Engineering 3D printed microfluidic chips for the fabrication of nanomedicines

Currently, there is an unmet need to manufacture nanomedicines in a continuous and controlled manner. Three-dimensional (3D) printed microfluidic chips are an alternative to conventional PDMS chips as they can be easily designed and manufactured to allow for customized designs that are able to reproducibly manufacture nanomedicines at an affordable cost. The manufacturing of microfluidic chips using existing 3D printing technologies remains very challenging because of the intricate geometry of the channels. Here, we demonstrate the manufacture and characterization of nifedipine (NFD) polymeric nanoparticles based on Eudragit L-100 using 3D printed microfluidic chips with 1 mm diameter channels produced with two 3D printing techniques that are widely available, stereolithography (SLA) and fuse deposition modeling (FDM). Fabricated polymeric nanoparticles showed good encapsulation efficiencies and particle sizes in the range of 50–100 nm. SLA chips possessed better channel resolution and smoother channel surfaces, leading to smaller particle sizes similar to those obtained by conventional manufacturing methods based on solvent evaporation, while SLA manufactured nanoparticles showed a minimal burst effect in acid media compared to nanoparticles fabricated with FDM chips. Three-dimensional printed microfluidic chips are a novel and easily amenable cost-effective strategy to allow for customization of the design process for continuous manufacture of nanomedicines under controlled conditions, enabling easy scale-up and reducing nanomedicine development times, while maintaining high-quality standards

