclinical species for projection of the plausible range of clinical dose; clinical trial simulation can be used to forecast the probability of achieving a target response in patients based on information obtained in early phases of development. Framing the right question and capturing the key assumptions are critical components of the "learn-and-confirm" paradigm in the drug development process and are essential to delivering high-value PK/PD M&S results. Selected works of PK/PD modeling and simulation from preclinical to phase III are presented as case examples in this article.

Physiological Approaches to the Prediction of Drug-Drug Interactions in Study Populations

The prediction of metabolic drug-drug interactions should include quantitative attributes, such as variability in the study populations, and the results should be presented in terms of probability and uncertainty. The simple algebraic equations used to calculate one mean value for the extent of drug-drug interaction are adequate for qualitative or semi-quantitative risk assessment. However, truly quantitative predictions continue to fail. The success of drug-drug interaction predictions requires understanding of the relationship between drug disposition and quantifiable influential factors on the change in systemic exposure. The complex interplay of influential factors, including variability estimates, on successful prediction of drug interaction have not been systematically examined. Therefore, physiologically relevant models of metabolic drug-drug interaction will likely play increasingly important roles in improving quantitative predictions and in the assessment of the influential factors underlying the interactions. The physiologically-based approach, with stochastic considerations, offers a powerful alternative to the empirical calculation of mean values. In addition to quantitative estimation of the interaction for assessing probability of risk, a reasonably validated predictive model is useful for prospective optimization of study designs. As a consequence, the definitive clinical trial would yield more meaningful information to support dosing recommendations. This review focuses on illustrating the importance of an integrated approach to building useful models for prediction of metabolism-based drug-drug interactions in human subjects.

CYP2E1 activity before and after weight loss in morbidly obese subjects with nonalcoholic fatty liver disease

Previous studies suggest that hepatic cytochrome P450 2E1 (CYP2E1) activity is increased in individuals with chronic alcoholism, nonalcoholic steatohepatitis (NASH), and morbid obesity, and may contribute to liver disease. We studied 16 morbidly obese subjects with varying degrees of hepatic steatosis and 16 normal-weight controls. Obese subjects were evaluated at baseline, 6 weeks, and 1 year after gastroplasty, a procedure that leads to weight loss. Hepatic CYP2E1 activity was assessed by determination of the clearance of chlorzoxazone (CLZ), an in vivo CYP2E1-selective probe. Liver biopsy tissue was obtained during surgery for histopathology. Both the total and unbound oral CLZ clearance (Cl(u)/F) was elevated approximately threefold in morbidly obese subjects compared with controls (P <.001). The Cl(u)/F was significantly higher among subjects with steatosis involving >50% of hepatocytes, compared with those with steatosis in < or =50% of hepatocytes (P =.02). At postoperative week 6 and year 1, the median body mass index (BMI) of subjects who underwent gastroplasty decreased by 11% and 33%, total oral CLZ clearance declined by 16% (P <.01) and 46% (P <.05), and Cl(u)/F decreased by 18% (P <.05) and 35% (P =.16), respectively. Moreover, those subjects with a year 1 BMI <30 kg/m(2) exhibited a median Cl(u)/F that was 63% lower (P =.02) than the respective clearance for all other subjects. In conclusion, hepatic CYP2E1 activity is up-regulated in morbidly obese subjects. A positive association between the degree of steatosis and CYP2E1 activity preoperatively and between the extent of obesity and CYP2E1 activity postoperatively, suggests that CYP2E1 induction is related to or caused by hepatic pathology that results from morbid obesity.

Ethanol and production of the hepatotoxic metabolite of acetaminophen in healthy adults

BACKGROUND

Recent case reports suggest that consumption of ethanol may increase the risk of liver injury induced by acetaminophen (INN, paracetamol). However, this possibility is at odds with previous clinical studies that showed that acute ethanol ingestion could protect against hepatotoxicity by inhibiting CYP-mediated acetaminophen oxidation. We tested the hypothesis that ethanol ingestion can increase susceptibility to acetaminophen toxicity if acetaminophen ingestion occurs shortly after ethanol is cleared from the body.

METHODS

Ten healthy volunteers each received a 6-hour intravenous infusion of ethanol (to achieve a blood concentration of 100 mg/dL ethanol) or 5% dextrose in water, administered in random order. Acetaminophen (500 mg) was ingested 8 hours after the end of the infusion. Blood and urine were collected for assessment of formation of N-acetyl-p-benzoquinone imine (NAPQI), the hepatotoxic metabolite of acetaminophen.

