Pharmacokinetic/pharmacodynamic modeling in drug development

Pharmacokinetics and pharmacodynamics of cyclodextrin-based oral drug delivery formulations for disease therapy

Oral drug administration has become the most common and preferred mode of disease treatment due to its good medication adherence and convenience. For orally administered drugs, the safety, efficacy, and targeting ability requirements have grown as disease treatment research advances. It is difficult to obtain prominent efficacy of traditional drugs simply via oral administration. Numerous studies have demonstrated that cyclodextrins (CDs) can improve the clinical applications of certain orally administered drugs by enhancing their water solubility and masking undesirable odors. Additionally, deeper studies have discovered that CDs can influence disease treatment by altering the drug pharmacokinetics (PK) or pharmacodynamics (PD). This review highlights recent research progress on the PK and PD effects of CD-based oral drug delivery in disease therapy. Firstly, the review describes the characteristics of current drug delivery modes in oral administration. Besides, we minutely summarized the different CD-containing drugs, focusing on the impact of CD-based alterations in PK or PD of orally administered drugs in treating diseases. Finally, we deeply discussed current challenges and future opportunities with regard to PK and PD of CD-based oral drug delivery formulations.

Making drugs from T cells: The quantitative pharmacology of engineered T cell therapeutics

Engineered T cells have emerged as highly effective treatments for hematological cancers. Hundreds of clinical programs are underway in efforts to expand the efficacy, safety, and applications of this immuno-therapeutic modality. A primary challenge in developing these "living drugs" is the complexity of their pharmacology, as the drug product proliferates, differentiates, traffics between tissues, and evolves through interactions with patient immune systems. Using publicly available clinical data from Chimeric Antigen Receptor (CAR) T cells, we demonstrate how mathematical models can be used to quantify the relationships between product characteristics, patient physiology, pharmacokinetics and clinical outcomes. As scientists work to develop next-generation cell therapy products, mathematical models will be integral for contextualizing data and facilitating the translation of product designs to clinical strategy.

Model-Informed Dose Selection for a Novel Human Immunoglobulin G4 Derived Monoclonal Antibody Targeting Proprotein Convertase Kwashiorkor Type 9: Insights from Population Pharmacokinetics-Pharmacodynamics and Systems Pharmacology

Monoclonal antibody drugs targeting proprotein convertase kwashiorkor type 9 (PCSK9) have recently demonstrated remarkable success in lipid-lowering therapies. Specifically, antibodies derived from immunoglobulin G1 (IgG1, alirocumab) and IgG2 (evolocumab) have been successfully utilized for this purpose. Recently, a novel recombinant fully human anti-PCSK9 monoclonal antibody, originally derived from IgG4 and designated as SAL003, was developed. This study aimed to explore the pharmacokinetics, efficacy, and safety of SAL003 in both single and multiple administrations. The investigation included both healthy individuals and individuals with hyperlipidemia. To comprehensively grasp the pharmacokinetic (PK) and pharmacodynamic (PD) attributes of SAL003, this study employed population PK-PD (popPK-PD) and mechanistic systems pharmacology (MSP) modeling. These models were employed for predicting low-density lipoprotein cholesterol (LDLc) concentrations and appropriate dosages across diverse potential clinical scenarios. The research results indicated that SAL003 demonstrated comparable pharmacokinetic properties to evolocumab, exhibited notable effectiveness in reducing lipid levels, and was confirmed to be safe and well-tolerated in both healthy individuals and individuals with hyperlipidemia. Notably, SAL003 displayed differing effectiveness between patients and healthy populations. This discrepancy was observed in the popPK-PD model, with a positive population influence on Emax, and the MSP model, indicating elevated PCSK9 clearance and LDLr-related LDLc clearance in the healthy group. Simulation results from the popPK-PD and MSP models indicated a dosage of 140 mg of Q4W and 420 mg of Q8W for phase II/III clinical trials. Reducing the drug dose or extending the dosing intervals may result in treatment failure. Additionally, the simultaneous use of statins led to elevated PCSK9 levels and intensified fluctuations in steady-state LDLc levels during SAL003 treatment.

Efficacy and safety of cetagliptin as monotherapy in patients with type 2 diabetes: A randomized, double-blind, placebo-controlled phase 3 trial

AIM

To assess the efficacy and safety of the dipeptidyl peptidase-4 inhibitor, cetagliptin, as monotherapy in Chinese patients with type 2 diabetes (T2D) and inadequate glycaemic control.

MATERIALS AND METHODS

In total, 504 eligible patients with T2D were enrolled and randomized to cetagliptin 50 mg once daily, cetagliptin 100 mg once daily or placebo at a ratio of 2:2:1 for 24 weeks of double-blind treatment, then all patients received cetagliptin 100 mg once daily for 28 weeks of open-label treatment. The primary efficacy endpoint was the change in HbA1c level from baseline at week 24.

RESULTS

After 24 weeks, HbA1c from baseline was significantly reduced with cetagliptin 50 mg (-1.08%) and cetagliptin 100 mg (-1.07%) compared with placebo (-0.35%). The placebo-subtracted HbA1c reduction was -0.72% with cetagliptin 50 mg and 100 mg. Patients with a baseline HbA1c of 8.5% or higher had a greater HbA1c reduction with cetagliptin than those patients with a baseline HbA1c of less than 8.5%. Both doses studied led to a significantly higher proportion of patients (42.3% with 100 mg and 45.0% with 50 mg) achieving an HbA1c of less than 7.0% compared with placebo (12.9%). Cetagliptin also significantly lowered fasting plasma glucose and 2-hour postmeal plasma glucose relative to placebo. The incidence of adverse experiences was similar between cetagliptin and placebo. No drug-related hypoglycaemia was reported.

CONCLUSIONS

Cetagliptin monotherapy was effective and well tolerated in Chinese patients with T2D who had inadequate glycaemic control on exercise and diet.

Pharmacokinetic-Pharmacodynamic Modeling of the Ponesimod Effect on Heart Rate in Patients With Multiple Sclerosis

The purpose of this study was to characterize the ponesimod effect on the heart rate (HR) in patients with multiple sclerosis (MS). A previous pharmacokinetic (PK) and pharmacodynamic model developed in healthy participants was updated using data from phase II and III trials conducted in patients with MS. Clinically relevant covariates were assessed. Simulations were conducted to evaluate the impact of the lack of adherence to ponesimod treatment and provide guidance in cases of treatment re-initiation. The maximal effect parameter of the PK/HR model was lower in patients with MS (23.5% decrease) compared with healthy volunteers (43.2%). The effect of patient covariates on PK/HR was similar to those identified in healthy participants and not clinically relevant in patients with MS. The population PK/HR model well characterized the effect of ponesimod on the time course of HR in patients with MS. After 2 weeks of treatment with 10 mg or higher doses, the model indicated full tolerance development. After repeated dosing at 20 mg, tolerance was maintained > 60% of the steady-state tolerance for up to 4 days after the last dose. Re-initiating with gradual uptitration is recommended if drug discontinuation lasts ≥ 4 days. This managed the negative chronotropic effects of ponesimod. No bradycardia events were observed within the first 2 weeks of treatment in patients with relapsing MS with a baseline HR > 55 bpm. This justifies the recommendation included in the human prescription drug labeling to monitor HR after the first ponesimod dose in these patients.

Pharmacometrics: The Already-Present Future of Precision Pharmacology

The use of mathematical modeling to represent, analyze, make predictions or providing information on data obtained in drug research and development has made pharmacometrics an area of great prominence and importance. The main purpose of pharmacometrics is to provide information relevant to the search for efficacy and safety improvements in pharmacotherapy. Regulatory agencies have adopted pharmacometrics analysis to justify their regulatory decisions, making those decisions more efficient. Demand for specialists trained in the field is therefore growing. In this review, we describe the meaning, history, and development of pharmacometrics, analyzing the challenges faced in the training of professionals. Examples of applications in current use, perspectives for the future, and the importance of pharmacometrics for the development and growth of precision pharmacology are also presented.

