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Design of Experiment Application in Human Plasma in The Development of a Sensitive Bioanalytical Assay

PRESENTED BY:
Ajinkya Virgamwar
170620021
DEPARTMENT OF PHARMACEUTICAL CHEMISTRY
GUIDED BY:
DR. B.S JAYASHREE
PROFESSOR
DEPARTMENT OF PHARMACEUTICAL CHEMISTRY

Introduction
Methods of bioanalytical are daily used in pharmaceutical industries for studies of pharmacokinetics and pharmacodynamics. With emerging new technologies accuracy, precision and analysis time has been greatly reduced. Although with the advanced technology like Liquid chromatography-mass spectroscopy (LC-MS) sample preparation remains the vital step and hence this can be tedious.

A design of experiment (DOE) is statistical practice and goal is to test the effects of factors that are being considered while designing of an experiment. It can emulate the experiment region by obtaining predictive model. These developments are enclosed of comparing the consequences of different variables and factors on the deign which gradually being compared to old traditional methods light changing one factor at a time. A DOE is adopted prior to method development and effectively used for revamp extraction methods and LC separation.

For this assay, use of two analytes as compound A, parent compound and compound B, metabolite is done. Three major problems were encountered while design the experiment as initial problem was to transform system into non-clinical to first in human (FIH) approach as this required the sensitivity 20 folds increased. Other problem was to response for metabolite compound B is much lower as that of compound A. Another problem was to obtain broader linear dynamics. Sample extraction process was the essential and fundamental solution to the problems.

Experimental Conditions
Standard curve range: 50.0–5000 pg/mL Compound A 100–10,000 pg/mL Compound B
IS working solution: 30 ng/mL in (2 M) sodium carbonate (pH 11)
Extraction buffer: (2 M) sodium carbonate buffer (pH 11)
LLE method: 50 µL IS + 350 µL plasma + 500 µL MTBE : hexane (90:10, v/v) shake on linear shaker for 10 min, centrifuge for 15 min, remove organic layer, and evaporate to dryness reconstitute in 50 µL of (50:50, v/v) mobile phase A:mobile phase B
Mobile phase: Mobile phase A: (10 mM) ammonium formate, 0.06% formic acid (10:90, v/v) methanol: water. Mobile phase B: (10 mM) ammonium formate, 0.06% formic acid (90:10, v/v) methanol: water
HPLC conditions: Column: Waters Atlantis dC18, 2.1×50 mm, particle size 5 m (column heater temperature = 40 ?C) Flow rate: 0.4 mL/min; injection volume = 20 µL Run time = 5.0 min (gradient elution)
LC-MS Equipment: All sample analyses were performed on a Sciex API 4000 triple quadrupole mass spectrometer (AB Sciex, Foster City, CA), which was controlled by Analyst® 1.4.2 software.

Computation: SAS Version 8.02 14 software was used to evaluate the DOE data.

Approach of DOE in Method Evolution
Extraction buffer maintained at 2 pH levels i.e. ammonium carbonate pH 9 and sodium carbonate pH11.

The volume of human plasma was 200 µL instead of 350 µL for validation purpose. Hence human plasma 200 µL was added to organic extraction solvent was at 225 µL or 367 µL.

Three level of extraction shaking time was being established as 5 min, 10 min or 20 min.

To reduce or to overcome the chromatographic issues design run were practiced on three different plates on three different days, hence it also simultaneously compared between and within day variability.
Sample Analysis
Sample Extraction:
Stock solutions of each analyte was prepared of 1.00 concentration.

Combined stock was prepared containing both analyte and spiked into human plasma working solution from which sample was prepared at low concentration 0.15 ng/mL
200 µL sample solution aliquots with extraction buffer (50 µL) added to 1.1 mL micro tubes and was subjected to vortex (20 sec).

Organic solvent was added and solution is capped and agitated, later centrifuged for 15 min. Supernatant was transferred to 96 well collection plate, evaporated to dryness under nitrogen, and reconstituted in 60 µL of (50:50, v/v) (10 mM) ammonium formate in (10:90, v/v) methanol : water with 0.06% formic acid : (10 mM), ammonium formate in (90:10, v/v) methanol : water with 0.06% formic acid containing 30.0 ng/mL of each stable label IS for Compound A and Compound B. The reconstituted samples were vortexed for 2 min, sonicated for 10 min, vortexed again for 2 min, and then centrifuged for 2 min.

LC-MS Analysis: A 20 µL sample injected into system and separated by c18 column. Both mobile phase was being used with linear gradient increase in volume from 20 % to 70 % followed by stabilization period and subsequent decrease. Compound A, Compound B, and the stable label IS for each analyte were detected using positive ionization selected reaction monitoring (SRM) mode.

Data Processing: Sciex Analyst software version 1.4.2 was used for the calculation of the peak areas of Compound A and Compound B.

Outcomes
Low concentration DOE experiment was performed for the sensitivity optimization and to obtain information about the analyte recovery. extract. Two output variables were selected: the area count ratio of the analyte to its corresponding IS and the absolute peak response (area) of the analyte. Both the variables altered by the condition of extraction.

Consequence of Extraction Buffer pH
The peak areas and analyte recovery for compound A is marginally influenced b pH as there was better recovery at higher pH . Where as compound B showed drastic increase in the peak and analyte recovery as from PH 9 to pH11. The response increased by 2 folds. There was two way interaction observed between pH and organic extraction solvent. With large volume of solvent and higher pH lead to 6 times increase in recovery and analyte response.

Human plasma to organic solvent volume ratio
For both the compounds there was observed increase in the recovery with high organic extraction solvent volume. With the relative 1.5 fold increase for compound and for compound B 2 fold increase.

Extraction Period Effect
The period for the extraction was majorly influenced for compound B as seen decrease in the recovery as time was increased. For compound A also shown recovery decrease with linear shaker time. Longer shaking time constituted to lower recoveries this is due to matrix effect. There was 10% decrease for compound A and 30% for compound B.

Run to run variability
Internal standard was added to compensate instrument variations for both compounds. For compound B showed more run to run variability than compound A. Total relative standard deviation observed was 11.2% for comp. A and 18.5% for comp. B.

Discussion
Form three factors volume of organic extraction solvent affected the recovery of compound A. On other hand for compound B several factor influenced for its recovery.

DOE established relation between previously traditional validated method and human LC-MS with only exception of the shake time.

There was observed two-way interaction between pH and volume of organic extraction solvent contributed to the recovery of compound B but did not affect compound A.

Conclusion
DOE is done prior to the method validation in place of the traditional method development process. It helps to define parameter as per the experiment region. The optimization is greatly achieved with the implementation of the DOE.

Here, for the assay, there has been compound B that is drastically changed or altered with changing variables or factors like pH, volume of extraction solvent and shake time. It was believed that higher shake time grater is recovery but, in this case, it leads to the matrix effect. Compound A, it showed major change in the recovery due to volume of organic extraction solvent. It provides better understanding and how factors affect the recovery and peak of the analyte.

One of the greatest benefit of DOE is scientist can study two-way and multi-way interaction which can not be studied using traditional system.

Reference
Application of a design of experiment approach in the development of a sensitive bioanalytical assay in human plasma, Journal of Pharmaceutical and Biomedical Analysis, Elsevier.

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