Engineering 3D printed microfluidic chips for the fabrication of nanomedicines

1.Purpose -- Nanomedicine manufacture remains expensive and difficult to scale-up which limits the uptake of nano-enabled technologies by industry. Thus, there is an urgent unmet need for continuous and controlled manufacturing processes. Microfluidic manufacture has emerged as a novel and easily adaptable strategy to overcome these challenges, but majority of chips used are fabricated using polydimethulsiloxane (PDMS) and soft mask lithography that remains tedious, not easily customizable and requires specialized equipment and expertise for their production. 3D printed chips are a novel and easily adaptable cost-effective alternative able to provide microfluidic chips for enabling quick pilot studies towards the manufacture of nanomedicines under controlled conditions with optimal and controlled characteristics enabling easy scale-up and shorter development times. However, for 3D printed chips to be successful as an alternative, 3D printing channels with adequate resolution to produce the required geometry needs to be demonstrated. In this work, we utilized the most easily accessible 3D printing techniques (fused deposition modelling (FDM) and sterolithography (SLA)) and commercially available solvent resistant filaments and resin to produce designed microfluidic chips with appropriate geometry and channel characteristics to allow for the manufacture of polymeric nanoparticles based on polymethacrylate polymers encapsulating high concentration of a BCS class II drug (nifedipine, NFD). 2.Method -- Chips were designed in Tinkercad® (Autodesk®) and measured 8.2 cm in length, 3.5 cm in width, and 0.7 cm in height. Channel length was 44 cm and the diameter was 1 mm. Chip designed was exported into a standard tessellation language (.stl) digital file. An Anycubic Mega Zero FDM printer printed 70 layers of the microfluidic chip at 245°C, with a 0.4 mm diameter nozzle, 0.1 mm layer height, and 10 mm/s printer and 30 mm/s travel speed with cyclic olefin copolymer filament. The Anycubic Photon Mono X (LCD-based SLA printer with 405 nm light source and 0.01 mm Z resolution) was used for stereolithography. Anycubic® UV sensitive resin (transparent yellow) was photopolymerized at 405 nm. The print settings were 0.05 mm layer height, 60 s bottom exposure, 3 s normal exposure, 1 s off-time, and 140 layers. Polymeric nifedipine loaded nanoparticles were prepared using solvent evaporation and microfluidically. For the latter, the aqueous phase (8 ml) consisting of Tween 80 in deionized water (0.25 % w/v) and the organic phase consisting of Eudragit L100-55 (30 mg) and NFD (10 mg) dissolved in ethanol (2 ml) were loaded into two 10 ml syringes. Using two syringe pumps (New Era Pump Systems, NY, USA), the organic phase was flown at a rate of 0.5 ml min-1 and the aqueous phase at 2 ml min-1. The eluate was rota-evaporated for 10 minutes at 150 rpm and 60 °C to remove the ethanol and centrifuged at 5,000 rpm for 5 minutes to remove any free NFD. Part of the supernatant was lyophilized for 24 hours under 0.2 mbar pressure at -50oC. Formulations were characterized in terms of drug loading, particle size, zeta potential and morphology and the channels were imaged with light microscopy, scanning electron microscopy while the surface roughness was measured with profilometry. Solid state characterisation of lyophilized particles were also undertaken. Release of NFD from nanoparticles was assessed using a type II dissolution apparatus (Ewerka DT 80, Heusenstamm, Germany) under simulated gastric and intestinal media (Ayyoubi S.). 3.Results --  The chip geometry produced was in close accordance to the .stl file sent for printing (Fig. 1a). The channel diameter ranged from 985 – 1015 µm. SLA-printed chips exhibited channels with a smoother surface (10.5-fold) than FDM chips. NFD nanoparticles showed a 7% greater drug encapsulation when manufactured by SLA than with FDM chips (one-way ANOVA, p < 0.05) which was closer to the loading reported by solvent evaporation. NFD nanoparticles manufactured using SLA chips were significantly smaller than those particles obtained from FDM chips, 68 ± 1 nm versus 75 ± 1 nm, respectively (one-way ANOVA, p < 0.05), which was closer to the particle size obtained by solvent evaporation (Fig. 2). Lyophilised nanoparticles showed similar FTIR, pXRD, and DSC patterns obtained from both SLA and FDM chips. NFD release was hampered in acidic media (<20% at 1 hour), but near complete released was achieved when the pH was raised to 6.8 within 6 hours, which was similar to that obtained for particles prepared with solvent evaluation (Fig. 3). However, NFD particles produced with FDM showed a burst release in acidic media (~40%) followed by controlled release in simulated intestinal media (p<0.05, One-way Anova). NFD localization within the particles produced with different 3D printed chips due differences in surface roughness and drug–polymer interactions are contributing to these findings. The smoother channels of SLA chips lead to a more homogenous loading process, where NFD is located within the core of the polymeric nanoparticles, which is further supported by the smaller particle size and controlled release profile in acidic media where NFD is more likely to be soluble.  4. Conclusion -- 3D printed microfluidic chips with 1 mm diameter channels have been successfully designed and manufactured and are capable to engineer polymeric nanoparticles with good encapsulation efficiencies and particle sizes of ~100 nm, like nanoparticles obtained by solvent evaporation. 3D printed microfluidic chips control the process and convert discontinuous methods into a continuous nanomedicine manufacturing process that are easily industrialized

The Montreal Cognitive Assessment (MoCA) - A Sensitive Screening Instrument for Detecting Cognitive Impairment in Chronic Hemodialysis Patients

BackgroundChronic kidney disease (CKD) patients undergoing hemodialysis (HD) therapy have an increased risk of developing cognitive impairment and dementia, which are known relevant factors in disease prognosis and therapeutic success, but still lack adequate screening in clinical routine. We evaluated the Montreal Cognitive Assessment (MoCA) for suitability in assessing cognitive performance in HD patients in comparison to the commonly used Mini-Mental State Examination (MMSE) and a detailed neuropsychological test battery, used as gold standard.Methods43 HD patients and 42 healthy controls with an average age of 58 years, were assessed with the MoCA, the MMSE and a detailed neuropsychological test battery, covering the domains of memory, attention, language, visuospatial and executive functions. Composite scores were created for comparison of cognitive domains and test results were analyzed using Spearman's correlation and linear regression. Cognitive dysfunction was defined using z-score values and predictive values were calculated. Sensitivity and specificity of the MoCA were determined using receiver operating characteristic (ROC) analysis.ResultsHD patients performed worse in all cognitive domains, especially in memory recall and executive functions. The MoCA correlated well with the detailed test battery and identified patients with cognitive impairment with a sensitivity of 76.7% and specificity of 78.6% for a cut-off value of ≤24 out of 30 points. In the detailed assessment executive functions accounted significantly for performance in the MoCA. The MMSE only discriminated weakly between groups.ConclusionsThe MoCA represents a suitable cognitive screening tool for hemodialysis patients, demonstrating good sensitivity and specificity levels, and covering executive functions, which appear to play an important role in cognitive performance of HD patients