Safety, Tolerability, Pharmacokinetics and Initial Pharmacodynamics of a Subcommissural Organ-Spondin-Derived Peptide: A Randomized, Placebo-Controlled, Double-Blind, Single Ascending Dose First-in-Human Study

INTRODUCTION

This randomized, double-blind, placebo-controlled study in healthy volunteers assessed the safety, tolerability, and pharmacokinetics of single ascending doses of intravenously administered NX210-a linear peptide derived from subcommissural organ-spondin-and explored the effects on blood/urine biomarkers and cerebral activity.

METHODS

Participants in five cohorts (n = 8 each) were randomized to receive a single intravenous dose of NX210 (n = 6 each) (0.4, 1.25, 2.5, 5, and 10 mg/kg) or placebo (n = 2 each); in total, 10 and 29 participants received placebo and NX210, respectively. Blood samples were collected for pharmacokinetics within 180 min post dosing. Plasma and urine were collected from participants (cohorts: 2.5, 5, and 10 mg/kg) for biomarker analysis and electroencephalography (EEG) recordings within 48 h post dosing. Safety/tolerability and pharmacokinetic data were assessed before ascending to the next dose.

RESULTS

The study included 39 participants. All dosages were safe and well tolerated. All treatment-emergent adverse events (n = 17) were of mild severity and resolved spontaneously (except one with unknown outcome). Twelve treatment-emergent adverse events (70.6%) were deemed drug related; seven of those (58.3%) concerned nervous system disorders (dizziness, headache, and somnolence). The pharmacokinetic analysis indicated a short half-life in plasma (6-20 min), high apparent volume of distribution (1870-4120 L), and rapid clearance (7440-16,400 L/h). In plasma, tryptophan and homocysteine showed dose-related increase and decrease, respectively. No drug dose effect was found for the glutamate or glutamine plasma biomarkers. Nevertheless, decreased blood glutamate and increased glutamine were observed in participants treated with NX210 versus placebo. EEG showed a statistically significant decrease in beta and gamma bands and a dose-dependent increasing trend in alpha bands. Pharmacodynamics effects were sustained for several hours (plasma) or 48 h (urine and EEG).

CONCLUSION

NX210 is safe and well tolerated and may exert beneficial effects on the central nervous system, particularly in terms of cognitive processing.

Fluconazole Population Pharmacokinetics after Fosfluconazole Administration and Dosing Optimization in Extremely Low-Birth-Weight Infants

A prospective single-center study was conducted to characterize the pharmacokinetics (PK) of fluconazole (FLCZ) in extremely low-birth-weight infants (ELBWIs) who received fosfluconazole (F-FLCZ). Intravenous F-FLCZ was administered at a dose of 3 mg/kg of body weight every 72 h during the first 2 weeks of life, every 48 h during the third and fourth weeks of life, and every 24 h after 5 weeks of life. Blood samples from ELBWIs treated with F-FLCZ were collected using scavenged samples. The concentration of FLCZ was determined using liquid chromatography-tandem mass spectrometry. The population pharmacokinetic model was established using Phenix NLME 8.2 software. In total, 18 ELBWIs were included in this analysis. Individual PK parameters were determined by a one-compartment analysis with first-order conversion. Postmenstrual age (PMA), serum creatinine (SCr), and alkaline phosphatase were considered covariates for clearance (CL). The mean population CL and the volume of distribution were 0.011 L/h/kg^0.75 and 0.95 L/kg, respectively. Simulation assessments with the final model revealed that the current regimen (3 mg/kg every 72 h) could achieve the proposed target FLCZ trough concentration (>2 μg/mL) in 43.3% and 72.2% of infants with a PMA of ≥37 and 30 to 36 weeks, respectively, and an SCr level of <0.5 mg/dL. Shortened dosing intervals (every 48 or 24 h) might improve the probability of target attainment. This study was the first to assess the PK of F-FLCZ in ELBWI, as well as the first to provide fundamental information about FLCZ exposure after F-FLCZ administration, with the goal of facilitating dose optimization in the ELBWI population.

IMPORTANCE Invasive fungal infection is an important cause of mortality and morbidity in very preterm or very-low-birth-weight infants. In order to limit the risk of invasive fungal infections in this population, the administration of fluconazole is generally recommended for extremely low-birth-weight infants admitted to a neonatal intensive care unit with a Candida species colonization prevalence rate of >10%, under the guidelines of the Infectious Diseases Society of America. Fosfluconazole can reduce the volume of solution required for intravenous therapy compared to fluconazole because it has increased solubility, which is a major advantage for infants undergoing strict fluid management. To date, no study has demonstrated the fluconazole pharmacokinetics after fosfluconazole administration in neonates and infants, and this needs to be clarified. Here, we characterized the pharmacokinetics of fluconazole in extremely low-birth-weight infants who received F-FLCZ and explored the appropriate dosage in this patient population.

Pharmacometrics Approaches and its Applications in Diabetes: An Overview

Type 2 diabetes mellitus is the most prevalent and progressive in nature. As the time progress, the multifaceted complications and comorbidities associated to diabetes worsen in the form of macrovascular or microvascular or both. Pharmacometrics modeling is a step forward in minimizing the risk or at least understanding the factors associated to its progression with the passage of time. These models investigate diabetes treatments effects and the progression factors with different viewpoints incorporating insulin-glucose dynamics, dose-response and pharmacokinetics, and pharmacodynamics relationships. Pharmacometrics modeling is an innovative approach in a sense that it is taking us away from the conventional analysis by providing all the opportunities in improving the decision-making in health sector. It has been suggested that we can achieve greater statistical power for determining drug effects through model-based evaluation than through traditional evaluations. The main aim of this review was to evaluate pharmacometrics approaches used in modeling diabetes progression through time and also the integrated models describing glucose-insulin dynamics.

Exenatide-loaded inside-porous poly(lactic-co-glycolic acid) microspheres as a long-acting drug delivery system with improved release characteristics

The glucagon-like peptide-1 receptor agonist exenatide (EXT) is an effective treatment for type 2 diabetes. However, this peptide has a short biological half-life and the delayed release characteristic of current formulations limit its clinical application. Herein, we prepared EXT-loaded inside-porous poly(d,l-lactic-co-glycolic acid (PLGA) microspheres with outside layers (EXT-PMS) using a W₁/O/W₂ emulsion method with a microfluidic technique and its fabrication and formulation conditions were systematically investigated. In vitro dissolution experiments showed that the PLGA concentration, proportion of drug and oil phase, and the number and size of pores strongly affected the release behaviors of EXT-PMS. In vitro, the optimized EXT-PMS with large internal pores exhibited rapid and stable release without a lag phase. In a rat model, subcutaneous administration of the product yielded plasma concentrations of EXT that was sustained for 30 days with low burst and no delayed-release effect. The preparation of inside-porous microspheres is lighting up the development of long-acting drug delivery systems for other drugs with favorable release characteristics.

