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2.  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
3.  Model-Based Development of Anacetrapib, a Novel Cholesteryl Ester Transfer Protein Inhibitor 
The AAPS Journal  2011;13(2):179-190.
A model-based strategy was used to inform the early clinical development of anacetrapib, a novel cholesteryl ester transfer protein inhibitor under development for the treatment of hyperlipidemia. The objectives of this model-based approach were to enable bridging variable pharmacokinetic effects, differences among formulations used in development, and to identify an appropriate dose for the phase III confirmatory program. Nonlinear mixed effects PK/PD models were initially developed based on data obtained from multiple phase I studies and later were updated with data from a phase IIb study. The population pharmacokinetic model described differences between the liquid-filled capsule used in phase I and phase IIb and the hot-melt extruded (HME) tablet formulation introduced in phase III, allowing for bridging of the two formulations, and quantified the complex relationship of apparent anacetrapib bioavailability with subject meal intake. Proportional Emax models quantified the relationships between anacetrapib trough concentration and lipoprotein effects (LDL-C and HDL-C), with covariate effects of study population (normal volunteers vs. patients), and co-administration with HMG-CoA reductase inhibitor (“statin”). The interaction between anacetrapib and atorvastatin suggested pharmacological independence, i.e., that when given together, each agent exerts the same proportional lipid effect observed from monotherapy. Clinical trial simulation was used to examine the robustness of the effects to random dietary indiscretion, and found that the results were robust as long as patients generally adhered to a low-fat diet. These results allowed the selection of the 100 mg dose with the HME formulation for phase III development even though this dose and formulation were not specifically studied in a phase IIb trial.
Electronic supplementary material
The online version of this article (doi:10.1208/s12248-011-9254-0) contains supplementary material, which is available to authorized users.
doi:10.1208/s12248-011-9254-0
PMCID: PMC3085715  PMID: 21347617
anacetrapib; cetp inhibition; clinical trial simulation; modeling
4.  Evaluation of Agile Designs in First-in-Human (FIH) Trials—A Simulation Study 
The AAPS Journal  2009;11(4):653-663.
The aim of the investigation was to evaluate alternatives to standard first-in-human (FIH) designs in order to optimize the information gained from such studies by employing novel agile trial designs. Agile designs combine adaptive and flexible elements to enable optimized use of prior information either before and/or during conduct of the study to seamlessly update the study design. A comparison of the traditional 6 + 2 (active + placebo) subjects per cohort design with alternative, reduced sample size, agile designs was performed by using discrete event simulation. Agile designs were evaluated for specific adverse event models and rates as well as dose-proportional, saturated, and steep-accumulation pharmacokinetic profiles. Alternative, reduced sample size (hereafter referred to as agile) designs are proposed for cases where prior knowledge about pharmacokinetics and/or adverse event relationships are available or appropriately assumed. Additionally, preferred alternatives are proposed for a general case when prior knowledge is limited or unavailable. Within the tested conditions and stated assumptions, some agile designs were found to be as efficient as traditional designs. Thus, simulations demonstrated that the agile design is a robust and feasible approach to FIH clinical trials, with no meaningful loss of relevant information, as it relates to PK and AE assumptions. In some circumstances, applying agile designs may decrease the duration and resources required for Phase I studies, increasing the efficiency of early clinical development. We highlight the value and importance of useful prior information when specifying key assumptions related to safety, tolerability, and PK.
Electronic supplementary material
The online version of this article (doi:10.1208/s12248-009-9141-0) contains supplementary material, which is available to authorized users.
doi:10.1208/s12248-009-9141-0
PMCID: PMC2782075  PMID: 19763840
agile design; simulation
5.  Accelerating Drug Development Using Biomarkers: A Case Study with Sitagliptin, A Novel DPP4 Inhibitor for Type 2 Diabetes 
The AAPS Journal  2008;10(2):401-409.
The leveraged use of biomarkers presents an opportunity in understanding target engagement and disease impact while accelerating drug development. For effective integration in drug development, it is essential for biomarkers to aid in the elucidation of mechanisms of action and disease progression. The recent years have witnessed significant progress in biomarker selection, validation, and qualification, while enabling surrogate and clinical endpoint qualification and application. Biomarkers play a central role in target validation for novel mechanisms. They also play a central role in the learning/confirming paradigm, particularly when utilized in concert with pharmacokinetic/pharmacodynamic modeling. Clearly, these attributes make biomarker integration attractive for scientific and regulatory applications to new drug development. In this review, applications of proximal, or target engagement, and distal, or disease-related, biomarkers are highlighted using the example of the recent development of sitagliptin for type 2 diabetes, wherein elucidation of target engagement and disease-related biomarkers significantly accelerated sitagliptin drug development. Importantly, use of biomarkers as tools facilitated design of clinical efficacy trials while streamlining dose focus and optimization, the net impact of which reduced overall cycle time to filing as compared to the industry average.
doi:10.1208/s12248-008-9041-8
PMCID: PMC2751391  PMID: 18686043
disease progression; distal biomarkers; DPP4; glucose; proximal biomarkers; sitagliptin; type 2 diabetes

Results 1-5 (5)