Algorithms for the self-optimisation of chemical reactions

Self-optimising chemical systems have experienced a growing momentum in recent years, with the evolution of self-optimising platforms leading to their application for reaction screening and chemical synthesis. With the desire for improved process sustainability, self-optimisation provides a cheaper, faster and greener approach to the chemical development process. The use of such platforms aims to enhance the capabilities of the researcher by removing the need for labor-intensive experimentation, allowing them to focus on more challenging tasks. The establishment of these systems have enabled opportunities for self-optimising platforms to become a key element of a laboratory’s repertoire. To enable the wider adoption of self-optimising chemical platforms, this review summarises the history of algorithmic usage in chemical reaction self-optimisation, detailing the functionality of the algorithms and their applications in a way that is accessible for chemists and highlights opportunities for the further exploitation of algorithms in chemical synthesis moving forward

A Hybridised Optimisation of an Automated Photochemical Continuous Flow Reactor

A new hybridized algorithm that combines process optimisation with response surface mapping was developed and applied in an automated continuous flow reaction. Moreover, a photochemical cascade CSTR was developed and characterised by chemical actinometry, showing photon flux density of ten times greater than previously reported in batch. The success of the algorithm was then evaluated in the aerobic oxidation of sp3 C–H bonds using benzophenone as photosensitizer in the newly developed photo reactor

Automated Self-Optimisation of Multi-Step Reaction and Separation Processes Using Machine Learning

There has been an increasing interest in the use of automated self-optimising continuous flow platforms for the development and manufacture in synthesis in recent years. Such processes include multiple reactive and work-up steps, which need to be efficiently optimised. Here, we report the combination of multi-objective optimisation based on machine learning methods (TSEMO algorithm) with self-optimising platforms for the optimisation of multi-step continuous reaction processes. This is demonstrated for a pharmaceutically relevant Sonogashira reaction. We demonstrate how optimum reaction conditions are re-evaluated with the changing downstream work-up specifications in the active learning process. Furthermore, a Claisen-Schmidt condensation reaction with subsequent liquid-liquid separation was optimised with respect to three-objectives. This approach provides the ability to simultaneously optimise multi-step processes with respect to multiple objectives, and thus has the potential to make substantial savings in time and resources

Rapid, Automated Determination of Reaction Models and Kinetic Parameters

We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and kinetic parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding with minimal user input. An automated flow chemistry platform was employed to initially conduct linear flow-ramp experiments to rapidly map the reaction profile of three processes using transient flow data. Following experimental data acquisition, a computational approach was utilised to discriminate between all possible reaction models as well as identify the correct kinetic parameters for each process. Species that are known to participate in the process (starting materials, intermediates, products) are initially inputted by the user prior to flow ramp experiments, then all possible model candidates are compiled into a model library based on their potential to occur after mass balance assessment. Parallel computational optimisation then evaluates each model by algorithmically altering the kinetic parameters of the model to allow convergence of a simulated kinetic curve to the experimental data provided. Statistical analysis then determines the most likely reaction model based on model simplicity and agreement with experimental data. This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost. The computational approach herein described can be employed using data from any set of experiments and the code is open-source

Evaluating Active U: an Internet-mediated physical activity program.

Background: Engaging in regular physical activity can be challenging, particularly during the winter months. To promote physical activity at the University of Michigan during the winter months, an eight-week Internet-mediated program (Active U) was developed providing participants with an online physical activity log, goal setting, motivational emails, and optional team participation and competition. Methods: This study is a program evaluation of Active U. Approximately 47,000 faculty, staff, and graduate students were invited to participate in the online Active U intervention in the winter of 2007. Participants were assigned a physical activity goal and were asked to record each physical activity episode into the activity log for eight weeks. Statistics for program reach, effectiveness, adoption, and implementation were calculated using the Re-Aim framework. Multilevel regression analyses were used to assess the decline in rates of data entry and goal attainment during the program, to assess the likelihood of joining a team by demographic characteristics, to test the association between various predictors and the number of weeks an individual met his or her goal, and to analyze server load. Results: Overall, 7,483 individuals registered with the Active U website (≈16% of eligible), and 79% participated in the program by logging valid data at least once. Staff members, older participants, and those with a BMI < 25 were more likely to meet their weekly physical activity goals, and average rate of meeting goals was higher among participants who joined a competitive team compared to those who participated individually (IRR = 1.28, P < .001). Conclusion: Internet-mediated physical activity interventions that focus on physical activity logging and goal setting while incorporating team competition may help a significant percentage of the target population maintain their physical activity during the winter months

Cellulose acetate phthalate, a common pharmaceutical excipient, inactivates HIV-1 and blocks the coreceptor binding site on the virus envelope glycoprotein gp120