Translational pharmacokinetic-pharmacodynamic modeling of preclinical and clinical data of the oral MET inhibitor tepotinib to determine the recommended phase II dose

Tepotinib is a highly selective and potent MET inhibitor in development for the treatment of patients with solid tumors. Given the favorable tolerability and safety profiles up to the maximum tested dose in the first‐in‐human (FIH) trial, an efficacy‐driven translational modeling approach was proposed to establish the recommended phase II dose (RP2D). To study the in vivo pharmacokinetics (PKs)/target inhibition/tumor growth inhibition relationship, a subcutaneous KP‐4 pancreatic cell‐line xenograft model in mice with sensitivity to MET pathway inhibition was selected as a surrogate tumor model. Further clinical PK and target inhibition data (derived from predose and postdose paired tumor biopsies) from a FIH study were integrated with the longitudinal PKs and target inhibition profiles from the mouse xenograft study to establish a translational PK/pharmacodynamic (PD) model. Preclinical data showed that tumor regression with tepotinib treatment in KP‐4 xenograft tumors corresponded to 95% target inhibition. We therefore concluded that a PD criterion of sustained, near‐to‐complete (>95%) phospho‐MET inhibition in tumors should be targeted for tepotinib to be effective. Simulations of dose‐dependent target inhibition profiles in human tumors that exceeded the PD threshold in more than 90% of patients established an RP2D of tepotinib 500 mg once daily. This translational mathematical modeling approach supports an efficacy‐driven rationale for tepotinib phase II dose selection of 500 mg once daily. Tepotinib at this dose has obtained regulatory approval for the treatment of patients with non‐small cell lung cancer harboring MET exon 14 skipping.

Effect of Ponesimod Exposure on Total Lymphocyte Dynamics in Patients with Multiple Sclerosis

OBJECTIVE

The aim of this study was to characterize the relationship between ponesimod plasma concentrations and the temporal evolution of lymphocyte counts in multiple sclerosis (MS) patients.

METHODS

Population pharmacokinetic (PK) and PK/pharmacodynamic (PD) models were developed using data from phase I, II, and III trials, and the impact of clinically relevant covariates on PK and PD parameters was assessed. Simulations were conducted to evaluate the maximal lymphocyte count reduction after ponesimod treatment, and the time required for total lymphocyte counts to return to normal values after treatment interruption.

RESULTS

In MS patients, ponesimod PK were characterized by a low mean apparent plasma clearance (5.52 L/h) and a moderate mean apparent volume of distribution at steady state (239 L). The model developed indicated that none of the evaluated covariates (age, sex, formulation, food, body weight, clinical condition, and renal impairment) had a clinically relevant impact on the PK/PD parameters. In MS patients, total lymphocyte counts were characterized by a maximum reduction of 88.0% and a half maximal inhibitory concentration (IC₅₀) of 54.9 ng/mL. Simulations indicated that in patients with normal hepatic function treated with ponesimod 20 mg daily, total lymphocyte counts were reduced to 41% of baseline at trough. After stopping treatment, lymphocyte counts were restored to normal levels within one week.

CONCLUSIONS

The population PK/PD model well-characterized the PK of ponesimod and the time course of total lymphocyte counts in MS patients. Additionally, none of the evaluated covariates had a clinically relevant impact. This should be taken into consideration when assessing the risk of infection, administration of live-attenuated vaccines, and concomitant use of immunosuppressants.

Population Pharmacokinetics and Pharmacodynamics of Meropenem in Critically Ill Pediatric Patients

This study investigates the optimal meropenem (MEM) dosing regimen for critically ill pediatric patients, for which there is a lack of pharmacokinetic (PK) studies. We conducted a retrospective single-center PK and pharmacodynamic (PD) analysis of 34 pediatric intensive care unit patients who received MEM. Individual PK parameters were determined by a two-compartment analysis. The median (range) age and body weight were 1.4 (0.03 to 14.6) years and 8.9 (2.7 to 40.9) kg, respectively, and eight (23.5%) patients received continuous renal replacement therapy (CRRT), three of whom received extracorporeal membrane oxygenation. Renal function, the systemic inflammatory response syndrome (SIRS) score for the clearance (CL), and the use of CRRT for the central volume of distribution (V _c) were identified as significant covariates. The mean CL, V _c, and peripheral volume of distribution (V _p) were 0.45 liters/kg/h, 0.49 liters/kg, and 0.34 liters/kg, respectively. The mean population CL of MEM increased by 35% in patients with SIRS and V _c increased by 66% in patients on CRRT in the final model. Dosing simulations suggested that the standard dosing regimen provided insufficient PD exposures of a 100% free time above the MIC, and higher doses (40 to 80 mg/kg of body weight/dose every 8 h) with a prolonged 3-h infusion were required to ensure the appropriate PD exposures for patients with SIRS. Our PK model indicated that critically ill pediatric patients are at risk of subtherapeutic exposure under the standard dosing regimen of MEM. A larger, prospective investigation confirming the safety and efficacy of higher concentrations and prolonged infusion of MEM is necessary.

Meropenem population pharmacokinetics in patients with decompensated cirrhosis and severe infections

OBJECTIVES

Meropenem pharmacokinetics (PK) may be altered in patients with cirrhosis, hampering target attainment. We aimed to describe meropenem PK in patients with decompensated cirrhosis and severe bacterial infections, identify the sources of PK variability and assess the performance of different dosing regimens to optimize the PK/pharmacodynamic (PD) target.

METHODS

Serum concentrations and covariates were obtained from patients with severe infections under meropenem treatment. A population PK analysis was performed using non-linear mixed-effects modelling and the final model was used to simulate meropenem exposure to assess the PTA.

RESULTS

Fifty-four patients were enrolled in the study. Data were best described by a one-compartment linear model. The estimated typical mean value for clearance (CL) was 8.35 L/h and the estimated volume of distribution (V) was 28.2 L. Creatinine clearance (CLCR) and MELD score significantly influenced meropenem CL, and acute-on-chronic liver failure (ACLF) significantly affected V. Monte Carlo simulations showed that a lower meropenem dose would be needed as CLCR decreases and as the MELD score increases. Patients with ACLF would have lower peak meropenem concentrations but similar steady-state concentrations compared with patients with no ACLF.

CONCLUSIONS

Our study identified two new covariates that influence meropenem PK in patients with decompensated cirrhosis in addition to CLCR: MELD score and ACLF. Dosing regimens are recommended to reach several PK/PD targets considering these clinical variables and any MIC within the susceptibility range.

Predictive modeling of aspirin-triggered resolvin D1 pharmacokinetics for the study of Sjögren's syndrome

OBJECTIVES

Sjögren's syndrome (SS) is an autoimmune disease that causes chronic inflammation of the salivary glands leading to secretory dysfunction. Previous studies demonstrated that aspirin-triggered resolvin D1 (AT-RvD1) reduces inflammation and restores tissue integrity in salivary glands. Specifically, progression of SS-like features in NOD/ShiLtJ mice can be systemically halted using AT-RvD1 prior or after disease onset to downregulate proinflammatory cytokines, upregulate anti-inflammatory molecules, and restore saliva production. Therefore, the goal of this paper was to create a physiologically based pharmacokinetic (PBPK) model to offer a reasonable starting point for required total AT-RvD1 dosage to be administered in future mice and humans thereby eliminating the need for excessive use of animals and humans in preclinical and clinical trials, respectively. Likewise, PBPK modeling was employed to increase the range of testable scenarios for elucidating the mechanisms under consideration.

MATERIALS AND METHODS

Pharmacokinetics following intravenous administration of a 0.1 mg/kg dose of AT-RvD1 in NOD/ShiLtJ were predicted in both plasma and saliva using PBPK modeling with PK-Sim® and MoBi® Version 7.4 software.

RESULTS

The model provides high-value pathways for future validation via in vivo studies in NOD/ShiLtJ to corroborate the findings themselves while also establishing this method as a means to better target drug development and clinical study design.

CONCLUSIONS

Clinical and basic research would benefit from knowledge of the potential offered by computer modeling. Specifically, short-term utility of these pharmacokinetic modeling findings involves improved targeting of in vivo studies as well as longer term prospects for drug development and/or better designs for clinical trials.

