Development of a selective androgen receptor modulator for transdermal use in hypogonadal patients.

We have identified a non-steroidal selective androgen receptor modulator (SARM), termed LY305, that is bioavailable through a transdermal route of administration while highly cleared via hepatic metabolism to limit parent compound exposure in the liver. Selection of this compound and its transdermal formulation was based on the optimization of skin absorption properties using both in vitro and in vivo skin models that supported PBPK modeling for human PK predictions. This molecule is an agonist in perineal muscle while being a weak partial agonist in the androgenic tissues such as prostate. When LY305 was tested in animal models of skeletal atrophy it restored the skeletal muscle mass through accelerated repair. In a bone fracture model, LY305 remained osteoprotective in the regenerating tissue and void of deleterious effects. Finally, in a small cohort of healthy volunteers, we assessed the safety and tolerability of LY305 when administered transdermally. LY305 showed a dose-dependent increase in serum exposure and was well tolerated with minimal adverse effects. Notably, there were no statistically significant changes to hematocrit or HDL after 4-week treatment period. Collectively, LY305 represents a first of its kind de novo development of a non-steroidal transdermal SARM with unique properties which could find clinical utility in hypogonadal men.

Optimal design criteria for discrimination and estimation in nonlinear models.

Nonlinear models are common in pharmacokinetics and pharmacodynamics. To date, most work in design in this area has concentrated on parameter estimation. Here, we introduce the idea of optimization of both estimation and model selection. However, experimental designs that provide powerful discrimination between a pair of competing model structures are rarely efficient in terms of estimating the parameters under each model. Conversely, designs which are efficient for parameter estimation may not provide suitable power to discriminate between the models. Several different methods of addressing both of these objectives simultaneously are introduced in this paper and are compared to an existing optimality criterion.

Optimal crossover designs for logistic regression models in pharmacodynamics.

Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.