PubMed · 14711136
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James Wharton. 2003. Beware confusing micrograms and milligrams.. https://pubmed.ncbi.nlm.nih.gov/14711136/
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Metered dose inhalers (MDIs) are a widely used dosage form for pulmonary delivery of anti-asthmatic drugs. However, with the phase-out of chlorofluorocarbon (CFC) propellants and need to switch to the alternative pharmaceutically approved hydrofluoroalkane (HFA) propellants, the MDI formulator was faced with several technical challenges. Product components such as valves and elastomers needed to re-designed, and, due to the limited solubility of the commonly used surfactants in the HFA propellants, novel surfactants were developed or co-solvents were used to bring the conventional surfactants into solution. This paper describes a novel formulation approach for HFA based metered-dose inhalers. A physically stable micro-suspension of the model drug, budesonide, was formulated by an in situ-precipitation process using a hydrophilic stabilizer in the propellant system. A network-like structure of the precipitated drug and excipient was formed and resulted in physically stable suspensions in which the solid phase remained suspended in the propellant system for several weeks. Through life dose uniformity testing of MDI units containing formulations of budesonide produced by the novel process, was consistent and within the limits specified by the FDA draft guidance on metered dose inhalers. The fine particle fraction of the budesonide formulations showed a dependence on formulation composition and aerosol hardware (canister and actuator) illustrating flexibility in optimizing the product using this novel in situ formulation technique.
The success rate of discovering new polymorphs by crystallization from solution may be increased if solvents with diverse properties are used during initial polymorph screening. In this study, eight solvent parameters, including hydrogen bond acceptor propensity, hydrogen bond donor propensity, polarity/dipolarity, dipole moment, dielectric constant, viscosity, surface tension and cohesive energy density (equal to square of solubility parameter), of 96 solvents were collected. Using the cluster statistical analysis of the parameters, these 96 solvents were separated into 15 solvent groups. Such solvent groups may provide guidelines for the judicious choice of solvents with diverse properties for polymorph screening.
Medicinal chemists are frequently asked to review lists of compounds to assess their drug- or leadlike nature and to evaluate the suitability of lead compounds based on their "attractiveness" and/or synthetic feasibility as a basis for launching a drug-discovery campaign. It is often felt that one medicinal chemist's opinion is as good as any other, but is it? In an attempt to answer this question, an experiment was performed in conjunction with a recent compound acquisition program (CAP) conducted at Pharmacia. Historically, the CAP included a review of many thousands of compounds by medicinal chemists who eliminate anything deemed undesirable for any reason. In a review conducted in 2002, about 22 000 compounds requiring review by medicinal chemists were broken down into 11 lists of approximately 2000 compounds each. Unknown to the medicinal chemists, a subset of 250 compounds, previously rejected by a very experienced senior medicinal chemist, was added to each of the lists. Most of the 13 medicinal chemists who participated in this process reviewed two lists, although some only reviewed a single list and one reviewed three lists. Those compounds that were deemed unacceptable were recorded and tabulated in various ways to assess the consistency of the reviews. It was found that medicinal chemists were not very consistent in the compounds they rejected as being undesirable. The inconsistency arises from the subjective analysis that all humans utilize when considering "data sets" of any kind. This has important implications for pharmaceutical project teams where individual medicinal chemists review lists of primary screening hits to identify those compounds suitable for follow-up. Once a compound is removed from a list, it and other structurally similar compounds are effectively removed from further consideration. This can also have an impact on computational chemists who are developing models for assessing the desirability or attractiveness of different classes of compounds for lead discovery.