Relationship Between Plasma Concentrations and Clinical Effects of Cariprazine in Patients With Schizophrenia or Bipolar Mania

Population pharmacokinetic/pharmacodynamic modeling (via NONMEM) was used to describe longitudinal exposure‐response relationships for total cariprazine (sum of cariprazine and its major active metabolites) in 2,558 patients with schizophrenia or bipolar mania. Drug exposure metrics were explored for potential relationships with efficacy and safety end points. Total cariprazine exposures were significantly related to reductions in Positive and Negative Syndrome Scale (PANSS) or Young Mania Rating Scale (YMRS) total scores in schizophrenia or bipolar mania, respectively, via a maximum effect (E_max)‐type relationship. Typical steady‐state plasma concentrations after 3 and 4.5 mg/day were associated with 50% of maximum typical reductions in PANSS and YMRS total scores, respectively. Time‐weighted cariprazine exposures had significant relationships with the probability of common adverse events (AEs). Dose increase was associated with increased efficacy but was also associated with an increase in AEs. Results of these pharmacokinetic/pharmacodynamic analyses support that the recommended dose range (1.5–6 mg/day for schizophrenia and 3–6 mg/day for bipolar mania) provides an appropriate benefit‐risk balance between cariprazine efficacy and safety.

Optimizing Mycophenolic Acid Exposure in Kidney Transplant Recipients: Time for Target Concentration Intervention

The immunosuppressive agent mycophenolate is used extensively in kidney transplantation, yet dosing strategy applied varies markedly from fixed dosing ("one-dose-fits-all"), to mycophenolic acid (MPA) trough concentration monitoring, to dose optimization to an MPA exposure target (as area under the concentration-time curve [MPA AUC0-12]). This relates in part to inconsistent results in prospective trials of concentration-controlled dosing (CCD). In this review, the totality of evidence supporting mycophenolate CCD is examined: pharmacological characteristics, observational data linking exposure to efficacy and toxicities, and randomized controlled trials of CCD, with attention to dose optimization method and exposure achieved. Fixed dosing of mycophenolate consistently leads to underexposure associated with rejection, as well as overexposure associated with toxicities. When CCD is driven by pharmacokinetic calculation to a target concentration (target concentration intervention), MPA exposure is successfully controlled and clinical benefits are seen. There remains a need for consensus on practical aspects of mycophenolate target concentration intervention in contemporary tacrolimus-containing regimens and future research to define maintenance phase exposure targets. However, given ongoing consequences of both overimmunosuppression and underimmunosuppression in kidney transplantation, impacting short- and long-term outcomes, these should be a priority. The imprecise "one-dose-fits-all" approach should be replaced by the clinically proven MPA target concentration strategy.

Antitumor effect of axitinib combined with dopamine and PK-PD modeling in the treatment of human breast cancer xenograft

Rising evidence has shown the development of resistance to vascular endothelial growth factor receptor (VEGFR) inhibitors in the practices of cancer therapy. It is reported that the efficacy of axitinib (AX), a VEGFR inhibitor, is limited in the treatment of breast cancer as a single agent or in combination with other chemotherapeutic drugs due to the probability of rising population of cancer stem-like cells (CSCs) caused by AX. The present study evaluated the effect of dopamine (DA) improving AX's efficacy on MCF-7/ADR breast cancer in vitro and in vivo, and developed a pharmacokinetic-pharmacodynamic (PK-PD) model describing the in vivo experimental data and characterizing the interaction of effect between AX and DA. The results showed that AX up-regulated the expression of breast CSC (BCSC) markers (CD44⁺/CD24^-/low) in vivo, and DA significantly synergized the inhibitory effect on tumor growth by deducting the BCSC frequency. The PK-PD model quantitatively confirmed the synergistic interaction with the parameter estimate of interaction factor ψ 2.43. The dose regimen was optimized as 60 mg/kg AX i.g. b.i.d. combined with 50 mg/kg DA i.p. q3d in the simulation study on the basis of the PK-PD model. The model where DA synergistically enhances the effect of AX in an all-or-none manner provides a possible solution in modeling the agents like DA. Moreover, the outcome of AX and DA combination therapy in MCF-7/ADR breast cancer provided further insight of co-administering DA in the treatment of the possible CSC-causing AX-resisting breast cancer. And this combination therapy has the prospect of clinical translation.

Pharmacokinetic and Metabolism Studies of Curculigoside C by UPLC-MS/MS and UPLC-QTOF-MS

Pharmacokinetic and metabolism studies were carried out on curculigoside C (CC), a natural product with good antioxidant and neuroprotective effects, with the purpose of investigating the effects of the hydroxyl group at C-3' in curculigoside. A rapid and sensitive method with UPLC-MS was developed and fully validated for the first time in the pharmacokinetic analysis for quantification of CC in rat plasma. The assay was linear (R² > 0.9984) over the concentration range of 1⁻2500 ng/mL, with the lower limit of quantification (LLOQ) being 1 ng/mL. The intra-day and inter-day precision (expressed as relative standard deviation, RSD) ranged from 4.10% to 5.51% and 5.24% to 6.81%, respectively. The accuracy (relative error, RE) ranged from -3.28% to 0.56% and -5.83% to -1.44%, respectively. The recoveries ranged from 92.14% to 95.22%. This method was then applied to a pharmacokinetic study of rats after intragastric administration of 15, 30 and 60 mg/kg CC. The results revealed that CC exhibited rapid oral absorption (Tmax = 0.106 h, 0.111 h, and 0.111 h, respectively), high elimination (t1/2 = 2.022 h, 2.061 h, and 2.048 h, respectively) and low absolute bioavailability (2.01, 2.13, and 2.39%, respectively). Furthermore, an investigation on the metabolism of CC was performed by UPLC-QTOF-MSE. Twelve metabolites of CC from plasma, bile, urine and faeces of rats were confirmed. The main metabolic pathways of CC, which involve dehydration, glucosylation, desaturation, formylation, cysteine conjugation, demethylation and sulfonation, were profiled. In conclusion, this research has developed a sensitive quantitative method and demonstrated the metabolism of CC in vivo.

In silico drug absorption tract: An agent-based biomimetic model for human oral drug absorption

Background

An agent-based modeling approach has been suggested as an alternative to traditional, equation-based modeling methods for describing oral drug absorption. It enables researchers to gain a better understanding of the pharmacokinetic (PK) mechanisms of a drug. This project demonstrates that a biomimetic agent-based model can adequately describe the absorption and disposition kinetics both of midazolam and clonazepam.

Methods

An agent-based biomimetic model, in silico drug absorption tract (ISDAT), was built to mimic oral drug absorption in humans. The model consisted of distinct spaces, membranes, and metabolic enzymes, and it was altogether representative of human physiology relating to oral drug absorption. Simulated experiments were run with the model, and the results were compared to the referent data from clinical equivalence trials. Acceptable similarity was verified by pre-specified criteria, which included 1) qualitative visual matching between the clinical and simulated concentration-time profiles, 2) quantitative similarity indices, namely, weighted root mean squared error (RMSE), and weighted mean absolute percentage error (MAPE) and 3) descriptive similarity which requires less than 25% difference between key PK parameters calculated by the clinical and the simulated concentration-time profiles. The model and its parameters were iteratively refined until all similarity criteria were met. Furthermore, simulated PK experiments were conducted to predict bioavailability (F). For better visualization, a graphical user interface for the model was developed and a video is available in Supporting Information.

Results

Simulation results satisfied all three levels of similarity criteria for both drugs. The weighted RMSE was 0.51 and 0.92, and the weighted MAPE was 5.99% and 8.43% for midazolam and clonazepam, respectively. Calculated PK parameter values, including area under the curve (AUC), peak plasma drug concentration (C_max), time to reach C_max (T_max), terminal elimination rate constant (Kel), terminal elimination half life (T_1/2), apparent oral clearance (CL/F), and apparent volume of distribution (V/F), were reasonable compared to the referent values. The predicted absolute oral bioavailability (F) was 44% for midazolam (literature reported value, 31–72%) and 93% (literature reported value, ≥ 90%) for clonazepam.

