A number of strategies have been employed within the pharmaceutical industry in order to mitigate the risk of applying design space boundaries developed on the laboratory scale to commercial drug substance manufacturing. The following communication presents a number of case histories from members of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), with the aim of exemplifying strategies used to confirm applicability of design spaces developed on the laboratory scale. The strategies presented have a common aim of ensuring that appropriate quality standards are developed, maintained, and enhanced during the product lifecycle whilst delivering rapid and cost-effective mechanisms for drug substance commercialization.

Taranabant (1) is a cannabinoid-1 receptor (CB1R) inverse agonist that was recently in late-stage clinical development for the treatment of obesity. The previously employed synthesis exhibited a number of shortcomings for continuing development, and in this paper we report an improved synthesis of the target molecule that is suitable for large-scale implementation. Palladium-catalyzed amidation of an enol tosylate afforded a stereodefined tetrasubstituted enamide, and asymmetric hydrogenation thereof provided the target molecule.

rhodium D . J . WA L L A CE , * K . R . C A M P O S , * C . S . S C H U L T Z , * A . K L A P A R S , D . Z EW G E , B . R . C R U M P , B . D . P H E N IX , J . C . M C WI L L IA M S , S . K R S K A , Y. S U N , C . Y. C H E N , F. S P IN D L E R ( M E R C K R E S E A R CH L A B O R A T O RI E S , R A H WA Y, U S A A N D S O L V I A S AG , BA S E L , S W I T Z E R L A N D ) New Efficient Asymmetric Synthesis of Taranabant, a CB1R Inverse Agonist for the Treatment of Obesity Org. Process Res. Dev. 2009, 13, 84-90.

Chiral amide 1 ( MK- 0364, taranabant) is a potent, selective, and orally bioavailable cannabinoid-1 receptor ( CB-1R) inverse agonist indicated for the treatment of obesity. An asymmetric synthesis featuring a dynamic kinetic resolution via hydrogenation for the preparation of the bromo alcohol 5 is disclosed. Conversion of the alcohol intermediate to the chiral amide 1 is accomplished in good overall yield.

The palladium-catalyzed cyanation reaction is known to be sensitive to dissolved cyanide. Investigation into some causes of high levels of dissolved cyanide is presented here, along with a robust solution to this problem.

In this study, uncertainty analysis is applied to a supercritical water hydrogen oxidation mechanism to determine the effect of uncertainties in reaction rate constants and species thermochemistry on predicted species concentrations. Forward rate constants and species thermochemistry are assumed to be the sole contributors to uncertainty in the reaction model with all other model parameters and inputs treated as deterministic quantities. The analysis is conducted by treating the model parameters as random variables, assigning each a suitable probability density function, and propagating the parametric uncertainties through to the predicted species concentrations. Uncertainty propagation is performed using traditional Monte Carlo (MC) simulation and a new, more computationally efficient, probabilistic collocation method called the Deterministic Equivalent Modeling Method (DEMM). Both methods predict virtually identical probability distributions for the resulting species concentrations as a function of time, with DEMM requiring approximately two orders of magnitude less computation time than the corresponding MC simulation. The results of both analyses show that there is considerable uncertainty in all predicted species concentrations. The predicted H2 and O2 concentrations vary ± 70% from their median values. Similarly, the HO2 concentration ranges of +90 to −70% of its median, while the H2O2 concentration varies by + 180 to − 80%. In addition, the DEMM methodology identified two key model parameters, the standard-state heat of formation of HO2 radical and the forward rate constant for H2O2 dissociation, as the largest contributors to the uncertainty in the predicted hydrogen and oxygen species concentrations. The analyses further show that the change in model predictions due to the inclusion of real-gas effects, which are potentially important for SCWO process modeling, is small relative to the uncertainty introduced by the model parameters themselves.