Discriminative and quantitative analysis of norepinephrine and epinephrine by surface-enhanced Raman spectroscopy with gold nanoparticle suspensions.

Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique capable of increasing the Raman signal of an analyte using specific nanostructures. The close contact between those nanostructures, usually a suspension of nanoparticles, and the molecule of interest produces an important exaltation of the intensity of the Raman signal. Even if the exaltation leads to an improvement of Raman spectroscopy sensitivity, the complexity of the SERS signal and the numbers of parameters to be controlled allow the use of SERS for detection rather than quantification. The aim of this study was to develop a robust discriminative and quantitative analysis in accordance with pharmaceutical standards. In this present work, we develop a discriminative and quantitative analysis based on the previous optimized parameters obtained by the design of experiments fixed for norepinephrine (NOR) and extended to epinephrine (EPI) which are two neurotransmitters with very similar structures. Studying the short evolution of the Raman signal intensity over time coupled with chemometric tools allowed the identification of outliers and their removal from the data set. The discriminant analysis showed an excellent separation of EPI and NOR. The comparative analysis of the data showed the superiority of the multivariate analysis after logarithmic transformation. The quantitative analysis allowed the development of robust quantification models from several gold nanoparticle batches with limits of quantification of 32 µg/mL for NOR and below 20 µg/mL for EPI even though no Raman signal is observable for such concentrations. This study improves SERS analysis over ultrasensitive detection for discrimination and quantification using a handheld Raman spectrometer.

Effectiveness of a 'do not interrupt' vest intervention to reduce medication errors during medication administration: a multicenter cluster randomized controlled trial.

BACKGROUND: The use of a 'do not interrupt' vest during medication administration rounds is recommended but there have been no controlled randomized studies to evaluate its impact on reducing administration errors. We aimed to evaluate the impact of wearing such a vest on reducing such errors. The secondary objectives were to evaluate the types and potential clinical impact of errors, the association between errors and several risk factors (such as interruptions), and nurses' experiences. METHODS: This was a multicenter, cluster, controlled, randomized study (March-July 2017) in 29 adult units (4 hospitals). Data were collected by direct observation by trained observers. All nurses from selected units were informed. A 'Do not interrupt' vest was implemented in all units of the experimental group. A poster was placed at the entrance of these units to inform patients and relatives. The main outcome was the administration error rate (number of Opportunities for Error (OE), calculated as one or more errors divided by the Total Opportunities for Error (TOE) and multiplied by 100). RESULTS: We enrolled 178 nurses and 1346 patients during 383 medication rounds in 14 units in the experimental group and 15 units in the control group. During the intervention period, the administration error rates were 7.09% (188 OE with at least one error/2653 TOE) for the experimental group and 6.23% (210 OE with at least one error/3373 TOE) for the control group (p = 0.192). Identified risk factors (patient age, nurses' experience, nurses' workload, unit exposition, and interruption) were not associated with the error rate. The main error type observed for both groups was wrong dosage-form. Most errors had no clinical impact for the patient and the interruption rates were 15.04% for the experimental group and 20.75% for the control group. CONCLUSIONS: The intervention vest had no impact on medication administration error or interruption rates. Further studies need to be performed taking into consideration the limitations of our study and other risk factors associated with other interventions, such as nurse's training and/or a barcode system. TRIAL REGISTRATION: The PERMIS study protocol (V2-1, 11/04/2017) was approved by institutional review boards and ethics committees (CPP Ile de France number 2016-A00211-50, CNIL 21/03/2017, CCTIRS 11/04/2016). It is registered at ClinicalTrials.gov (registration number: NCT03062852 , date of first registration: 23/02/2017).

A mathematical approach to deal with nanoparticle polydispersity in surface enhanced Raman spectroscopy to quantify antineoplastic agents.