Conclusion

The ISDAT met all the pre-specified similarity criteria for both midazolam and clonazepam, and demonstrated its ability to describe absorption kinetics of both drugs. Therefore, the validated ISDAT can be a promising platform for further research into the use of similar in silico models for drug absorption kinetics.

Useful pharmacodynamic endpoints in children: selection, measurement, and next steps

Pharmacodynamic (PD) endpoints are essential for establishing the benefit-to-risk ratio for therapeutic interventions in children and neonates. This article discusses the selection of an appropriate measure of response, the PD endpoint, which is a critical methodological step in designing pediatric efficacy and safety studies. We provide an overview of existing guidance on the choice of PD endpoints in pediatric clinical research. We identified several considerations relevant to the selection and measurement of PD endpoints in pediatric clinical trials, including the use of biomarkers, modeling, compliance, scoring systems, and validated measurement tools. To be useful, PD endpoints in children need to be clinically relevant, responsive to both treatment and/or disease progression, reproducible, and reliable. In most pediatric disease areas, this requires significant validation efforts. We propose a minimal set of criteria for useful PD endpoint selection and measurement. We conclude that, given the current heterogeneity of pediatric PD endpoint definitions and measurements, both across and within defined disease areas, there is an acute need for internationally agreed, validated, and condition-specific pediatric PD endpoints that consider the needs of all stakeholders, including healthcare providers, policy makers, patients, and families.

Regulatory Perspectives in Pharmacometric Models of Osteoporosis

Osteoporosis is a disorder of the bones in which they are weakened to the extent that they become more prone to fracture. There are various forms of osteoporosis: some of them are induced by drugs, and others occur as a chronic progressive disorder as an individual gets older. As the median age of the population rises across the world, the chronic form of the bone disease is drawing attention as an important worldwide health issue. Developing new treatments for osteoporosis and comparing them with existing treatments are complicated processes due to current acceptance by regulatory authorities of bone mineral density (BMD) and fracture risk as clinical end points, which require clinical trials to be large, prolonged, and expensive to determine clinically significant impacts in BMD and fracture risk. Moreover, changes in BMD and fracture risk are not always correlated, with some clinical trials showing BMD improvement without a reduction in fractures. More recently, bone turnover markers specific to bone formation and resorption have been recognized that reflect bone physiology at a cellular level. These bone turnover markers change faster than BMD and fracture risk, and mathematically linking the biomarkers via a computational model to BMD and/or fracture risk may help in predicting BMD and fracture risk changes over time during the progression of a disease or when under treatment. Here, we discuss important concepts of bone physiology, osteoporosis, treatment options, mathematical modeling of osteoporosis, and the use of these models by the pharmaceutical industry and the Food and Drug Administration.

Population Pharmacokinetic and Pharmacodynamic Modeling of Lusutrombopag, a Newly Developed Oral Thrombopoietin Receptor Agonist, in Healthy Subjects

OBJECTIVES

The aim of this study was to develop a population pharmacokinetic (PK)/pharmacodynamic (PD) model for describing plasma lusutrombopag concentrations and platelet response following oral lusutrombopag dosing and for evaluating covariates in the PK/PD profiles.

METHODS

A population PK/PD model was developed using a total of 2539 plasma lusutrombopag concentration data and 1408 platelet count data from 78 healthy adult subjects following oral single and multiple (14-day once-daily) dosing. Covariates in PK and PK/PD models were explored for subject age, body weight, sex, and ethnicity.

RESULTS

A three-compartment model with first-order rate and lag time for absorption was selected as a PK model. A three-transit and one-platelet compartment model with a sigmoid E _max model for drug effect and feedback of platelet production was selected as the PD model. The PK and PK/PD models well described the plasma lusutrombopag concentrations and the platelet response, respectively. Body weight was a significant covariate in PK. The bioavailability of non-Japanese subjects (White and Black/African American subjects) was 13 % lower than that of Japanese subjects, while the simulated platelet response profiles using the PK/PD model were similar between Japanese and non-Japanese subjects. There were no significant covariates of the tested background data including age, sex, and ethnicity (Japanese or non-Japanese) for the PD sensitivity.

CONCLUSION

A population PK/PD model was developed for lusutrombopag and shown to provide good prediction for the PK/PD profiles. The model could be used as a basic PK/PD model in the drug development of lusutrombopag.

Optimized Cocktail Phenotyping Study Protocol Using Physiological Based Pharmacokinetic Modeling and In silico Assessment of Metabolic Drug-Drug Interactions Involving Modafinil

In vivo cocktail pathway phenotyping (ICPP) is routinely used to assess the metabolic drug-drug interaction (mDDI) potential of new drug candidates (NDC) during drug development. However, there are a number of potential limitations to this approach and the use of validated drug cocktails and study protocols is essential. Typically ICPP mDDI studies assess only the impact of interactions following multiple postulated perpetrator doses and hence the emphasis in terms of validation of these studies has been ensuring that there are no interactions between probe substrates. Studies assessing the comparative impact of single and multiple doses of the postulated perpetrator have the potential to provide richer information regarding both the clinical impact and mechanism of mDDIs. Using modafinil as a model compound, we sought to develop an optimized ICPP mDDI study protocol to evaluate the potential magnitude and clinical relevance of mDDIs using a physiologically based pharmacokinetic modeling approach.

Testing the "read-across hypothesis" by investigating the effects of ibuprofen on fish

Human pharmaceuticals present in the environment have the potential to cause adverse effects on non-target organisms. The "read-across hypothesis" stipulates that pharmaceuticals will exhibit similar biological effects across species (e.g. human and fish) if the molecular target has been conserved and the effective drug concentrations are reached (Cmax). We tested this hypothesis by evaluating if ibuprofen, a non-selective inhibitor of prostaglandins and the cyclooxygenase (COX) enzyme, can mimic its primary effect in humans, on fish, at comparable plasma concentrations. The endpoints, prostaglandin E metabolite (PGEM) levels and the mRNA expression of COX (ptgs) gene, were measured in the gills of control and exposed fathead minnows (Pimephales promelas), using enzyme-immunoassay and quantitative real-time PCR (qPCR). Fish were exposed, for 24-72 h, to measured water concentrations of 9 (n = 12), 370 (n = 40) and 470 μg ibuprofen/L (n = 12). Water and blood plasma concentrations were determined using LC-MS/MS. Results showed that PGEM levels in fish exposed to 370 and 470 μg ibuprofen/L were significantly decreased compared to control fish, when mean plasma ibuprofen concentrations were 1.8-5.6-fold below the Cmax. The plasma ibuprofen concentrations and PGEM levels varied greatly between individuals. In fish exposed to 9 μg ibuprofen/L, when the mean plasma ibuprofen concentration was 224-fold below Cmax, no change in PGEM levels was observed. These data provide evidence for the read-across hypothesis, but suggest establishing a direct dose-response between internal plasma and PGEM is difficult, and would require significantly larger numbers of fish to overcome the inter-individual variation.

Good Practices in Model-Informed Drug Discovery and Development: Practice, Application, and Documentation

This document was developed to enable greater consistency in the practice, application, and documentation of Model-Informed Drug Discovery and Development (MID3) across the pharmaceutical industry. A collection of "good practice" recommendations are assembled here in order to minimize the heterogeneity in both the quality and content of MID3 implementation and documentation. The three major objectives of this white paper are to: i) inform company decision makers how the strategic integration of MID3 can benefit R&D efficiency; ii) provide MID3 analysts with sufficient material to enhance the planning, rigor, and consistency of the application of MID3; and iii) provide regulatory authorities with substrate to develop MID3 related and/or MID3 enabled guidelines.