Increased Cerebral Water Content in Hemodialysis Patients

Little information is available on the impact of hemodialysis on cerebral water homeostasis and its distribution in chronic kidney disease. We used a neuropsychological test battery, structural magnetic resonance imaging (MRI) and a novel technique for quantitative measurement of localized water content using 3T MRI to investigate ten hemodialysis patients (HD) on a dialysis-free day and after hemodialysis (2.4±2.2 hours), and a matched healthy control group with the same time interval. Neuropsychological testing revealed mainly attentional and executive cognitive dysfunction in HD. Voxel-based-morphometry showed only marginal alterations in the right inferior medial temporal lobe white matter in HD compared to controls. Marked increases in global brain water content were found in the white matter, specifically in parietal areas, in HD patients compared to controls. Although the global water content in the gray matter did not differ between the two groups, regional increases of brain water content in particular in parieto-temporal gray matter areas were observed in HD patients. No relevant brain hydration changes were revealed before and after hemodialysis. Whereas longer duration of dialysis vintage was associated with increased water content in parieto-temporal-occipital regions, lower intradialytic weight changes were negatively correlated with brain water content in these areas in HD patients. Worse cognitive performance on an attention task correlated with increased hydration in frontal white matter. In conclusion, long-term HD is associated with altered brain tissue water homeostasis mainly in parietal white matter regions, whereas the attentional domain in the cognitive dysfunction profile in HD could be linked to increased frontal white matter water content

ROC curves for the cognitive screening tests Montreal Cognitive Assessment and Mini-Mental State Examination.

<p>The receiver operating characteristics curves for the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) illustrate the discriminative capacity of each of the screening tests, displaying their individual sensitivity, specificity and area under the curve (AUC). The MoCA shows good levels of sensitivity and specificity, as well as an overall greater AUC than the MMSE, while the MMSE presents a high specificity and relatively low sensitivity. Notes. MoCA = Montreal Cognitive Assessment; MMSE = Mini-Mental State Examination; AUC = Area under the curve.</p

Demographic and health characteristics.

<p>Demographic and health characteristics.</p

Demographic and clinical characteristics of the hemodialysis patients and healthy control groups.

<p>All data shown as mean (SD), except where noted. Charlson Comorbidity Index (CCI) corrected for dialysis patients and corrected for age in the control group. CV = Cerebrovascular; py = pack years; CKD = Chronic kidney disease. Other causes include progression of CKD due to post-operative infections, reflux diseases, analgesic medication.</p><p>Demographic and clinical characteristics of the hemodialysis patients and healthy control groups.</p

Histogram.

<p>Distributions of the brain water content (X-axis) and T1 (Y-axis) from HD patients (red thin histogram lines before dialysis, thin green histograms lines after dialysis) and healthy controls (blue thin histogram lines for first time point, black for second time point) are shown. Left: Individual data and mean value histograms (bold) for T1 (Y-axis, left) reveal no significant differences in HD patients compared to healthy controls. Lower panel: Individual data as well as mean value histograms (bold) for water content (X-axis) reveal increased white matter water content (~2%) as shown by the observed shift, but only mild changes in gray matter in HD patients compared to controls.</p