Sara Baldelli (Presenter)
Clinical Pharmacology, L.Sacco University Hospital
Authorship: Sara Baldelli (1), Giorgio Marrubini (2), Dario Cattaneo (1), Emilio Clementi (3,4) and Matteo Cerea (5)
(1) Unit of Clinical Pharmacology, L. Sacco University Hospital, Milano, Italy (2) Department of Drug Sciences, University of Pavia, Pavia, Italy (3) Clinical Pharmacology Unit, CNR Institute of Neuroscience, Dept Biomedical and Clinical Sciences, L. Sacco University Hospital, Università di Milano, Milano, Italy (4)Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy (5)Department of Pharmaceutical Sciences, Università degli Studi di Milano, Milan, Italy
| Short Abstract The application of Quality by Design (QbD) principles in clinical laboratories can help to develop an analytical method through a systematic approach providing a significant advance over the traditional heuristic and empirical methodology. In the present work, we applied for the first time the QbD concept in the development of a method for drug quantification in human plasma using elvitegravir as the test molecule. The obtained method was validated according to EMA guidelines on bioanalytical method validation, and clinically applied with success. |
Long Abstract
Introduction
The application of Quality by Design (QbD) principles in clinical laboratories can help to develop an analytical method through a systematic approach providing a significant advance over the traditional heuristic and empirical methodology.
By understanding and studying critical variables that affect the uncertainty of the method, using risk analysis and by applying the design of experiments (DoE) methodology, the quality of the method can be built through rational planning, so that forthcoming failures can be avoided.
In the present work, we assessed for the first time the validity of this procedure applying the QbD concept in the development of a method for the quantification of elvitegravir in human plasma as test molecule.
Methods
The goal of the study was to develop a fast and inexpensive quantification method, with precision and accuracy as requested by the EMA guidelines on bioanalytical method validation. To select the appropriate method for extraction and quantitative determination of the molecule, the following elements have been considered: 1. Potential to reach the Analytical Target Profile; 2. Instrumentation availability in the laboratory; 3. Experience of the operators for developing, use, and maintaining the method; 4. Time to complete the analysis; 5. Specificity; 6. Operator safety; 7. Costs.
Every parameter was weighted according to priority decided by the laboratory planning and hospital management (from 1 very important to 0 not important).
Every considered variable was scored from 0 (lowest impact) to 10 (highest impact), while for the costs 0 corresponded to the most expensive and 10 to the most convenient analytical set-up. Every technique was finally ranked according to the result of the sum of all scores multiplied for the assigned weight.
In order to reduce the bias due to subjective judgements, variable scores were expressed as the mean of the scores collected from an interview to the laboratory manager, two HPLC experts of the laboratory and two experts in the field external to the laboratory.
The method was divided into operative units and for each unit critical variables affecting the results were identified. All these variables were reported on an Ishikawa diagram. A risk analysis, Risk Assessment Failure Mode Effect Analysis (FMEA) was performed to select critical process parameters that should be introduced in the DoE.
Ishikawa diagram and FMEA analysis were completed by involving the laboratory manager, two HPLC experts and two technicians of the laboratory and two experts in the field external to the laboratory. Different DoEs were employed depending on the phase of advancement of the study. For the selection of the variables involved in the analytical process, Plackett-Burman, 2-level full factorial, and a 26-2IV fractional factorial designs were used. For the optimization of the analytical conditions, face centered composite designs were applied.
The developed method was validated according to the recommendations of EMA guidelines
Results
Protein precipitation (PPT) resulted as the preferred method to be investigated with DoE for elvitegravir isolation from plasma samples, and HPLC-MS/MS as the technique of choice for quantifying the molecule. This result was based on the rank determined as sum of all the mean scores obtained for every single variable.
For every operative unit (sample preparation, chromatographic conditions and detector settings) a model based on factors affecting the responses was developed and optimized.
The first step studied was that of the isolation of the target analyte by solvent precipitation. A Plackett-Burman screening design consisting of eight experiments was selected to study the relevance of the effects of five factors: solvent type (X1, acetonitrile or methanol), the plasma volume in µL to be used for the precipitation (X2, 50 or 200 µL), the solvent to plasma volume ratio (X3, 3 to 1 or 7 to 1), the mixing time (X4, 20 or 60 seconds), and the temperature of centrifugation (X5, 4 or 25°C). Other processing factors were fixed to standard values as suggested by FMEA analysis. The experimental responses were the target compound peak area (R1) and height (R2), the signal-to-noise ratio (S/N, R3), and the peak symmetry (R4) as computed and printed by the instrument software. The goal of the experimentation was to assess which factors were the more important in order to maximize the responses R1, R2, and R3 while bringing R4 as close as possible to the value of 1.
Acetonitrile was selected as solvent for the protein precipitation, in a ratio 3 to 1
The second step involved the screening of the eluent composition. a mobile phase containing acetonitrile was selected and the effect of formic acid (X1, % v/v) and of ammonium acetate (X2, mM) was analysed. An isocratic elution was applied with a composition of 60% eluent A and 40% eluent B.
the experimental responses that were considered were elvitegravir and IS peaks areas (R1 and R2), and the MF (R3). The goals of the study were to find the mobile phase composition that produced the highest peaks areas (maximize R1 and R2) while bringing the MF closer to 1.
water and acetonitrile with formic acid 0.1% appeared to be best eluent for HPLC in isocratic conditions.
Also detector parameters were optimized to detect elvitegravir and IS molecular ions at the transitions m/z 448>344 and m/z 454>344.
The goal of this step was to find the optimal settings of the MS apparatus to achieve the highest analytical sensitivity as expressed by the molecular ion intensity (MII) and its value respect to the total ion current (TIC). Six factors were considered: the ion source temperature (X1), capillary voltage (X2), cone voltage (X3), desolvation gas flow rate (X4), cone gas flow rate (X5), and desolvation temperature (X6).
Data were collected by infusing a standard solution of elvitegravir in HPLC mobile phase at the concentration of 1000 ng/mL directly in the mass spectrometer at a flow rate of 10 µl/min and monitoring the m/z = 448.
The maximum predicted response was obtained with an ion source temperature of 119°C, a cone voltage of 45V a desolvation gas flow rate of 650 L/h and a desolvation temperature of 250°C.
The final step was addressed at the optimization of the response of the MS/MS system. Two factors were considered, the collision energy and the collision gas flow rate. The transition selected was that from the parent ion at 448 m/z to the product ion at 344 m/z. We chose as response the ratio between the product ion intensity (PII) and the TIC in order to optimize the sensitivity of detection in terms of S/N.
A central composite design was selected, since 12 experiments were considered an affordable effort for this phase of the study. Optimal settings for the MRM reaction were obtained with collision energy of 32 eV, and collision gas flow rate of 0.29 ml min-1.
The obtained method was validated and clinically applied with success. The performance of the method is continuously monitored using control charts and by participating to international quality control programs.
Conclusions & Discussion
To the best of our knowledge, this is the first investigation thoroughly facing with the application of the QbD to the analysis of a drug in a biological matrix applied in a clinical laboratory. QbD approach may represent a novelty for the clinical laboratory and a clear guide to develop a controlled bioanalytical method which resulted very robust and reliable in its clinical application.
References & Acknowledgements:
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