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1.  Novel Endogenous Glycan Therapy for Retinal Diseases: Safety, In Vitro Stability, Ocular Pharmacokinetic Modeling, and Biodistribution 
The AAPS Journal  2014;16(2):311-323.
Asialo, tri-antennary oligosaccharide (NA3 glycan) is an endogenous compound, which supports proper folding of outer segment membranes, promotes normal ultrastructure, and maintains protein expression patterns of photoreceptors and Müller cells in the absence of retinal pigment epithelium support. It is a potential new therapeutic for atrophic age-related macular degeneration (AMD) and other retinal degenerative disorders. Herein, we evaluate the safety, in vitro stability, ocular pharmacokinetics and biodistribution of NA3. NA3 was injected into the vitreous of New Zealand white rabbits at two concentrations viz. 1 nM (minimum effective concentration (MEC)) and 100 nM (100XMEC) at three time points. Safety was evaluated using routine clinical and laboratory tests. Ocular pharmacokinetics and biodistribution of [3H]NA3 were estimated using scintillation counting in various parts of the eye, multiple peripheral organs, and plasma. Pharmacokinetic parameters were estimated by non-compartmental modeling. A 2-aminobenzamide labeling and hydrophilic interaction liquid interaction chromatography were used to assess plasma and vitreous stability. NA3 was well tolerated by the eye. The concentration of NA3 in eye tissues was in the order: vitreous > retina > sclera/choroid > aqueous humor > cornea > lens. Area under the curve (0 to infinity) (AUC∞) was the highest in the vitreous thereby providing a positive concentration gradient for NA3 to reach the retina. Half-lives in critical eye tissues ranged between 40 and 60 h. NA3 concentrations were negligible in peripheral organs. Radioactivity from [3H]NA3 was excreted via urine and feces. NA3 was stable at 37°C in vitreous over a minimum of 6 days, while it degraded rapidly in plasma. Collectively, these results document that NA3 shows a good safety profile and favorable ocular pharmacokinetics.
Electronic supplementary material
The online version of this article (doi:10.1208/s12248-014-9563-1) contains supplementary material, which is available to authorized users.
doi:10.1208/s12248-014-9563-1
PMCID: PMC3933590  PMID: 24470212
age-related macular degeneration (AMD); NA3 glycan; pharmacokinetics; safety
2.  Strategic Biomarkers for Drug Development in Treating Rare Diseases and Diseases in Neonates and Infants 
The AAPS Journal  2013;15(2):447-454.
There are similar challenges in developing a product designed to treat patients with a rare disease and drugs to treat critically ill neonates and infants. Part of the challenge in developing such products as well as identifying the optimal dosing regimen for the treatment of young children arises from the complex interrelationship between developmental changes and changes in biomarkers responsive to drug therapy. These difficulties are further compounded by our lack of understanding of the key physiological factors that cause the differences in clinical responses between adults and neonates and infants. Regulatory efforts have succeeded in overcoming these challenges in many areas of pediatric and orphan drug development. Strategic applications of biomarkers and surrogate endpoints for the development and approval of a product used to treat an orphan disease will be highlighted with examples of approved products. Continued efforts are still needed to fill in our knowledge gap and to strategically link biomarkers and surrogate endpoints to clinical responses for rare diseases and diseases affecting neonates and infants.
doi:10.1208/s12248-013-9452-z
PMCID: PMC3675740  PMID: 23334978
biomarkers; infants; neonates; rare diseases
3.  Immunogenicity to Therapeutic Proteins: Impact on PK/PD and Efficacy 
The AAPS Journal  2012;14(2):296-302.