Antineoplastic agents are, for most of them, highly toxic drugs prepared at hospital following individualized prescription. To protect patients and healthcare workers, it is important to develop analytical tools able to identify and quantify such drugs on a wide concentration range. In this context, surface enhanced Raman spectroscopy (SERS) has been tested as a specific and sensitive technique. Despite the standardization of the nanoparticle synthesis, a polydispersity of nanoparticles in the suspension and a lack of reproducibility persist. This study focuses on the development of a new mathematical approach to deal with this nanoparticle polydispersity and its consequences on SERS signal variability through the feasibility of 5-fluorouracil (5FU) quantification using silver nanoparticles (AgNPs) and a handled Raman spectrophotometer. Variability has been maximized by synthetizing six different batches of AgNPs for an average size of 24.9 nm determined by transmission electron microscopy, with residual standard deviation of 17.0%. Regarding low performances of the standard multivariate data processing, an alternative approach based on the nearest neighbors were developed to quantify 5FU. By this approach, the predictive performance of the 5FU concentration was significantly improved. The mean absolute relative error (MARE) decreased from 16.8% with the traditional approach based on PLS regression to 6.30% with the nearest neighbors approach (p-value < 0.001). This study highlights the importance of developing mathematics adapted to SERS analysis which could be a step to overcome the spectral variability in SERS and thus participate in the development of this technique as an analytical tool in quality control to quantify molecules with good performances, particularly in the pharmaceutical field.

Integration of a Commercial Barcode-Assisted Medication Dispensing System in a Teaching Hospital.

OBJECTIVES: A commercial barcode-assisted medication administration (BCMA) system was integrated to secure the medication process and particularly the dispensing stage by technicians and the administration stage with nurses. We aimed to assess the impact of this system on medication dispensing errors and barriers encountered during integration process. METHODS: We conducted a controlled randomized study in a teaching hospital, during dispensing process at the pharmacy department. Four wards were randomized in the experimental group and control group, with two wards using the system during 3 days with dedicated pharmacy technicians. The system was a closed loop system without information return to the computerized physician order entry system. The two dedicated technicians had a 1-week training session. Observations were performed by one observer among the four potential observers previously trained. The main outcomes assessed were dispensing error rates and the identification of barriers encountered to expose lessons learned from this study. RESULTS: There was no difference between the dispensing error rate of the control and experimental groups (7.9% for both, p = 0.927). We identified 10 barriers to pharmacy barcode-assisted system technology deployment. They concerned technical (problems with semantic interoperability interfaces, bad user interface, false errors generated, lack of barcodes), structural (poor integration with local information technology), work force (short staff training period, insufficient workforce), and strategic issues (system performance problems, insufficient budget). CONCLUSION: This study highlights the difficulties encountered in integrating a commercial system in current hospital information systems. Several issues need to be taken into consideration before the integration of a commercial barcode-assisted system in a teaching hospital. In our experience, interoperability of this system with the electronic health record is the key for the success of this process with an entire closed loop system from prescription to administration. BCMA system at the dispensing process remains essential to purchase securing medication administration process.

Impact of drug storage systems: a quasi-experimental study with and without an automated-drug dispensing cabinet.

OBJECTIVE: To compare the costs and benefits of an automated-drug dispensing cabinet (ADC) versus traditional floor stock storage (TFSS). DESIGN: A quasi-experimental multicenter study conducted during 2015. SETTING: A teaching hospital (814 beds) equipped with 43 ADCs and a not-for-profit teaching hospital (643 beds) equipped with 38 TFSS systems, in Paris, France. PARTICIPANTS: All the wards of the two hospitals were included in the study. INTERVENTION(S): ADC versus TFSS. MAIN OUTCOME MEASURE(S): A composite outcome composed of cost and benefits. RESULTS: The total cost with payback period was substantially higher for the ADCs (574 006€ for 41 ADCs) than TFSS (190 305€ for 30 TFSS systems). The mean number of costly drugs and units were significantly higher for ADCs (P < 0.001). There was no significant difference in the mean number of overall drugs and units. There were significantly fewer urgent global deliveries with ADCs than TFSS units. Nurses' satisfaction with ADCs was high and the prevalence of medication process errors related to ADCs was low. No event due to storage errors was reported for ADCs and nine events were reported for TFSS units. On the contrary, informatic-related events increased with the use of ADCs, as expected. CONCLUSIONS: Overall, ADCs are well-established in wards and are particularly appreciated by nurses. A significant difference in the initial investment cost was confirmed, but it must be adjusted over time. This difference is offset in the long-term by gains in preparation time and fewer medication process errors, securing the medication process.

A centralized automated-dispensing system in a French teaching hospital: return on investment and quality improvement.

