Predicting phase resetting due to multiple stimuli

We generalized the phase resetting curve (PRC) to a more realistic case of neural oscillators receiving two or more inputs per cycle. The PRC tabulates the transient change in the firing period of a neuron due to an external perturbation, such as a presynaptic stimulus. We used a conductance-based model neuron to estimate experimentally the two-stimulus PRC and compared the results against our mathematical prediction based on the assumption of instantaneous recurrent stimulation. Within the limits of the recurrent stimulation assumptions, we found that the newly introduced prediction for the two-stimulus PRC matched experimental measurements. Our new results open the possibility of a more realistic approach to predicting phase-locked modes in neural networks, such as the synchronous activity of large networks during epileptic seizures

3D printing of tablets using inkjet with UV photoinitiation

Additive manufacturing (AM) offers significant potential benefits in the field of drug delivery and pharmaceutical/medical device manufacture. Of AM processes, 3D inkjet printing enables precise deposition of a formulation, whilst offering the potential for significant scale up or scale out as a manufacturing platform. This work hypothesizes that suitable solvent based ink formulations can be developed that allow the production of solid dosage forms that meet the standards required for pharmaceutical tablets, whilst offering a platform for flexible and personalised manufacture. We demonstrate this using piezo-activated inkjetting to 3D print ropinirole hydrochloride. The tablets produced consist of a cross-linked poly(ethylene glycol diacrylate) (PEGDA) hydrogel matrix containing the drug, photoinitiated in a low oxygen environment using an aqueous solution of Irgacure 2959. At a Ropinirole HCl loading of 0.41 mg, drug release from the tablet is shown to be Fickian. Raman and IR spectroscopy indicate a high degree of cross-linking and formation of an amorphous solid dispersion. This is the first publication of a UV inkjet 3D printed tablet. Consequently, this work opens the possibility for the translation of scalable, high precision and bespoke ink-jet based additive manufacturing to the pharmaceutical sector

A Reactive Prodrug Ink Formulation Strategy for Inkjet 3D Printing of Controlled Release Dosage Forms and Implants

We propose a strategy for creating tuneable 3D printed drug delivery devices. 3D printing offers the opportunity for improved compliance and patient treatment outcomes through personalisation, but bottlenecks include finding formulations that provide a choice of drug loading and release rate, are tuneable and avoid the need for surgical removal. Our solution is to exploit 3D inkjet printing freedoms. We use a reactive prodrug that can polymerize into drug-attached macromolecules during 3D printing, and by tuning the hydrophilicity we can facilitate or hinder hydrolysis, which in turn controls the drug release. To demonstrate this approach, we attach ibuprofen to 2-hydroxyethyl acrylate through a cleavable ester bond, formulate it for inkjet 3D printing, and then print to produce a solid dosage form. This allows a much higher loading than is usually achievable-in our case up to 58 wt%. Of equal importance, the 3D inkjet printing freedoms mean that our drug delivery device is highly tuneable: by selection of spacer monomers to adjust the hydrophilicity; through geometry; by spatially varying the components. Consequently, we create bespoke, hierarchical release systems, from the molecular to macro. This approach represents a new paradigm for the formulation of printable inks for drug-loaded medical devices

Identification of novel ‘inks’ for 3D printing using high throughput screening: bioresorbable photocurable polymers for controlled drug delivery

A robust discovery methodology is presented to identify novel biomaterials suitable for 3D printing. Currently the application of Additive Manufacturing is limited by the availability of functional inks, especially in the area of biomaterials-this method tackles this problem for the first time allowing hundreds of formulations to be readily assessed. Several functional properties, including the release of an antidepressive drug (paroxetine), cytotoxicity and printability are screened for 253 new ink formulations in a high-throughput format as well as mechanical properties. The selected candidates with the desirable properties are successfully scaled up using 3D printing into a range of objects architectures. A full drug release study, degradability and tensile modulus experiments are presented on a simple architecture to validating the suitability of this methodology to identify printable inks for 3D printing devices with bespoke properties

Ink-jet 3D printing as a strategy for developing bespoke non-eluting biofilm resistant medical devices

