AQbD APPROACH FOR ANALYTICAL METHOD

 

AQbD APPROACH FOR ANALYTICAL METHOD

  

What is AQbD Approach?

The analytical procedure life cycle is controlled at every level by the methodical approach to method development known as AQbD. The analytical target profile (ATP) is defined, crucial method parameters or factors are identified, and critical method attributes (CMAs).

Method Design

The first stage in the method lifecycle is creating the optimal analytical technique. Many factors need to be taken into account when using an effective analysis approach. The method design of the AQbD approach includes space generation, ATP definition, experimental design screening, and CQA establishment.

Establish CQA

The initial phase of process validation is usually when CQAs are identified. This phase is known as process design. Establishing protocols for measurement, data collecting, and analysis, as well as appropriate limits and ranges, is best done now.

Risk Assessment

Stationary phase selection, composition of the mobile phase, gradient and flow rate, temperature of the column, detection parameters, sample preparation, resolution and peak shape, sensitivity and selectivity, repeatability, and method validation are some of the important characteristics.

Quality Target Product Profile

Critical quality attributes of the drug product are identified in the Quality Target Product Profile. QTPP is a potential summary of a drug product's quality attributes that, with safety and efficacy taken into consideration, should ideally be met to guarantee the intended quality.

Development strategy with design-experiment 

The key procedure that drives critical analytical attributes (CAAs) and critical process parameters (CPP) to produce a quality-targeted method profile (QTMP) is optimization. The QTMP considered for the Analytical method was the area, peak resolution, and tailing factor. To achieve QTMP from the developed Analytical method, independent variables & crucial independent factors were dependent. The Analytical method was developed by varying independent variables to get optimum dependent variables according to ICH guidelines.

Application:

Robust and effective analytical methods can be developed and optimized by AQbD. Analytical QbD implementation lowers the chance of method failure while also offering a better way to handle OOS results.

Dr. BHOOMI D. PATEL

Associate Professor & HOD

Pharmaceutical Chemistry & QA

School of Pharmacy, Rai University