OBJECTIVES: To evaluate the return on investment (ROI) and quality improvement after implementation of a centralized automated-dispensing system after 8 years of use. DESIGN: Prospective evaluation of ROI; before and after study to evaluate dispensing errors; user satisfaction questionnaire after 8 years of use. SETTING: The study was conducted at a French teaching hospital in the pharmacy department, which is equipped with decentralized automated medication cabinets in the wards. PARTICIPANTS: Pharmacy staff (technicians and residents). INTERVENTION(S): Implementation of a centralized automated-dispensing robot. MAIN OUTCOME MEASURE(S): The true ROI was prospectively and annually compared to estimated returns calculated after implementation and upgrade of the robot; dispensing errors determined by observation of global deliveries and the satisfaction of users based on a validated questionnaire were evaluated. RESULTS: Following the upgrade, we found little difference for the ROI (+1.86%). The payback period increased by almost 3 years. There was a significant reduction of dispensing errors, from 2.9% to 1.7% (P < 0.001). User satisfaction of the robot by the pharmacy staff was reported (score of 5.52 ± 1.20 out of 7). CONCLUSIONS: These systems are worthwhile investments and largely contribute to improving the quality and safety of the medication process.

Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach.

The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300 data scientists in collaborative work. Using machine learning, the prediction of the four mAbs samples was considerably improved. The best predictive model showed a combined error of 2.4% versus 14.6% using linear approach. The concentration and classification errors were 5.8% and 0.7%, only three spectra were misclassified over the 429 spectra of the test set. This large improvement obtained with machine learning techniques was uniform for all molecules but maximal for Bevacizumab with an 88.3% reduction on combined errors (2.1% versus 17.9%).

Rapid discrimination and quantification analysis of five antineoplastic drugs in aqueous solutions using Raman spectroscopy.

The aim of this study was to assess the ability of Raman spectroscopy to discriminate and quantify five antineoplastic drugs in an aqueous matrix at low concentrations before patient administration. Five antineoplastic drugs were studied at therapeutic concentrations in aqueous 0.9% sodium chloride: 5-fluorouracil (5FU), gemcitabine (GEM), cyclophophamide (CYCLO), ifosfamide (IFOS) and doxorubicin (DOXO). All samples were packaged in glass vials and analyzed using Raman spectrometry from 400 to 4000cm-1. Discriminant analyses were performed using Partial Least Squares Discriminant Analysis (PLS-DA) and quantitative analyses using PLS regression. The best discrimination model was obtained using hierarchical PLS-DA models including three successive models for concentrations higher than the lower limit of quantification (0% of fitting and cross-validation error rate with an excellent accuracy of 100%). According to these hierarchical discriminative models, 90.8% (n=433) of external validation samples were correctly predicted, 2.5% (n=12) were misclassified and 6.7% (n=32) of the external validation set were not assigned. The quantitative analysis was characterized by the RMSEP that ranged from 0.23mg/mL for DOXO to 3.05mg/mL for 5FU. The determination coefficient (R2) was higher than 0.9994 for all drugs evaluated except for 5FU (R2=0.9986). This study provides additional information about the potential value of Raman spectroscopy for real-time quality control of cytotoxic drugs in hospitals. In some situations, this technique therefore constitutes a powerful alternative to usual methods with ultraviolet (UV) detection to ensure the correct drug and the correct dose in solutions before administration to patients and to limit exposure of healthcare workers during the analytical control process.

Safety analysis of occupational exposure of healthcare workers to residual contaminations of cytotoxic drugs using FMECA security approach.

Handling cytotoxic drugs is associated with chemical contamination of workplace surfaces. The potential mutagenic, teratogenic and oncogenic properties of those drugs create a risk of occupational exposure for healthcare workers, from reception of starting materials to the preparation and administration of cytotoxic therapies. The Security Failure Mode Effects and Criticality Analysis (FMECA) was used as a proactive method to assess the risks involved in the chemotherapy compounding process. FMECA was carried out by a multidisciplinary team from 2011 to 2016. Potential failure modes of the process were identified based on the Risk Priority Number (RPN) that prioritizes corrective actions. Twenty-five potential failure modes were identified. Based on RPN results, the corrective actions plan was revised annually to reduce the risk of exposure and improve practices. Since 2011, 16 specific measures were implemented successively. In six years, a cumulative RPN reduction of 626 was observed, with a decrease from 912 to 286 (-69%) despite an increase of cytotoxic compounding activity of around 23.2%. In order to anticipate and prevent occupational exposure, FMECA is a valuable tool to identify, prioritize and eliminate potential failure modes for operators involved in the cytotoxic drug preparation process before the failures occur.

Rapid discrimination and determination of antibiotics drugs in plastic syringes using near infrared spectroscopy with chemometric analysis: Application to amoxicillin and penicillin.