RESULTS

Mean NAPQI formation was enhanced by 22% (range, 2% to 38%; P < .03) when the acetaminophen dose was given after an ethanol infusion, compared with after 5% dextrose in water infusion. This mean increase was similar in magnitude to that predicted by a mathematical model describing the induction of CYP2E1, the main enzyme catalyzing NAPQI formation, by a mechanism of enzyme stabilization.

CONCLUSIONS

Consumption of up to one 750-mL bottle of wine, six 12-ounce cans of beer, or 9 ounces of 80-proof liquor over the course of a single evening modestly increases the fraction of an acetaminophen dose converted to its toxic metabolite, NAPQI, when acetaminophen is ingested soon after ethanol has been cleared from the body. This change in acetaminophen metabolism may present an incremental increase in the risk of acetaminophen hepatotoxicity.

Age-dependent tetrahydrothiophenium ion formation in young children and adults receiving high-dose busulfan

Busulfan, a bifunctional alkylating agent, is a mainstay of myeloablative preparative regimens before hematopoietic stem cell transplantation. The apparent oral clearance of busulfan expressed relative to body surface area is 2-3-fold higher in children 1-4 years old than it is in adults. The first step in busulfan elimination is the formation of a tetrahydrothiophenium ion (THT+) in a glutathione S-transferase-catalyzed reaction. We present computer simulations that demonstrate that the ratio of the AUC of THT+ to that of busulfan over 6 h [(AUC(THT+)/AUC(BU))(0-->6)] is highly correlated (r2 = 0.805) with the determinants of THT+ formation and is virtually independent of the determinants of its elimination (r2 = 0.0201). We compared (AUC(THT+)/AUC(BU))(0-->6) determined in 14 children (0.5-4 years) to that of 11 adults (12-54 years) and found a 1.5-fold elevation in the area ratio (P = 0.0098) and a similarly significant increase in busulfan apparent oral clearance expressed relative to body surface area (P = 0.042). The only common explanation for the elevated busulfan apparent oral clearance and (AUC(THT+)/AUC(BU))(0-->6) is an enhanced ability of children to metabolize busulfan through glutathione conjugation.

Pharmacokinetic consequences of induction of CYP2E1 by ligand stabilization

Models of the time course of the effect of P450 induction on substrate clearance have previously only considered induction through enhanced synthesis of protein. Induction of CYP2E1 does not always conform to this model, in that many chemicals induce the enzyme through stabilization of the protein apparently by binding to the active site. While such binding protects the enzyme from degradation, it also results in competitive inhibition of substrate clearance. We present a model based on experimental studies of chemical induction of CYP2E1 by ligand stabilization through which this mechanism of induction can be translated into its pharmacokinetic consequence with regard to clearance of substrate. CYP2E1 is considered to be localized in two pools: Pool 1 at which two mechanisms of degradation, fast and slow, operate and pool 2, at which only the slower mechanism operates. Binding of substrate to enzyme in pool 1 stabilizes it from degradation by the fast process, leaving only the slow process. Ligand stabilization therefore results in induction of CYP2E1 as enzyme accumulates as a consequence of unchanged synthesis. Binding of ligand to the active site results in competitive inhibition of the clearance of substrate. Model-based computer simulations show that the time course of interaction between inhibitor/inducer and substrate can be predicted from knowledge of I/Ki and S/Km and the synthesis and degradation kinetics of CYP2E1. The simulations demonstrate further that as long as inhibitor/inducer administration is not interrupted, the clearance of substrate will always be less than the value observed at low concentration of substrate even if the substrate concentration is raised to displace inhibitor/inducer from the active site. On the other hand, the degree of inhibition of clearance is less than would be seen if induction had not taken place. Clearance of substrate is observed to rise above the value observed in the absence of the inhibitor/inducer only after the inhibitor/inducer concentration declines low enough for substrate to gain access to the active site of the enzyme. The model-based simulations agree with reports of the interaction between isoniazid and acetaminophen in humans.

Influence of polymorphic N-acetyltransferase phenotype on the inhibition and induction of acetaminophen bioactivation with long-term isoniazid

OBJECTIVE

To determine in patients receiving isoniazid prophylaxis whether an increase in the CYP2E1 dependent formation clearance of acetaminophen (paracetamol) to N-acetyl-p-benzoquinone imine (NAPQI) occurs during a normal 24-hour isoniazid dose interval and whether the interaction is dependent on acetylation status.

METHODS

Acetaminophen elimination kinetics were determined on four different occasions. Ten subjects were assigned to receive acetaminophen either simultaneously with the 8 am dose of isoniazid or 12 hours after the isoniazid dose. One week later, on the last day of isoniazid therapy, subjects received acetaminophen at the alternate time of day. The control phase acetaminophen administrations were repeated 1 and 2 weeks later, following the initial randomization. Isoniazid acetylation (NAT2) genotype was determined by analysis of genomic DNA obtained from peripheral blood leukocytes.