Gap analysis of pharmacokinetics and pharmacodynamics in burn patients: a review

Severe burn injury results in a multifaceted physiological response that significantly alters drug pharmacokinetics and pharmacodynamics (PK/PD). This response includes hypovolemia, increased vascular permeability, increased interstitial hydrostatic pressure, vasodilation, and hypermetabolism. These physiologic alterations impact drug distribution and excretion-thus varying the drug therapeutic effect on the body or microorganism. To this end, in order to optimize critical care for the burn population it is essential to understand how burn injury alters PK/PD parameters. The purpose of this article is to describe the relationship between burn injury and drug PK/PD. We conducted a literature review via PubMed and Google to identify burn-related PK/PD studies. Search parameters included "pharmacokinetics," "pharmacodynamics," and "burns." Based on our search parameters, we located 38 articles that studied PK/PD parameters specifically in burns. Twenty-seven articles investigated PK/PD of antibiotics, 10 assessed analgesics and sedatives, and one article researched an antacid. Out of the 37 articles, there were 19 different software programs used and eight different control groups. The mechanisms behind alterations in PK/PD in burns remain poorly understood. Dosing techniques must be adapted based on burn injury-related changes in PK/PD parameters in order to ensure drug efficacy. Although several PK/PD studies have been undertaken in the burn population, there is wide variation in the analytical techniques, software, and study sample sizes used. In order to refine dosing techniques in burns and consequently improve patient outcomes, there must be harmonization among PK/PD analyses.

Application of PK/PD Modeling in Veterinary Field: Dose Optimization and Drug Resistance Prediction

Among veterinary drugs, antibiotics are frequently used. The true mean of antibiotic treatment is to administer dose of drug that will have enough high possibility of attaining the preferred curative effect, with adequately low chance of concentration associated toxicity. Rising of antibacterial resistance and lack of novel antibiotic is a global crisis; therefore there is an urgent need to overcome this problem. Inappropriate antibiotic selection, group treatment, and suboptimal dosing are mostly responsible for the mentioned problem. One approach to minimizing the antibacterial resistance is to optimize the dosage regimen. PK/PD model is important realm to be used for that purpose from several years. PK/PD model describes the relationship between drug potency, microorganism exposed to drug, and the effect observed. Proper use of the most modern PK/PD modeling approaches in veterinary medicine can optimize the dosage for patient, which in turn reduce toxicity and reduce the emergence of resistance. The aim of this review is to look at the existing state and application of PK/PD in veterinary medicine based on in vitro, in vivo, healthy, and disease model.

Piperacillin population pharmacokinetics in critically ill patients with multiple organ dysfunction syndrome receiving continuous venovenous haemodiafiltration: effect of type of dialysis membrane on dosing requirements

OBJECTIVES

This multicentre study aimed to describe the pharmacokinetics (PK) of piperacillin in critically ill patients with multiple organ dysfunction syndrome (MODS) receiving continuous venovenous haemodiafiltration (CVVHDF), to identify the sources of PK variability and evaluate different dosing regimens to develop recommendations based on clinical parameters.

PATIENTS AND METHODS

Nineteen patients with MODS and CVVHDF receiving piperacillin/tazobactam were enrolled from three tertiary hospitals (95 plasma samples). Population PK modelling and Monte Carlo simulations were performed using NONMEM v7.3(®).

RESULTS

Patients' median age was 70 years (range 39-82), median weight was 80 kg (45-129), median APACHE II score at admission was 21 (13-33) and median SOFA score on the day of study was 11 (8-21). The final population PK model was characterized by CL (L/h) = 6.11 * [weight (kg)/80](1.39) * CLMEMB. If membrane = 1.5 m(2) AN69ST, CLMEMB = 1; if membrane = 0.9 m(2) AN69, CLMEMB = 0.51. Monte Carlo simulations showed that: (i) to maintain unbound piperacillin concentrations above the MIC for the bacteria for 100% of dosing interval T (100%fuT>MIC), patients receiving CVVHDF with 1.5 m(2) AN69ST membranes required doses of 4000 mg q8h for the treatment of bacteria with a susceptibility to piperacillin close to the clinical breakpoint (MIC = 8-16 mg/L) (2000 mg q8h was sufficient for patients with CVVHDF using 0.9 m(2) AN69 membranes); and (ii) for the treatment of bacteria with high susceptibility to piperacillin (MIC <4 mg/L) or for the attainment of a more traditional pharmacodynamic target (50%fuT>MIC), 2000 mg q8h sufficed regardless of type of membrane and body weight.

CONCLUSIONS

Our results suggest that type of membrane and body weight should be considered for piperacillin dose titration in critically ill patients with MODS and CVVHDF requirement.

Early diagnosis of gestational trophoblastic neoplasia based on trajectory classification with compartment modeling

BACKGROUND

In randomized clinical trials or observational studies, it is common to collect biomarker values longitudinally on a cohort of individuals. The investigators may be interested in grouping individuals that share similar changes of biomarker values and use these groups for diagnosis or therapeutic purposes. However, most classical model-based classification methods rely mainly on empirical models such as splines or polynomials and do not reflect the physiological processes.

METHODS

A model-based classification method was developed for longitudinal biomarker measurements through a pharmacokinetic model that describes biomarker changes over time. The method is illustrated using data on human Chorionic Gonadotrophic Hormone measurements after curettage of hydatidiform moles.

RESULTS

The resulting classification was linked to the evolution toward gestational trophoblastic neoplasia and may be used as a tool for early diagnosis. The diagnostic accuracy of the pharmacokinetic model was more reproducible than the one of a purely mathematical model that did not take into account the biological processes.

CONCLUSION

The use of pharmacokinetic models in model-based classification approaches can lead to clinically useful classifications.

Comparison of the Efficacy and Safety of a Pharmacokinetic Model-Based Dosing Scheme Versus a Conventional Fentanyl Dosing Regimen For Patient-Controlled Analgesia Immediately Following Robot-Assisted Laparoscopic Prostatectomy: A Randomized Clinical Trial

Conventional, intravenous, patient-controlled analgesia, which is only administered by demand bolus without basal continuous infusion, is closely associated with inappropriate analgesia. Pharmacokinetic model-based dosing schemes can quantitatively describe the time course of drug effects and achieve optimal drug therapy. We compared the efficacy and safety of a conventional dosing regimen for intravenous patient-controlled analgesia that was administered by demand bolus without basal continuous infusion (group A) versus a pharmacokinetic model-based dosing scheme performed by decreasing the dosage of basal continuous infusion according to the model-based simulation used to achieve a targeted concentration (group B) following robot-assisted laparoscopic prostatectomy.In total, 70 patients were analyzed: 34 patients in group A and 36 patients in group B. The postoperative opioid requirements, pain scores assessed by the visual analog scale, and adverse events (eg, nausea, vomiting, pruritis, respiratory depression, desaturation, sedation, confusion, and urinary retention) were compared on admission to the postanesthesia care unit and at 0.5, 1, 4, 24, and 48 h after surgery between the 2 groups. All patients were kept for close observation in the postanesthesia care unit for 1 h, and then transferred to the general ward.The fentanyl requirements in the postanesthesia care unit for groups A and B were 110.0 ± 46.4 μg and 77.5 ± 35.3 μg, respectively. The pain scores assessed by visual analog scale at 0.5, 1, 4, and 24 h after surgery in group B were significantly lower than in group A (all P < 0.05). There were no differences in the adverse events between the 2 groups.We found that the pharmacokinetic model-based dosing scheme resulted in lower opioid requirements, lower pain scores, and no significant adverse events in the postanesthesia care unit following robot-assisted laparoscopic prostatectomy in comparison with conventional dosing regimen.

