Mixture Experimentation in Pharmaceutical Formulations: A Tutorial.

Mixture experimentation is commonly seen in pharmaceutical formulation studies, where the relative proportions of the individual components are modeled for effects on product attributes. The requirement that the sum of the component proportions equals 1 has given rise to the class of designs, known as mixture designs. The first mixture designs were published by Quenouille in 1953 but it took nearly 40 years for the earliest mixture design applications to be published in the pharmaceutical sciences literature by Kettaneh-Wold in 1991 and Waaler in 1992. Since then, the advent of efficient computer algorithms to generate designs has made this class of designs easily accessible to pharmaceutical statisticians, although the use of these designs appears to be an underutilized experimental strategy even today. One goal of this tutorial is to draw the attention of experimental statisticians to this class of designs and their advantages in pursuing formulation studies such as excipient compatibility studies. We present sufficient materials to introduce the novice practitioner to this class of design, associated models, and analysis strategies. An example of a mixture-process variable design is given as a case study.

A Bayesian Approach to Kinetic Modeling of Accelerated Stability Studies and Shelf Life Determination.

Kinetic modeling of accelerated stability data serves an important purpose in the development of pharmaceutical products, providing support for shelf life claims and expediting the path to clinical implementation. In this context, a Bayesian kinetic modeling framework is considered, accommodating different types of nonlinear kinetics with temperature and humidity dependent rates of degradation and accounting for the humidity conditions within the packaging to predict the shelf life. In comparison to kinetic modeling based on nonlinear least-squares regression, the Bayesian approach allows for interpretable posterior inference, flexible error modeling and the opportunity to include prior information based on historical data or expert knowledge. While both frameworks perform comparably for high-quality data from well-designed studies, the Bayesian approach provides additional robustness when the data are sparse or of limited quality. This is illustrated by modeling accelerated stability data from two solid dosage forms and is further examined by means of artificial data subsets and simulated data.

Lipid Based Formulations in Hard Gelatin and HPMC Capsules: a Physical Compatibility Study.

PURPOSE: To investigate the compatibility between hard gelatin and HPMC capsules with a range of different isotropic lipid based formulations containing multiple excipients. METHODS: The miscibility was investigated for 350 systems applying five different oils (Labrafac ™ lipophile WL1349, Maisine® CC, Captex 300 EP/NF, olive oil, and Capmul MCM EP/NF), five different surfactans (Labrasol ® ALF, Labrafil M 2125 CS, Kolliphor ® ELP, Kolliphor ® HS 15, Tween 80) and three different cosolvents (propylene glycol, polyethylene glycol 400, and Transcutol ® HP). For the isotropic systems capsule compatibility was investigated in both gelatin and HPMC capsules at 25°C at 40% and 60% relative humidity by examining physical damages to the capsules and weight changes after storage. RESULTS: The miscibility of lipid based vehicles was best when the formulation contained monoglycerides and surfactants with a hydrophilic-lipophilic balance value <12. Gelatin capsules in general resulted in a better compatibility when compared to HPMC capsules for the evaluated formulations. Addition of water to the formulation improved the capsule compatibility for both capsule types. The expected capsule mass change could partly be predicted in binary systems using the provided data of the single excipients weighted for its formulation proportion. CONCLUSIONS: The capsule compatibility was driven by the components incorporated into the formulations, where more was compatible with gelatin than HPMC capsules. Prediction of the mass change from individual excipient contributions can provide a good first estimate if a vehicle is compatible with a capsule, however, this needs to be proved experimentally.

The individual-level surrogate threshold effect in a causal-inference setting with normally distributed endpoints.

In the meta-analytic surrogate evaluation framework, the trial-level coefficient of determination Rtrial2 quantifies the strength of the association between the expected causal treatment effects on the surrogate (S) and the true (T) endpoints. Burzykowski and Buyse supplemented this metric of surrogacy with the surrogate threshold effect (STE), which is defined as the minimum value of the causal treatment effect on S for which the predicted causal treatment effect on T exceeds zero. The STE supplements Rtrial2 with a more direct clinically interpretable metric of surrogacy. Alonso et al. proposed to evaluate surrogacy based on the strength of the association between the individual (rather than expected) causal treatment effects on S and T. In the current paper, the individual-level surrogate threshold effect (ISTE) is introduced in the setting where S and T are normally distributed variables. ISTE is defined as the minimum value of the individual causal treatment effect on S for which the lower limit of the prediction interval around the individual causal treatment effect on T exceeds zero. The newly proposed methodology is applied in a case study, and it is illustrated that ISTE has an appealing clinical interpretation. The R package surrogate implements the methodology and a web appendix (supporting information) that details how the analyses can be conducted in practice is provided.

Refinement of symptoms of neuropathic pain measurements after various transections of the nerve endings of the sciatic and femoral nerve in rats: an exploratory behavioral analysis.

BACKGROUND: Many animal models can be used to study the underlying pathophysiological mechanisms of neuropathic pain. Most of these models rely on a partial denervation of the limb of the animal by ligating a selected nerve. In this study, we performed nerve lesions on three peripheral nerves supplying the plantar side of the rat hindpaw by differentially transecting the saphenous, the tibial, and the sural nerves alone or in paired combinations. METHODS: The development of neuropathic pain symptoms at three different anatomical areas (medial, central, and lateral) of the glabrous skin of the hindpaw was evaluated by sensory testing over a 12-wk period. Mechanical hyperalgesia (pinprick), cold allodynia (acetone), and abnormalities of hindpaw posture were continuously present in animals with tibial and tibial and saphenous nerve transection. RESULTS: Transection of the tibial and sural nerves induced cold allodynia and moderate mechanical hyperalgesia. Transection of the sural, the saphenous, or both nerves simultaneously induced no signs of specific neuropathic pain behavior and no abnormalities in posture of the affected hindpaw were noted after adequate stimulation. CONCLUSIONS: The overlapping innervation of nerve distribution can complicate the interpretation of nerve ligation studies of peripheral neuropathies.