Electrochemical oxidation of drug molecules is a useful tool to generate several different types of metabolites. In the present study we developed a model system involving electrochemical oxidation followed by characterization of the oxidation products and their propensity to modify peptides. The CB1 antagonist rimonabant was chosen as the model drug. Rimonabant has previously been shown to give high covalent binding to proteins in human liver microsomes and hepatocytes and the iminium ion and/or the corresponding aminoaldehyde formed via P450 mediated α-carbon oxidation of rimonabant was proposed to be a likely contributor. This proposal was based on the observation that levels of covalent binding were significantly reduced when iminium species were trapped as cyanide adducts but also following addition of methoxylamine expected to trap aldehydes. Incubation of electrochemically oxidized rimonabant with peptides resulted in peptide adducts to the N-terminal amine with a mass increment of 64 Da. The adducts were shown to contain an addition of C5H4 originating from the aminopiperidine moiety of rimonabant. Formation of the peptide adducts required further oxidation of the iminium ion to short-lived intermediates, such as dihydropyridinium species. In addition, the metabolites and peptide adducts generated in human liver microsomes were compared with those generated by electrochemistry. Interestingly, the same peptide modification was found when rimonabant was coincubated with one of the model peptides in microsomes. This clearly indicated that reactive metabolite(s) of rimonabant identical to electrochemically generated species are also present in the microsomal incubations. In summary, electrochemical oxidation combined with peptide trapping of reactive metabolites identified a previously unobserved bioactivation pathway of rimonabant that was not captured by traditional trapping agents and that may contribute to the in vitro covalent binding.

There is much recent interest in finding rare genetic variants associated with various diseases. Owing to the scarcity of rare mutations, single-variant analyses often lack power. To enable pooling of information across variants, we use a random effect formulation within a retrospective modeling framework that respects the retrospective data collecting mechanism of case-control studies. More concretely, we model the control allele frequencies of the variants as random effects, and the systematic differences between the case and control frequencies as fixed effects, resulting in a mixed model. The use of Poisson approximation and gamma-distributed random effects results in a generalized negative binomial distribution for the joint distribution of the control and case frequencies. Variants are selected by conducting stepwise likelihood ratio tests. The superiority of the proposed method over two existing variant selection methods is demonstrated in a simulation study. The effects of non-gamma random effects and correlated variants are also found to be not too detrimental in the simulation study. When the proposed procedure is applied to identify rare variants associated with obesity, it identifies one additional variant not picked up by existing methods.

Crystalline polymorphism occurs frequently in the solid state of active pharmaceutical ingredients, and this is problematic for the development of a suitable dose form. Rimonabant, an active pharmaceutical ingredient developed by Sanofi and discontinued because of side effects, exhibits dimorphism; both solid forms have nearly the same melting temperatures, melting enthalpies, and specific volumes. Although the problem may well be academic from an industrial point of view, the present case demonstrates the usefulness of constructing pressure-temperature phase diagrams by direct measurement as well as by topological approach. The system is overall monotropic and form II is the more stable solid form. Interestingly, the more stable form does not possess any hydrogen bonds, whereas the less stable one does.

Value-based pricing (VBP) is a method of setting prices for products based on perceived benefits to the consumer. When information is symmetric and freely available and agency is perfect, VBP is efficient and desirable. Because of substantial information asymmetries, medical insurance distortions, and the prescribing monopoly of physicians, VBP is rare for prescription drugs, though a number of countries have recently moved in this direction. Because the potential benefits can be sizable, it is high time for a review of actual VBP-based decision-making in practice. Sweden, with its pharmaceutical benefits board (TLV), was an early adopter of VBP decision-making. We illustrate actual decision-making, thus, using the case of Acomplia for the treatment of obesity in Sweden, with and without the presence of co-morbid conditions. This example has a number of features that will be useful in illustrating the strengths and weaknesses of VBP in actual practice, including multiple indications, a need for not just one but two economic simulation models, considerable sub-group analysis, and requirements for additional evidence development. TLV concluded, in 2006, that Acomplia was cost-effective for patients with a body mass index (BMI) exceeding 35 kg/m2 and patients with a BMI exceeding 28 kg/m2 and either dyslipidemia or type 2 diabetes. Because of uncertainty in some of the underlying assumptions, reimbursement was granted only until 31 December 2008, at which time the manufacturer would be required to submit additional documentation of the long-term effects and cost-effectiveness in order to obtain continued reimbursement. Deciding on reimbursement coverage for pharmaceutical products is difficult. Ex ante VBP assessment is a form of risk sharing, which has been used by TLV to speed up reimbursement and dispersion of effective new drugs despite uncertainty in their true cost-effectiveness. Manufacturers are often asked in return to generate additional health economic evidence that will establish cost-effectiveness as part of ex post review. The alternative is to delay the reimbursement approval until satisfactory evidence is available.