Iloperidone (HP 873) is a D2 and 5-HT2 receptor-antagonist that is under development as a potential atypical antipsychotic agent. Two studies on iloperidone evaluated its safety and tolerability, made a preliminary pharmacokinetic assessment of single 3- and 5-mg doses, and determined the effect of food on its tolerability and pharmacokinetics in healthy volunteers after single 3-mg doses. Iloperidone was well absorbed orally in fasted subjects. The Cmax occurred approximately 2 to 3 hours after administration of a single 3- or 5-mg dose. The pharmacokinetic parameters increased with the dose between 3 and 5 mg (from 2.2 to 5.2 ng/mL for Cmax, and 16 to 50 ng/mL.h for AUC). Iloperidone was eliminated slowly, with a mean t1/2 of 13.5 to 14.0 hours. Coadministration with food did not significantly affect AUC, tmax, or Cmax. These results indicate that the rate of iloperidone's absorption is decreased, but the overall bioavailability is unchanged, when the drug is taken with food. Orthostatic hypotension, dizziness, and somnolence were the most commonly reported adverse events. Coadministration of food reduced the incidence and severity of these events.

For approval of generic drugs, the U.S. Food and Drug Administration (FDA) requires the evidence of bioequivalence in average bioavailability from the bioavailability/bioequivalence studies. The criterion for assessment of bioequivalence adopted by the FDA is a moment-based criterion evaluating log-transformed pharmacokinetic responses such as area under the blood or plasma concentration-time curve (AUC) or maximum concentration (Cmax). Unlike traditional small molecule drug products, the characteristics and development of biologic products are more complicated and sensitive to many factors. Thus, it is of concern to know whether the current bioequivalence criterion is applicable to the assessment of biosimilarity between biologic products. In this article, we compare the moment-based criterion with a probability-based criterion proposed by Tse et al. (2006) for assessment of bioequivalence or biosimilarity between two drug products in terms of consistency/inconsistency for correctly concluding bioequivalence or biosimilarity. A simulation study was conducted to study relative performance of the two criteria. The feasibility and applicability of the proposed criteria for assessment of biosimilarity of follow-on biologics are discussed.

As a regulatory strategy, it is nowadays not uncommon to conduct one confirmatory pivotal clinical trial, instead of two, to demonstrate efficacy and safety in drug development. This paper is intended to investigate the statistical foundation of such an approach. The one-study approach is compared with the conventional two-study approach in terms of power, type-I error, and fundamental statistical assumptions. Necessary requirements for a single-study model is provided in order to maintain equivalent evidence as that from a two-study model. In general, one-study model is valid only under a 'one population' assumption. In addition, higher data quality and more convincing and robust results need to be demonstrated in such cases. However, when 'one-population' assumption is valid and appropriate methods are selected, a one-study model can have a better power using the same sample size. The paper also investigates statistical assumptions and methods for making an overall inference when a two-study model has been used. The methods for integrated analysis are evaluated. It is important for statisticians to select correct pooling strategy based on the project objective and statistical hypothesis.

Unlike small molecule drug products, biological products are therapeutic agents producted using of a living system or organism. Thus, the development of biologic products is a very different and complicated process that is sensitive to environmental factors such as light and temperature. Therefore, the therapeutic effect of follow-on biologic products may not be equivalent to the innovative products even though the average biosimilarity has been established. Thus, Chow et al. suggested that the assessment of biosimilarity between biologic products should be conducted on the basis of variability in 2010. In this article, we propose a biosimilar index that is derived on the basis of estimated reproducibility probability approach and Bayesian approach, respectively. We conducted simulation studies to empirically investigate the relationship of reproducibility probability under various parameter combinations. The simulation results demonstrate that the proposed method based on biosimilar index can reflect the characteristics and impact of variability on the therapeutic effect of biologic products.

As more biologic products are going off patent protection, the development of follow-on biologics products has received much attention from both biotechnology industry and the regulatory agencies. Unlike small-molecule drug products, the development of biologic products is very different and variable via the manufacture process and environment. Thus, Chow et al. (2010) suggested that the assessment of biosimilarity between biologic products focus on variability rather than average biosimilarity. In addition, it is also suggested that a probability-based criterion, which is more sensitive to variability, should be employed. In this article, we propose a probability-based asymptotic statistical testing procedure to evaluate biosimilarity in variability of two biologic products. A numerical study is conducted to investigate the relationship between the probability-based criterion in variability and various study parameters. Simulation studies were also conducted to empirically investigate the performance of the proposed probability-based asymptotic statistical testing procedure in term of empirical sizes and powers. A numerical example is provided to illustrate the proposed methods.