Stochastic nonlinear mixed effects: a metformin case study

In nonlinear mixed effect (NLME) modeling, the intra-individual variability is a collection of errors due to assay sensitivity, dosing, sampling, as well as model misspecification. Utilizing stochastic differential equations (SDE) within the NLME framework allows the decoupling of the measurement errors from the model misspecification. This leads the SDE approach to be a novel tool for model refinement. Using Metformin clinical pharmacokinetic (PK) data, the process of model development through the use of SDEs in population PK modeling was done to study the dynamics of absorption rate. A base model was constructed and then refined by using the system noise terms of the SDEs to track model parameters and model misspecification. This provides the unique advantage of making no underlying assumptions about the structural model for the absorption process while quantifying insufficiencies in the current model. This article focuses on implementing the extended Kalman filter and unscented Kalman filter in an NLME framework for parameter estimation and model development, comparing the methodologies, and illustrating their challenges and utility. The Kalman filter algorithms were successfully implemented in NLME models using MATLAB with run time differences between the ODE and SDE methods comparable to the differences found by Kakhi for their stochastic deconvolution.

Meropenem population pharmacokinetics in critically ill patients with septic shock and continuous renal replacement therapy: influence of residual diuresis on dose requirements

Meropenem dosing in critically ill patients with septic shock and continuous renal replacement therapy (CRRT) is complex, with the recommended maintenance doses being 500 mg to 1,000 mg every 8 h (q8h) to every 12 h. This multicenter study aimed to describe the pharmacokinetics (PKs) of meropenem in this population to identify the sources of PK variability and to evaluate different dosing regimens to develop recommendations based on clinical parameters. Thirty patients with septic shock and CRRT receiving meropenem were enrolled (153 plasma samples were tested). A population PK model was developed with data from 24 patients and subsequently validated with data from 6 patients using NONMEM software (v.7.3). The final model was characterized by CL = 3.68 + 0.22 · (residual diuresis/100) and V = 33.00 · (weight/73)(2.07), where CL is total body clearance (in liters per hour), residual diuresis is the volume of residual diuresis (in milliliters per 24 h), and V is the apparent volume of distribution (in liters). CRRT intensity was not identified to be a CL modifier. Monte Carlo simulations showed that to maintain concentrations of the unbound fraction (fu ) of drug above the MIC of the bacteria for 40% of dosing interval T (referred to as 40% of the ƒ uT >MIC), a meropenem dose of 500 mg q8h as a bolus over 30 min would be sufficient regardless of the residual diuresis. If 100% of the ƒ uT >MIC was chosen as the target, oligoanuric patients would require 500 mg q8h as a bolus over 30 min for the treatment of susceptible bacteria (MIC < 2 mg/liter), while patients with preserved diuresis would require the same dose given as an infusion over 3 h. If bacteria with MICs close to the resistance breakpoint (2 to 4 mg/liter) were to be treated with meropenem, a dose of 500 mg every 6 h would be necessary: a bolus over 30 min for oligoanuric patients and an infusion over 3 h for patients with preserved diuresis. Our results suggest that residual diuresis may be an easy and inexpensive tool to help with titration of the meropenem dose and infusion time in this challenging population.

Evaluation of optimized bronchoalveolar lavage sampling designs for characterization of pulmonary drug distribution

Bronchoalveolar lavage (BAL) is a pulmonary sampling technique for characterization of drug concentrations in epithelial lining fluid and alveolar cells. Two hypothetical drugs with different pulmonary distribution rates (fast and slow) were considered. An optimized BAL sampling design was generated assuming no previous information regarding the pulmonary distribution (rate and extent) and with a maximum of two samples per subject. Simulations were performed to evaluate the impact of the number of samples per subject (1 or 2) and the sample size on the relative bias and relative root mean square error of the parameter estimates (rate and extent of pulmonary distribution). The optimized BAL sampling design depends on a characterized plasma concentration time profile, a population plasma pharmacokinetic model, the limit of quantification (LOQ) of the BAL method and involves only two BAL sample time points, one early and one late. The early sample should be taken as early as possible, where concentrations in the BAL fluid ≥ LOQ. The second sample should be taken at a time point in the declining part of the plasma curve, where the plasma concentration is equivalent to the plasma concentration in the early sample. Using a previously described general pulmonary distribution model linked to a plasma population pharmacokinetic model, simulated data using the final BAL sampling design enabled characterization of both the rate and extent of pulmonary distribution. The optimized BAL sampling design enables characterization of both the rate and extent of the pulmonary distribution for both fast and slowly equilibrating drugs.

Modeling and Simulation to Support Phase 2 Dose Selection for RG7652, a Fully Human Monoclonal Antibody Against Proprotein Convertase Subtilisin/Kexin Type 9

RG7652 is a fully humanized monoclonal antibody targeting human PCSK9, a regulator of serum low density lipoprotein cholesterol (LDLc) levels. RG7652 prevents degradation of the hepatic LDLc receptors by blocking PCSK9 binding and thereby resulting in efficient LDLc uptake by hepatocytes. The pharmacokinetics of RG7652 have been evaluated in healthy subjects after single and multiple subcutaneous doses. Pharmacokinetic (PK) and pharmacodynamic (PD) models were developed to explain the antibody PK and LDLc time course data. The PK and PD models based on data from healthy subjects were used to simulate the effects of RG7652 on LDLc levels for a range of potential dose regimens in patients with coronary heart disease. A one-compartment PK model combined with an indirect PD response model was able to adequately describe the PK and LDLc data. Simulations of 400 mg every 4 weeks or 800 mg every 8 weeks regimens show significant LDLc reduction and suggest that dosing RG7652 once every month or once every 2 months is predicted to be optimal for the treatment of hypercholesterolemia. The PK and PD model successfully described the PK and LDLc data from healthy subjects in a Phase 1 study, and the model-based simulations provided useful insights and quantitative understanding for the selection of Phase 2 study doses in patients with coronary heart disease. The approach used in the case study demonstrates the utility of modeling and simulation in designing dose-ranging studies.

Antibody Drug Conjugates: Application of Quantitative Pharmacology in Modality Design and Target Selection

Antibody drug conjugates (ADCs) are a multi-component modality comprising of an antibody targeting a cell-specific antigen, a potent drug/payload, and a linker that can be processed within cellular compartments to release payload upon internalization. Numerous ADCs are being evaluated in both research and clinical settings within the academic and pharmaceutical industry due to their ability to selectively deliver potent payloads. Hence, there is a clear need to incorporate quantitative approaches during early stages of drug development for effective modality design and target selection. In this review, we describe a quantitative approach and framework for evaluation of the interplay between drug- and systems-dependent properties (i.e., target expression, density, localization, turnover, and affinity) in order to deliver a sufficient amount of a potent payload into the relevant target cells. As discussed, theoretical approaches with particular considerations given to various key properties for the target and modality suggest that delivery of the payload into particular effect cells to be more sensitive to antigen concentrations for targets with slow turnover rates as compared to those with faster internalization rates. Further assessments also suggest that increasing doses beyond the threshold of the target capacity (a function of target internalization and expression) may not impact the maximum amount of payload delivered to the intended effect cells. This article will explore the important application of quantitative sciences in selection of the target and design of ADC modalities.

