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.

The determination of optimal processing conditions for PLA and PLA/CaCO3 in twin screw extrusion using DoE and multivariate analysis

Biodegradable polymers, such as PLA (Polylactide), come from renewable resources like corn starch and if disposed of correctly, degrade and become harmless to the ecosystem making them attractive alternatives to petroleum based polymers. PLA in particular is used in a variety of applications including medical devices, food packaging and waste disposal packaging. However, the industry faces challenges in melt processing of PLA due to its poor thermal stability which is influenced by processing temperatures and shearing.
Identification and control of suitable processing conditions is extremely challenging, usually relying on trial and error, and often sensitive to batch to batch variations. Off-line assessment in a lab environment can result in high scrap rates, long lead times and lengthy and expensive process development. Scrap rates are typically in the region of 25-30% for medical grade PLA costing between €2000-€5000/kg.
Additives are used to enhance material properties such as mechanical properties and may also have a therapeutic role in the case of bioresorbable medical devices, for example the release of calcium from orthopaedic implants such as fixation screws promotes healing. Additives can also reduce the costs involved as less of the polymer resin is required.
This study investigates the scope for monitoring, modelling and optimising processing conditions for twin screw extrusion of PLA and PLA w/calcium carbonate to achieve desired material properties. A DAQ system has been constructed to gather data from a bespoke measurement die comprising melt temperature; pressure drop along the length of the die; and UV-Vis spectral data which is shown to correlate to filler dispersion. Trials were carried out under a range of processing conditions using a Design of Experiments approach and samples were tested for mechanical properties, degradation rate and the release rate of calcium. Relationships between recorded process data and material characterisation results are explored.

The association between myopia and various subtypes of lens opacity: SEE (Salisbury Eye Evaluation) project.

PURPOSE: To establish the relationship between myopia and lens opacity. DESIGN: Population-based cross-sectional study. PARTICIPANTS: Two thousand five hundred twenty participants from the Salisbury Eye Evaluation aged 65 to 84 years. METHODS: Participants filled out questionnaires regarding medical history, social habits, and a detailed history of distance spectacle wear. They underwent a full ocular examination. Lens photographs were taken for assessment of lens opacity using the Wilmer grading system. Multivariate logistic regression models using generalized estimating equations were used to analyze the relationship between lens opacity type and degree of myopia, while accounting for potential confounders. MAIN OUTCOME MEASURES: Presence of posterior subcapsular opacity, cortical opacity, or nuclear opacity. RESULTS: Significant associations were found between myopia and both nuclear and posterior subcapsular opacities. For nuclear opacity, the odds ratios (ORs) were 2.25 for myopia between -0.50 diopters (D) and -1.99 D (P<0.001), 3.65 for myopia between -2.00 D and -3.99 D (P<0.001), 4.54 for myopia between -4.00 D and -5.99 D (P<0.001), and 3.61 for myopia -6.00 D or more (P = 0.002). For posterior subcapsular cataracts, ORs were 1.59 for myopia between -0.50 D and -1.99 D (P = 0.11), 3.22 for myopia between -2.00 D and -3.99 D (P = 0.002), 5.36 for myopia between -4.00 D and -5.99 D (P<0.001), and 12.34 for myopia -6.00 D or more (P<0.001). No association was found between myopia and cortical opacity. The association between posterior subcapsular opacity and myopia was equally strong for those wearing glasses by age 21 years and for those without glasses; for nuclear opacity, significantly higher ORs were found for myopes who started wearing glasses after age 21. CONCLUSIONS: These results confirm the previously reported association between myopia, posterior subcapsular opacity, and nuclear opacity. Furthermore, the strong association between early spectacle wear and posterior subcapsular opacity among myopes, absent for nuclear opacity, suggests that myopia may precede opacity in the case of posterior subcapsular opacity, but not nuclear opacity. Measures of association between posterior subcapsular opacity and myopia were stronger in the current study than have previously been found. Longitudinal studies to confirm the association are warranted.

Nonequilibrium processes from generalized Langevin equations: Realistic nanoscale systems connected to two thermal baths

We extend the generalized Langevin equation (GLE) method [L. Stella, C. D. Lorenz, and L. Kantorovich, Phys. Rev. B 89, 134303 (2014)] to model a central classical region connected to two realistic thermal baths at two different temperatures. In such nonequilibrium conditions a heat flow is established, via the central system, in between the two baths. The GLE-2B (GLE two baths) scheme permits us to have a realistic description of both the dissipative central system and its surrounding baths. Following the original GLE approach, the extended Langevin dynamics scheme is modified to take into account two sets of auxiliary degrees of freedom corresponding to the mapping of the vibrational properties of each bath. These auxiliary variables are then used to solve the non-Markovian dissipative dynamics of the central region. The resulting algorithm is used to study a model of a short Al nanowire connected to two baths. The results of the simulations using the GLE-2B approach are compared to the results of other simulations that were carried out using standard thermostatting approaches (based on Markovian Langevin and Nosé-Hoover thermostats). We concentrate on the steady-state regime and study the establishment of a local temperature profile within the system. The conditions for obtaining a flat profile or a temperature gradient are examined in detail, in agreement with earlier studies. The results show that the GLE-2B approach is able to treat, within a single scheme, two widely different thermal transport regimes, i.e., ballistic systems, with no temperature gradient, and diffusive systems with a temperature gradient.