The development of therapeutic proteins requires the understanding of the relationship between the dose, exposure, efficacy, and toxicity of these molecules. Several intrinsic and extrinsic factors contribute to the challenges for measuring therapeutic proteins in a precise and accurate manner. In addition, induction of an immune response to therapeutic protein results in additional complexities in the analysis of the pharmacokinetic profile, toxicity, safety, and efficacy of this class of molecules. Assessment of immunogenicity of therapeutic proteins is a required aspect of regulatory filings for a licensing application and for the safe and efficacious use of these compounds. A systematic strategy and well-defined criteria for measuring anti-drug antibodies (ADA) have been established, to a large extent, through coordinated efforts. These recommendations are based on risk assessment and include the determination of ADA content (concentration/titer), affinity, immunoglobulin isotype/subtype, and neutralization capacity. This manuscript reviews the requirements necessary for understanding the nature of an ADA response in order to discern the impact of immunogenicity on pharmacokinetics/pharmacodynamics and efficacy.
doi:10.1208/s12248-012-9340-y
PMCID: PMC3326159  PMID: 22407289
antibody; immunogenicity; pharmacodynamics; pharmacokinetics; protein therapeutics
4.  Comparative Performance of Cell Life Span and Cell Transit Models for Describing Erythropoietic Drug Effects 
The AAPS Journal  2011;13(4):650-661.
Prolonged time delay in response to drug action is a common feature of hematological responses to pharmacotherapy such as erythropoiesis. The objective of this study was to compare the performance of two competing modeling approaches for delayed drug effects, mechanistic cell life span models, and semi-mechanistic cell transit models. The comparison was performed with an experimental dataset from multiple dose administrations of an erythropoietin mimetic to Cynomolgus monkeys. Comparative performance measures include visual predictive checks, goodness-of-fit plots, model estimation time, estimation status, and estimation error. The analysis revealed that both models resulted in a similarly good description of the erythropoietic drug effect, with precision and bias of the model-based predictions of red blood cell counts of less than 11%. The cell transit model needed slightly longer time to converge compared to the cell life span model. The system and drug effect parameters were similar in both models indicating that the models can be interchangeably used to describe the current data. Thus, model selection would be dependent on the purpose of the modeling exercise, the available data, and the time allocated for model development.
Electronic supplementary material
The online version of this article (doi:10.1208/s12248-011-9302-9) contains supplementary material, which is available to authorized users.
doi:10.1208/s12248-011-9302-9
PMCID: PMC3231865  PMID: 22005901
cell life span model; cell transit model; delayed response; pharmacodynamics; PK/PD modeling
6.  Translational Biomarkers: from Preclinical to Clinical a Report of 2009 AAPS/ACCP Biomarker Workshop 
The AAPS Journal  2011;13(2):274-283.
There have been some successes in qualifying biomarkers and applying them to drug development and clinical treatment of various diseases. A recent success is illustrated by a collaborative effort among the US Food and Drug Administration, the European Medicines Agency, and the pharmaceutical industry to provide a set of seven preclinical kidney toxicity biomarkers for drug development. Other successes include, but are not limited to, clinical biomarkers for cancer treatment and clinical management of heart transplant patients. The value of fully qualified surrogate endpoints in facilitating successful drug development is undisputed, especially for diseases in which the traditional clinical outcome can only be assessed in large, multi-year trials. Emerging biomarkers, including chemical genomic or imaging biomarkers, and measurement of circulating tumor cells hold great promise for early diagnosis of disease and as prognostic tests for managing treatment of chronic diseases such as osteoarthritis, Alzheimer disease, cardiovascular disease, and cancer. To advance the success of treating and managing these diseases, efforts are needed to establish the temporal relationship between changes in inflammatory or imaging biomarkers with the progression of the chronic disease, and in the case of cancer, between the extent of circulating cancer cells and tumor progression or remission.
doi:10.1208/s12248-011-9265-x
PMCID: PMC3085704  PMID: 21448748
biomarkers; diagnostic; diseases; gene expression; imaging
7.  Concepts and Challenges in Quantitative Pharmacology and Model-Based Drug Development 
The AAPS Journal  2008;10(4):552-559.
