Slow Release Drug Dissolution Profile Prediction in Pharmaceutical Manufacturing: a Multivariate and Machine Learning Approach

Slow release drugs must be manufactured to meet target specifications with respect to dissolution curve profiles. In this paper we consider the problem of identifying the drivers of dissolution curve variability of a drug from historical manufacturing data. Several data sources are considered: raw material parameters, coating data, loss on drying and pellet size statistics. The methodology employed is to develop predictive models using LASSO, a powerful machine learning algorithm for regression with high-dimensional datasets. LASSO provides sparse solutions facilitating the identification of the most important causes of variability in the drug fabrication process. The proposed methodology is illustrated using manufacturing data for a slow release drug.

Denver - A City Profile

Denver has emerged from the 1990s as a city region experiencing rapid growth. This has been fuelled by a vibrant local economy, which has adjusted itself from dependency on an earlier oil boom to greater reliance on the information and communications technology sector. The current planning and development challenges are dominated by the need to deal with urban sprawl and pressured transportation infrastructure. The contemporary restructuring of the physical fabric of Denver is marked by a progressive downtown revitalisation effort and a number of space extensive brownfield development projects. The interplay of state and local governments with commercial interests and citizens is a powerful dynamic in shaping these negative and positive outcomes.

Optimisation of source/drain extension region profile for suppression of short channel effects in sub-50 nm DG SOI MOSFETs with high- k gate dielectrics

Novel technology dependent scaling parameters i.e. spacer to gradient ratio and effective channel length (Leff) are proposed for source/drain engineered DG MOSFET, and their significance in minimizing short channel effects (SCES) in high-k gate dielectrics is discussed in detail. Results show that a high-k dielectric should be associated with a higher spacer to gradient ratio to minimise SCEs The analytical model agrees with simulated data over the entire range of spacer widths, doping gradients, high-k gate dielectrics and effective channel lengths.

Effect of eucaloric high- and low-sucrose diets with identical macronutrient profile on insulin resistance and vascular risk - A randomized controlled trial

The long-term impact of dietary carbohydrate type, in particular sucrose, on insulin resistance and the development of diabetes and atherosclerosis is not established. Current guidelines for the healthy population advise restriction of sucrose intake. We investigated the effect of high- versus low-sucrose diet (25 vs. 10%, respectively, of total energy intake) in 13 healthy subjects aged 33 +/- 3 years (mean +/- SE), BMI 26.6 +/- 0.9 kg/m(2), in a randomized crossover design with sequential 6-week dietary interventions separated by a 4-week washout. Weight maintenance, eucaloric diets with identical macronutrient profiles and fiber content were designed. All food was weighed and distributed. Insulin action was assessed using a two-step euglycemic clamp; glycemic profiles were assessed by the continuous glucose monitoring system and vascular compliance by pulse-wave analysis. There was no change in weight across the study. Peripheral glucose uptake and suppression of endogenous glucose production were similar after each diet. Glycemic profiles and measures of vascular compliance did not change. A rise in total and LDL cholesterol was observed. In this study, a high-sucrose intake as part of an eucaloric, weight-maintaining diet had no detrimental effect on insulin sensitivity, glycemic profiles, or measures of vascular compliance in healthy nondiabetic subjects.

Correlation Effects in the Compton Profile of Silicon

Ab initio nonlocal pseudopotential variational quantum Monte Carlo techniques are used to compute the correlation effects on the valence momentum density and Compton profile of silicon. Our results for this case are in excellent agreement with the Lam-Platzman correction computed within the local density approximation. Within the approximations used, we rule out valence electron correlations as the dominant source of discrepancies between calculated and measured Compton profiles of silicon.