BACKGROUND: Cellulose acetate phthalate (CAP), a pharmaceutical excipient used for enteric film coating of capsules and tablets, was shown to inhibit infection by the human immunodeficiency virus type 1 (HIV-1) and several herpesviruses. CAP formulations inactivated HIV-1, herpesvirus types 1 (HSV-1) and 2 (HSV-2) and the major nonviral sexually transmitted disease (STD) pathogens and were effective in animal models for vaginal infection by HSV-2 and simian immunodeficiency virus. METHODS: Enzyme-linked immunoassays and flow cytometry were used to demonstrate CAP binding to HIV-1 and to define the binding site on the virus envelope. RESULTS: 1) CAP binds to HIV-1 virus particles and to the envelope glycoprotein gp120; 2) this leads to blockade of the gp120 V3 loop and other gp120 sites resulting in diminished reactivity with HIV-1 coreceptors CXCR4 and CCR5; 3) CAP binding to HIV-1 virions impairs their infectivity; 4) these findings apply to both HIV-1 IIIB, an X4 virus, and HIV-1 BaL, an R5 virus. CONCLUSIONS: These results provide support for consideration of CAP as a topical microbicide of choice for prevention of STDs, including HIV-1 infection

Congenital anomalies in low- and middle-income countries: the unborn child of global surgery.

Surgically correctable congenital anomalies cause a substantial burden of global morbidity and mortality. These anomalies disproportionately affect children in low- and middle-income countries (LMICs) due to sociocultural, economic, and structural factors that limit the accessibility and quality of pediatric surgery. While data from LMICs are sparse, available evidence suggests that the true human and financial cost of congenital anomalies is grossly underestimated and that pediatric surgery is a cost-effective intervention with the potential to avert significant premature mortality and lifelong disability

Water dispersible microbicidal cellulose acetate phthalate film

BACKGROUND: Cellulose acetate phthalate (CAP) has been used for several decades in the pharmaceutical industry for enteric film coating of oral tablets and capsules. Micronized CAP, available commercially as "Aquateric" and containing additional ingredients required for micronization, used for tablet coating from water dispersions, was shown to adsorb and inactivate the human immunodeficiency virus (HIV-1), herpesviruses (HSV) and other sexually transmitted disease (STD) pathogens. Earlier studies indicate that a gel formulation of micronized CAP has a potential as a topical microbicide for prevention of STDs including the acquired immunodeficiency syndrome (AIDS). The objective of endeavors described here was to develop a water dispersible CAP film amenable to inexpensive industrial mass production. METHODS: CAP and hydroxypropyl cellulose (HPC) were dissolved in different organic solvent mixtures, poured into dishes, and the solvents evaporated. Graded quantities of a resulting selected film were mixed for 5 min at 37°C with HIV-1, HSV and other STD pathogens, respectively. Residual infectivity of the treated viruses and bacteria was determined. RESULTS: The prerequisites for producing CAP films which are soft, flexible and dispersible in water, resulting in smooth gels, are combining CAP with HPC (other cellulose derivatives are unsuitable), and casting from organic solvent mixtures containing ≈50 to ≈65% ethanol (EtOH). The films are ≈100 µ thick and have a textured surface with alternating protrusions and depressions revealed by scanning electron microscopy. The films, before complete conversion into a gel, rapidly inactivated HIV-1 and HSV and reduced the infectivity of non-viral STD pathogens >1,000-fold. CONCLUSIONS: Soft pliable CAP-HPC composite films can be generated by casting from organic solvent mixtures containing EtOH. The films rapidly reduce the infectivity of several STD pathogens, including HIV-1. They are converted into gels and thus do not have to be removed following application and use. In addition to their potential as topical microbicides, the films have promise for mucosal delivery of pharmaceuticals other than CAP

Robust Poisson Surface Reconstruction

Abstract. We propose a method to reconstruct surfaces from oriented point clouds with non-uniform sampling and noise by formulating the problem as a convex minimization that reconstructs the indicator func-tion of the surface’s interior. Compared to previous models, our recon-struction is robust to noise and outliers because it substitutes the least-squares fidelity term by a robust Huber penalty; this allows to recover sharp corners and avoids the shrinking bias of least squares. We choose an implicit parametrization to reconstruct surfaces of unknown topology and close large gaps in the point cloud. For an efficient representation, we approximate the implicit function by a hierarchy of locally supported basis elements adapted to the geometry of the surface. Unlike ad-hoc bases over an octree, our hierarchical B-splines from isogeometric analysis locally adapt the mesh and degree of the splines during reconstruction. The hi-erarchical structure of the basis speeds-up the minimization and efficiently represents clustered data. We also advocate for convex optimization, in-stead isogeometric finite-element techniques, to efficiently solve the min-imization and allow for non-differentiable functionals. Experiments show state-of-the-art performance within a more flexible framework.