Computational prediction of formulation strategies for beyond-rule-of-5 compounds

AbstractThe physicochemical properties of some contemporary drug candidates are moving towards higher molecular weight, and coincidentally also higher lipophilicity in the quest for biological selectivity and specificity. These physicochemical properties move the compounds towards beyond rule-of-5 (B-r-o-5) chemical space and often result in lower water solubility. For such B-r-o-5 compounds non-traditional delivery strategies (i.e. those other than conventional tablet and capsule formulations) typically are required to achieve adequate exposure after oral administration. In this review, we present the current status of computational tools for prediction of intestinal drug absorption, models for prediction of the most suitable formulation strategies for B-r-o-5 compounds and models to obtain an enhanced understanding of the interplay between drug, formulation and physiological environment. In silico models are able to identify the likely molecular basis for low solubility in physiologically relevant fluids such as gastric and intestinal fluids. With this baseline information, a formulation scientist can, at an early stage, evaluate different orally administered, enabling formulation strategies. Recent computational models have emerged that predict glass-forming ability and crystallisation tendency and therefore the potential utility of amorphous solid dispersion formulations. Further, computational models of loading capacity in lipids, and therefore the potential for formulation as a lipid-based formulation, are now available. Whilst such tools are useful for rapid identification of suitable formulation strategies, they do not reveal drug localisation and molecular interaction patterns between drug and excipients. For the latter, Molecular Dynamics simulations provide an insight into the interplay between drug, formulation and intestinal fluid. These different computational approaches are reviewed. Additionally, we analyse the molecular requirements of different targets, since these can provide an early signal that enabling formulation strategies will be required. Based on the analysis we conclude that computational biopharmaceutical profiling can be used to identify where non-conventional gateways, such as prediction of ‘formulate-ability’ during lead optimisation and early development stages, are important and may ultimately increase the number of orally tractable contemporary targets

Physicochemical and physiological mechanisms for the effects of food on drug absorption: The role of lipids and pH

Drugs are absorbed after oral administration as a consequence of a complex array of interactions between the drug, its formulation, and the gastrointestinal (GI) tract. The presence of food within the GI tract impacts significantly on transit profiles, pH, and its solubilization capacity. Consequently, food would be expected to affect the absorption of co‐administered drugs when their physicochemical properties are sensitive to these changes. The physicochemical basis by which ingested food/lipids induce changes in the GI tract and influence drug absorption are reviewed. The process of lipid digestion is briefly reviewed and considered in the context of the absorption of poorly water‐soluble drugs. The effect of food on GI pH is reviewed in terms of location (stomach, upper and lower small intestine) and the temporal relationship between pH and drug absorption. Case studies are presented in which postprandial changes in bioavailability are rationalized in terms of the sensitivity of the physicochemical properties of the administered drug to the altered GI environment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97269/1/1_ftp.pd

To Give Chinese Children "a Memorable China":the Trend of Chinese Indigenous Picture Books

To investigate if drug solubility in pharmaceutical excipients used in lipid based formulations (LBFs) can be predicted from physicochemical properties. Solubility was measured for 30 structurally diverse drug molecules in soybean oil (SBO, long-chain triglyceride; TG(LC)), Captex355 (medium-chain triglyceride; TG(MC)), polysorbate 80 (PS80; surfactant) and PEG400 co-solvent and used as responses during PLS model development. Melting point and calculated molecular descriptors were used as variables and the PLS models were validated with test sets and permutation tests. Solvation capacity of SBO and Captex355 was equal on a mol per mol scale (R (2) = 0.98). A strong correlation was also found between PS80 and PEG400 (R (2) = 0.85), identifying the significant contribution of the ethoxylation for the solvation capacity of PS80. In silico models based on calculated descriptors were successfully developed for drug solubility in SBO (R (2) = 0.81, Q (2) = 0.76) and Captex355 (R (2) = 0.84, Q (2) = 0.80). However, solubility in PS80 and PEG400 were not possible to quantitatively predict from molecular structure. Solubility measured in one excipient can be used to predict solubility in another, herein exemplified with TG(MC) versus TG(LC), and PS80 versus PEG400. We also show, for the first time, that solubility in TG(MC) and TG(LC) can be predicted from rapidly calculated molecular descriptors

The reflective learning continuum: reflecting on reflection

The importance of reflection to marketing educators is increasingly recognized. However, there is a lack of empirical research which considers reflection within the context of both the marketing and general business education literature. This paper describes the use of an instrument which can be used to measure four identified levels of a reflection hierarchy: habitual action, understanding, reflection and intensive reflection and two conditions for reflection: instructor to student interaction and student to student interaction. Further we demonstrate the importance of reflective learning in predicting graduates’ perception of program quality. Although the focus was on assessment of MBA level curricula, the findings have great importance to marketing education and educators

A basic optimization problem in linear systems

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48017/1/224_2005_Article_BF01691464.pd

Generation of Functional CLL-Specific Cord Blood CTL Using CD40-Ligated CLL APC

PMCID: PMC3526610This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Big data and data repurposing – using existing data to answer new questions in vascular dementia research

Introduction: Traditional approaches to clinical research have, as yet, failed to provide effective treatments for vascular dementia (VaD). Novel approaches to collation and synthesis of data may allow for time and cost efficient hypothesis generating and testing. These approaches may have particular utility in helping us understand and treat a complex condition such as VaD. Methods: We present an overview of new uses for existing data to progress VaD research. The overview is the result of consultation with various stakeholders, focused literature review and learning from the group’s experience of successful approaches to data repurposing. In particular, we benefitted from the expert discussion and input of delegates at the 9th International Congress on Vascular Dementia (Ljubljana, 16-18th October 2015). Results: We agreed on key areas that could be of relevance to VaD research: systematic review of existing studies; individual patient level analyses of existing trials and cohorts and linking electronic health record data to other datasets. We illustrated each theme with a case-study of an existing project that has utilised this approach. Conclusions: There are many opportunities for the VaD research community to make better use of existing data. The volume of potentially available data is increasing and the opportunities for using these resources to progress the VaD research agenda are exciting. Of course, these approaches come with inherent limitations and biases, as bigger datasets are not necessarily better datasets and maintaining rigour and critical analysis will be key to optimising data use

Dopamine and opioid systems interact within the nucleus accumbens to maintain monogamous pair bonds

Prairie vole breeder pairs form monogamous pair bonds, which are maintained through the expression of selective aggression toward novel conspecifics. Here, we utilize behavioral and anatomical techniques to extend the current understanding of neural mechanisms that mediate pair bond maintenance. For both sexes, we show that pair bonding up-regulates mRNA expression for genes encoding D1-like dopamine (DA) receptors and dynorphin as well as enhances stimulated DA release within the nucleus accumbens (NAc). We next show that D1-like receptor regulation of selective aggression is mediated through downstream activation of kappa-opioid receptors (KORs) and that activation of these receptors mediates social avoidance. Finally, we also identified sex-specific alterations in KOR binding density within the NAc shell of paired males and demonstrate that this alteration contributes to the neuroprotective effect of pair bonding against drug reward. Together, these findings suggest motivational and valence processing systems interact to mediate the maintenance of social bonds