Model-based drug development (MBDD) has been recognized as a concept to improve the efficiency of drug development. The acceptance of MBDD from regulatory agencies, industry, and academia has been growing, yet today’s drug development practice is still distinctly distant from MBDD. This manuscript is aimed at clarifying the concept of MBDD and proposing practical approaches for implementing MBDD in the pharmaceutical industry. The following concepts are defined and distinguished: PK–PD modeling, exposure–response modeling, pharmacometrics, quantitative pharmacology, and MBDD. MBDD is viewed as a paradigm and a mindset in which models constitute the instruments and aims of drug development efforts. MBDD covers the whole spectrum of the drug development process instead of being limited to a certain type of modeling technique or application area. The implementation of MBDD requires pharmaceutical companies to foster innovation and make changes at three levels: (1) to establish mindsets that are willing to get acquainted with MBDD, (2) to align processes that are adaptive to the requirements of MBDD, and (3) to create a closely collaborating organization in which all members play a role in MBDD. Pharmaceutical companies that are able to embrace the changes MBDD poses will likely be able to improve their success rate in drug development, and the beneficiaries will ultimately be the patients in need.
doi:10.1208/s12248-008-9062-3
PMCID: PMC2628212  PMID: 19003542
drug development; modeling; pharmacodynamics; pharmacokinetics; pharmacometrics; simulation
8.  Pharmacokinetically-Guided Lead Optimization of Nitrofuranylamide Anti-Tuberculosis Agents 
The AAPS Journal  2008;10(1):157-165.
In an effort to develop novel and more potent therapies to treat tuberculosis, a new class of chemical agents, nitrofuranylamides, is being developed. The present study examines biopharmaceutic properties and preclinical pharmacokinetics of nitrofuranylamides at early stages of drug discovery to accelerate the optimization of leads into development candidates. The first tested compound, Lee 562, had high anti-tuberculosis activity in vitro, but exhibited poor metabolic stability resulting in a high systemic clearance, a short elimination half-life and low oral bioavailability in vivo in rats. Thus, two follow-up compounds were designed and tested that included structural modifications for increased metabolic stability. Both compounds showed improved metabolic stability compared to Lee 562, with Lee 878 being much more stable than Lee 952. As a consequence, the oral bioavailability of Lee 878 reached ~27% compared to 16% for the other two compounds. This observation prompted us to select compounds based on metabolic stability screening and a new set of nine compounds with high in vitro activity were tested for metabolic stability. The most stable compound in the assay, Lee 1106 was selected for further pharmacokinetic evaluation in rats. Surprisingly, Lee 1106 exhibited poor oral bioavailability, 4.6%. Biopharmaceutic evaluation of the compound showed that the compound has poor aqueous solubility and a high clogP. Based on these results, a screening paradigm was developed for optimization of the nitrofuranylamide lead compounds in a timely and cost-effective manner that might also be applicable to other classes of anti-infective drugs.
doi:10.1208/s12248-008-9017-8
PMCID: PMC2751462  PMID: 18446516
anti-infectives; lead optimization; metabolic stability; pharmacokinetics; preclinical drug development; tuberculosis
9.  Population pharmacokinetic studies in pediatrics: Issues in design and analysis 
The AAPS Journal  2005;7(2):E475-E487.
The current review addresses the following 3 frequently encountered challenges in the design and analysis of population pharmacokinetic studies in pediatrics: (1) body size adjustments during the development of pharmacostatistical models, (2) design and validation of limited sampling strategies, and (3) the integration of historical priors in data analysis and trial simulation. Size adjustments with empiric approaches based on body weight or body surface area have frequently proven as a pragmatic tool to overcome large size differences in a pediatric study population. Allometric size adjustments, however, provide a more mechanistic, physiologically based approach that, if used a priori, allows delineation of the effect of size from that of other covariates that show a high degree of collinearity. The frequent lack of dense data sets in pediatric clinical pharmacology because of ethical and logistic constraints in study design can be overcome with the application of D-optimality-based limited sampling schemes in combination with Bayesian and nonlinear mixed-effects modeling approaches. Empirically based dose selection and clinical trial designs for pediatric clinical pharmacology studies can be improved by applying clinical trial simulation techniques, especially if they integrate adult and pediatric in vitro and/or in vivo data as historic priors. Although integration of these concepts and techniques in population pharmacokinetic analyses is not only limited to pediatric research, their application allows researchers to overcome some major hurdles frequently encountered in pharmacokinetic studies in pediatrics and, thus, provides the basis for additional clinical pharmacology research in this previously insufficiently studied fraction of the general population.
doi:10.1208/aapsj070248
PMCID: PMC2750985  PMID: 16353925
population pharmacokinetics; pediatrics; body size; sparse sampling; clinical trial simulation

Results 1-9 (9)