Chronic infection as a result of bacterial biofilm formation on implanted medical devices is a major global healthcare problem requiring new biocompatible, biofilm-resistant materials. Here we demonstrate how bespoke devices can be manufactured through ink-jet-based 3D printing using bacterial biofilm inhibiting formulations without the need for eluting antibiotics or coatings. Candidate monomers were formulated and their processability and reliability demonstrated. Formulations for in vivo evaluation of the 3D printed structures were selected on the basis of their in vitro bacterial biofilm inhibitory properties and lack of mammalian cell cytotoxicity. In vivo in a mouse implant infection model, Pseudomonas aeruginosa biofilm formation on poly-TCDMDA was reduced by ∼99% when compared with medical grade silicone. Whole mouse bioluminescence imaging and tissue immunohistochemistry revealed the ability of the printed device to modulate host immune responses as well as preventing biofilm formation on the device and infection of the surrounding tissues. Since 3D printing can be used to manufacture devices for both prototyping and clinical use, the versatility of ink-jet based 3D-printing to create personalised functional medical devices is demonstrated by the biofilm resistance of both a finger joint prosthetic and a prostatic stent printed in poly-TCDMDA towards P. aeruginosa and Staphylococcus aureus

Inkjet based 3D Printing of bespoke medical devices that resist bacterial biofilm formation

We demonstrate the formulation of advanced functional 3D printing inks that prevent the formation of bacterial biofilms in vivo. Starting from polymer libraries, we show that a biofilm resistant object can be 3D printed with the potential for shape and cell instructive function to be selected independently. When tested in vivo, the candidate materials not only resisted bacterial attachment but drove the recruitment of host defences in order to clear infection. To exemplify our approach, we manufacture a finger prosthetic and demonstrate that it resists biofilm formation – a cell instructive function that can prevent the development of infection during surgical implantation. More widely, cell instructive behaviours can be ‘dialled up’ from available libraries and may include in the future such diverse functions as the modulation of immune response and the direction of stem cell fate

Correction to “Bespoke 3D-Printed Polydrug Implants Created via Microstructural Control of Oligomers”

The chemical structure of the drug trandolapril has been corrected in Figure 4c. The conclusions of the work have not been affected by this correction. (Figure present)

Exploiting Generative Design for Multi-Material Inkjet 3D Printed Cell Instructive, Bacterial Biofilm Resistant Composites

As our understanding of disease grows, it is becoming established that treatment needs to be personalized and targeted to the needs of the individual. In this paper we show that multi-material inkjet-based 3D printing, when backed with generative design algorithms, can bring a step change in the personalization of medical devices. We take cell-instructive materials known for their resistance to bacterial biofilm formation and reformulate for multi-material inkjet-based 3D printing. Specimens with customizable mechanical moduli are obtained without loss of their cell-instructive properties. The manufacturing is coupled to a design algorithm that takes a user-specified deformation and computes the distribution of the materials needed to meet the target under given load constraints. Optimisation led to a voxel map file defining where different materials should be placed. Manufactured products were assessed against the mechanical and cell-instructive specifications and ultimately showed how multifunctional personalization emerges from generative design driven 3D printing

Exploiting Generative Design for 3D Printing of Bacterial Biofilm Resistant Composite Devices

open access articleAs the understanding of disease grows, so does the opportunity for personalization of therapies targeted to the needs of the individual. To bring about a step change in the personalization of medical devices it is shown that multi-material inkjet-based 3D printing can meet this demand by combining functional materials, voxelated manufacturing, and algorithmic design. In this paper composite structures designed with both controlled deformation and reduced biofilm formation are manufactured using two formulations that are deposited selectively and separately. The bacterial biofilm coverage of the resulting composites is reduced by up to 75% compared to commonly used silicone rubbers, without the need for incorporating bioactives. Meanwhile, the composites can be tuned to meet user defined mechanical performance with ±10% deviation. Device manufacture is coupled to finite element modelling and a genetic algorithm that takes the user-specified mechanical deformation and computes the distribution of materials needed to meet this under given load constraints through a generative design process. Manufactured products are assessed against the mechanical and bacterial cell-instructive specifications and illustrate how multifunctional personalization can be achieved using generative design driven multi-material inkjet based 3D printing

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care