RESULTS

The mean NAPQI formation clearance was inhibited 57% when acetaminophen and isoniazid were coadministered but was unchanged compared with time-matched control when acetaminophen was given 12 hours after the isoniazid dose. However, when data from subjects was segregated according to isoniazid (INH) acetylation phenotype, the mean ratio of NAPQI formation clearances (+INH/-INH) with 8 PM acetaminophen was significantly higher for fast acetylators compared with slow acetylators (1.36 versus 0.68; p = 0.006).

CONCLUSIONS

Fast metabolizers of isoniazid appeared to clear the inducer or inhibitor from the active site of CYP2E1 more rapidly, which resulted in an increased formation of NAPQI 12 hours after the isoniazid dose. In contrast, formation of NAPQI for slow isoniazid metabolizers remained inhibited.

Saturable tissue binding and imirestat pharmacokinetics in rats

To investigate the hypothesis that the pharmacokinetics of imirestat, an aldose reductase inhibitor, are influenced by saturable binding to tissues, three experiments were done. (1) The nature of the dose dependence was characterized in rats. Two groups of nine adult male Sprague-Dawley rats received iv 14C-imirestat at doses of 2 or 8 mg/kg. Serial blood samples were obtained over 15 days. Volume of distribution at steady-state was significantly different between the high- and the low-dose groups (0.744 +/- 0.103 l and 1.10 +/- 0.228 L, respectively). Clearance was independent of dose over this fourfold range (approximately 15 ml/hr). (2) The effect of either statil or AL3152, both aldose reductase inhibitors and potential competitors for aldose reductase binding, on the pharmacokinetics of a single 0.2-mg/kg iv dose of imirestat was assessed. A 2.4-mg/kg loading dose of statil was administered and a constant-rate infusion (56 micrograms/hr/kg) was begun 16 hr before imirestat. A 2-mg/kg loading dose of AL3152 and a constant-rate infusion (115 micrograms/kg/hr) were also administered 16 hr before imirestat. The infusions were maintained throughout the study. AL3152 administration decreased the imirestat steady-state volume of distribution by a mean of 63%. Statil administration decreased it by a mean of 39%. (3) The dosing regimen of the second study was repeated and, at two sampling times, nine tissues and plasma were obtained from four rats per sampling time for determination of imirestat tissue-to-plasma concentration ratio. The tissue/plasma imirestat concentration ratio in the adrenals 24 hr after imirestat administration was 56.9 +/- 20.0 in the imirestat group, 17.7 +/- 1.27 in the statil-coadministered group, and 12.3 +/- 2.59 in the AL3152-coadministered group.(ABSTRACT TRUNCATED AT 250 WORDS)

Production of beta-fructofuranosidase with transfructosylating activity for fructooligosaccharides synthesis by Aspergillus japonicus NTU-1249

Microbial beta-fructofuranosidases with transfructosylating activity can catalyze the transfructosylation of sucrose and synthesize fructooligosaccharides. Aspergillus japonicus NTU-1249 isolated from natural habitat was found to produce a significant amount of beta-fructofuranosidase with high transfructosylating activity and to have the potential for industrial production of fructooligosaccharides. In order to improve it's enzyme productivity, the medium composition and the cultivation conditions for A. japonicus NTU-1249 were studied. A. japonicus NTU-1249 can produce 83.5 units of transfructosylating activity per ml broth when cultivated in a shaking flask at 28 degrees C for 72 hours with a modified medium containing 80 g/l sucrose, 15 g/l soybean flour, 5 g/l yeast extract and 5 g/l NaCl at an initial pH of 6.0. The enzyme productivity was also optimized by submerged cultivation in a 5-litre jar fermentor with aeration at 1.5 vvm and agitation at 500 rpm. Under these operating conditions, the productivity of transfructosylating activity increased to 185.6 U/ml. Furthermore, the transfructosylating activity was improved to 256.1 U/ml in 1,000-litre pilot-scale fermentor. Enzymatic synthesis of fructooligosaccharides by beta-fructofuranosidase from A. japonicus NTU-1249 was performed in batch type by adding 5.6 units of transfructosylating activity per gram of sucrose to a 50% (w/v) sucrose solution at pH 5.0 and 50 degrees C. The yield of fructooligosaccharides was about 60% after reaction for 24 hours, and the syrup produced contained 29.8% (w/v) fructooligosaccharides, 15.2% (w/v) glucose and 5.0% (w/v) sucrose.