Population pharmacokinetics of benznidazole in adult patients with Chagas disease

The aim of the present study was to build a population pharmacokinetic (popPK) model to characterize benznidazole (BNZ) pharmacokinetics in adults with chronic Chagas disease. This study was a prospective, open-label, single-center clinical trial approved by the local ethics committee. Patients received BNZ at 2.5 mg/kg of body weight/12 h (Abarax, Elea Laboratory, Argentina) for 60 days. Plasma BNZ samples were taken several times during the study and analyzed by high-performance liquid chromatography with UV-visible detection (HPLC-UV). The popPK analysis was done with NONMEMv.7.3. Demographic and biological data were tested as covariates. Intraindividual, interoccasion, and residual variabilities were modeled. Internal and external validations were completed to assess the robustness of the model. Later on, simulations were performed to generate BNZ concentration-time course profiles for different dosage regimens. A total of 358 plasma BNZ concentrations from 39 patients were included in the analysis. A one-compartment PK model characterized by clearance (CL/F) and the apparent volume of distribution (V/F), with first-order absorption (Ka) and elimination, adequately described the data (CL/F, 1.73 liters/h; V/F, 89.6 liters; and Ka, 1.15 h(-1)). No covariates were found to be significant for CL/F and V/F. Internal and external validations of the final model showed adequate results. Data from simulations revealed that a dose of 2.5 mg/kg/12 h might lead to overexposure in most patients. A lower dose (2.5 mg/kg/24 h) was able to achieve trough BNZ plasma concentrations within the accepted therapeutic range of 3 to 6 mg/liter. In summary, we developed a population PK model for BNZ in adults with chronic Chagas disease. Dosing simulations showed that a BNZ dose of 2.5 mg/kg/24 h will adequately keep BNZ trough plasma concentrations within the recommended target range for the majority of patients. (This study has been registered at EudraCT under number 2011-002900-34 and at ClinicalTrials.gov under number NCT01755403.).

Integrating dynamic mixed-effect modelling and penalized regression to explore genetic association with pharmacokinetics

CONTEXT

In a previous work, we have shown that penalized regression approaches can allow many genetic variants to be incorporated into sophisticated pharmacokinetic (PK) models in a way that is both computationally and statistically efficient. The phenotypes were the individual model parameter estimates, obtained a posteriori of the model fit and known to be sensitive to the study design.

OBJECTIVE

The aim of this study was to propose an integrated approach in which genetic effect sizes are estimated simultaneously with the PK model parameters, which should improve the estimate precision and reduce sensitivity to study design.

METHODS

A total of 200 data sets were simulated under the null and each of the following three alternative scenarios: (i) a phase II study with N=300 participants and n=6 sampling times, wherein six unobserved causal variants affect the drug elimination clearance; (ii) the addition of participants with a residual concentration collected in clinical routine (N=300, n=6 plus N=700, n=1); and (iii) a phase II study (N=300, n=6) in which four unobserved causal variants affect two different model parameters.

RESULTS

In all scenarios the integrated approach detected fewer false positives. In scenario (i), true-positive rates were low and the stepwise procedure outperformed the integrated approach. In scenario (ii), approaches performed similarly and rates were higher. In scenario (iii), the integrated approach outperformed the stepwise procedure.

CONCLUSION

A PK phase II study with N=300 lacks the power to detect genetic effects on PK using genetic arrays. Our approach can simultaneously analyse phase II and clinical routine data and identify when genetic variants affect multiple PK parameters.

Ozanezumab dose selection for amyotrophic lateral sclerosis by pharmacokinetic-pharmacodynamic modelling of immunohistochemistry data from patient muscle biopsies

Amyotrophic Lateral Sclerosis (ALS) is a rare and fatal neurodegenerative disease with a high unmet medical need. In this context, a potential therapy should be brought to patients in the most expeditious way and early exploration of pharmacology is highly beneficial. Ozanezumab, a humanised IgG monoclonal antibody against Nogo-A protein which is an inhibitor of neurite outgrowth, is currently under development for the treatment of ALS and has been recently assessed in 76 patients in a first-in-human study. Inadequate target engagement has been recognised as a major contributing reason for drug trial failures. In this work, we describe the development of a pharmacokinetic-pharmacodynamic (PKPD) model using immunohistochemistry (IHC) data of co-localization of ozanezumab with Nogo-A in skeletal muscle as a surrogate measure of target engagement. The rich plasma concentration data and the sparse IHC data after one or two intravenous doses of ozanezumab were modelled simultaneously using a non-linear mixed-effect approach. The final PKPD model was a two-compartment PK model combined with an effect compartment PD model that accounted for the delay in ozanezumab concentrations to reach the site of action which is skeletal muscle. Diagnostic plots showed a satisfactory fit of both PK and IHC data. The model was used as a simulation tool to design a dose regimen for sustained drug-target co-localization in a phase II study.

Comparison of Nonlinear Mixed Effects Models and Noncompartmental Approaches in Detecting Pharmacogenetic Covariates

Genetic data is now collected in many clinical trials, especially in population pharmacokinetic studies. There is no consensus on methods to test the association between pharmacokinetics and genetic covariates. We performed a simulation study inspired by real clinical trials, using the pharmacokinetics (PK) of a compound under development having a nonlinear bioavailability along with genotypes for 176 single nucleotide polymorphisms (SNPs). Scenarios included 78 subjects extensively sampled (16 observations per subject) to simulate a phase I study, or 384 subjects with the same rich design. Under the alternative hypothesis (H1), six SNPs were drawn randomly to affect the log-clearance under an additive linear model. For each scenario, 200 PK data sets were simulated under the null hypothesis (no gene effect) and H1. We compared 16 combinations of four association tests, a stepwise procedure and three penalised regressions (ridge regression, Lasso, HyperLasso), applied to four pharmacokinetic phenotypes, two observed concentrations, area under the curve estimated by noncompartmental analysis and model-based clearance. The different combinations were compared in terms of true and false positives and probability to detect the genetic effects. In presence of nonlinearity and/or variability in bioavailability, model-based phenotype allowed a higher probability to detect the SNPs than other phenotypes. In a realistic setting with a limited number of subjects, all methods showed a low ability to detect genetic effects. Ridge regression had the best probability to detect SNPs, but also a higher number of false positives. No association test showed a much higher power than the others.

Estimating HIV-1 fitness characteristics from cross-sectional genotype data

Despite the success of highly active antiretroviral therapy (HAART) in the management of human immunodeficiency virus (HIV)-1 infection, virological failure due to drug resistance development remains a major challenge. Resistant mutants display reduced drug susceptibilities, but in the absence of drug, they generally have a lower fitness than the wild type, owing to a mutation-incurred cost. The interaction between these fitness costs and drug resistance dictates the appearance of mutants and influences viral suppression and therapeutic success. Assessing in vivo viral fitness is a challenging task and yet one that has significant clinical relevance. Here, we present a new computational modelling approach for estimating viral fitness that relies on common sparse cross-sectional clinical data by combining statistical approaches to learn drug-specific mutational pathways and resistance factors with viral dynamics models to represent the host-virus interaction and actions of drug mechanistically. We estimate in vivo fitness characteristics of mutant genotypes for two antiretroviral drugs, the reverse transcriptase inhibitor zidovudine (ZDV) and the protease inhibitor indinavir (IDV). Well-known features of HIV-1 fitness landscapes are recovered, both in the absence and presence of drugs. We quantify the complex interplay between fitness costs and resistance by computing selective advantages for different mutants. Our approach extends naturally to multiple drugs and we illustrate this by simulating a dual therapy with ZDV and IDV to assess therapy failure. The combined statistical and dynamical modelling approach may help in dissecting the effects of fitness costs and resistance with the ultimate aim of assisting the choice of salvage therapies after treatment failure.

Mutations conferring drug resistance represent major threats to the therapeutic success of highly active antiretroviral therapy (HAART) against human immunodeficiency virus (HIV)-1 infection. Viral mutants differ in their fitness and assessing viral fitness is a challenging task. In this article, we estimate drug-specific mutational pathways by learning from clinical data using statistical techniques and incorporate these into mathematical models of in vivo viral infection dynamics. This approach enables us to estimate mutant fitness characteristics. We illustrate our method by predicting fitness characteristics of mutant genotypes for two different antiretroviral therapies with the drugs zidovudine and indinavir. We recover several established features of mutant fitnesses and quantify fitness characteristics both in the absence and presence of drugs. Our model extends naturally to multiple drugs and we illustrate this by simulating a dual therapy with ZDV and IDV to assess therapy failure. Additionally, our modelling approach relies only on cross-sectional clinical data. We believe that such an approach is a highly valuable tool in assisting the choice of salvage therapies after treatment failure.