The aim of this study was to investigate near infrared spectroscopy (NIRS) combined to chemometric analysis to discriminate and quantify three antibiotics by direct measurement in plastic syringes.Solutions of benzylpenicillin (PENI), amoxicillin (AMOX) and amoxicillin/clavulanic acid (AMOX/CLAV) were analyzed at therapeutic concentrations in glass vials and plastic syringes with NIR spectrometer by direct measurement. Chemometric analysis using partial least squares regression and discriminative analysis was conducted to develop qualitative and quantitative calibration models. Discrimination of the three antibiotics was optimal for concentrated solutions with 100% of accuracy. For quantitative analysis, the three antibiotics furnished a linear response (R²>0.9994) for concentrations ranging from 0.05 to 0.2 g/mL for AMOX, 0.1 to 1.0 MUI/mL for PENI and 0.005 to 0.05 g/mL for AMOX/CLAV with excellent repeatability (maximum 1.3%) and intermediate precision (maximum of 3.2%). Based on proposed models, 94.4% of analyzed AMOX syringes, 80.0% of AMOX/CLAV syringes and 85.7% of PENI syringes were compliant with a relative error including the limit of ± 15%.NIRS as rapid, non-invasive and non-destructive analytical method represents a potentially powerful tool to further develop for securing the drug administration circuit of healthcare institutions to ensure that patients receive the correct product at the right dose.

Non-invasive quantification of 5 fluorouracil and gemcitabine in aqueous matrix by direct measurement through glass vials using near-infrared spectroscopy.

Fourier transform near infrared spectroscopy (NIRS) was used for quantitative analysis of two cytotoxic drugs used in pharmaceutical infusion, 5-fluorouracil (5FU) and gemcitabine (GEM), at therapeutic concentrations in aqueous matrix. Spectra were collected from 4000 cm(-1) to 13,000 cm(-1) by direct measurement through standard glass vials and calibration models were developed for 5FU and GEM using partial least-squares regression. NIR determination coefficient (R(2)) greater than 0.9992, root-mean-square-error of cross-validation (RMESCV) of 0.483 mg/ml for 5FU and 0.139 mg/ml for GEM and the root mean square error of prediction (RMSEP) of 0.519 for 5FU and 0.108 mg/ml for GEM show a good prediction ability of NIR spectroscopy to predict 5FU and GEM concentrations directly through a glass packaging. According to accuracy profile, the linearity was validated from 7 to 50mg/ml and 2 to 40 mg/ml for 5-fluorouracil and gemcitabine respectively. This new approach for cytotoxic drugs control at hospital has shown the feasibility of near infrared spectroscopy to quantify antineoplastic drugs in aqueous matrix by a direct measurement through glass vial in less than 1 min and by non-invasive measurement perfect to limit exposure of operator to cytotoxic drugs.

Effectiveness of cleaning of workplace cytotoxic surface.

PURPOSE: To minimize the risk of chronic occupational exposure of antineoplastic drugs, cleaning procedures must be evaluated. This study was conducted to compare the detergent efficiency of cleaning solutions (two hydro-alcoholic solutions, three disinfectants and two detergents) used in different cleaning protocols. METHODS: The central surface of a stainless steel plate (30 × 50 cm) was exposed to a carboplatin solution equivalent to 105,100 ng of platinum. After cleaning according to a standardized protocol, residual platinum contaminations were assayed on 10 × 10 cm sections. RESULTS: After standardized cleaning, the residual quantity of platinum on the surface of the deposit accounted for between 1.0 and >15 % of the initial deposit. Spread of contamination on the plate depended on the cleaning movement and was between 2.1 and 53.9 % of the total quantity on the plate. The two detergents were more efficient (2,793-4,780 ng/plate) than hydro-alcoholic solutions (>20,000 ng/plate). The efficacy of the disinfectant was intermediate (5,891-6,122 ng/plate for solutions and 15,360 ng/plate for pre-soaked gauze). The cleaning protocol was also important with better efficiency of 8 mL of cleaning solution for 1,500 cm(2) (versus 4 mL), sprayed directly on the plate (versus wiping) with no contact time (versus 5 min). CONCLUSION: The efficacy of chemical decontamination of cytotoxic work surfaces depends not only on the cleaning solution used, but also on the cleaning protocol. It is necessary to adapt the protocol to the surface to clean and it must be standardized and validated. This work is an example of an experimental procedure to evaluate the efficacy of cleaning solutions and protocols used at a workstation after exposure to antineoplastic drugs.