Analytical Process Development in the Pharmaceutical Industry

The shift toward evidence-based drugs and increasing cost burden is putting pressure on biopharma firms to market drugs through low-cost and highly efficient production methods. 
    
Cost-effective and efficient paths to candidate drugs are established during the drug development lifecycle. It examines the influence of various parameters on product quality and process performance. Access to precise analytical information at the right time is essential to complete process development projects efficiently and effectively. 
Consequently, different methods are evaluated frequently and optimized through different phases of the drug development lifecycle for product characterization.   
With robust and well-designed analytical process Development and devetesting strategies, it is easy to confidently ensure product quality. This is a significant responsibility and represents a substantial amount of work that must be documented and communicated clearly to ensure effective and efficient review by regulatory authorities before product approval.
Investigative data on product quality and impurity are required to gain comprehensive process knowledge to determine additional parameters required to inspect and enhance the conditions for producing drugs on a commercial scale. Predictive models can be developed to enable technology transfer and scale-up. 
So, both the appropriateness and timeliness of the data can affect the productivity of the drug development process.
    

Process Analytical Background
Regulatory agencies around the world are aware of the incredible amount of work required to ensure product quality and the effort needed to encourage pharma manufacturers to accomplish success. 
In 2004, the drug administration in the United States published an aspirational guidance for the industry on Analytical Process Development Technology (PAT). Sadly, even after a decade, the use of PAT in an integrated manner to measure, design, and control performance attributes and critical process quality through appropriate measurements is yet to be realized. 
However, using PAT to comprehend and regulate pharmaceutical manufacturing processes to ensure final product quality continues to be a worthy goal. 
The “PAT umbrella” consists of a suite of tools, including chemical, analytical, microbiological, physical, and mathematical. Process Analytical Technology interfaces with the instrument and might include a feedback loop to change the conditions based on real-time analysis. This data might help both product quality and process control. 
On the other hand, by using the conventional approach, the process is sampled which is then transported to a lab. This results in an interruption between process sampling and the time when the results are made available.
     

Barriers to Adoption of PAT
The strong regulation process involved in the use of PAT in the pharma industry differentiates it from other industries. Pharmaceutical manufacturing uses cGMP controls to regulate the application of validated manufacturing processes and the operating systems with distinct operating arrays for each process.

Importance of Collaboration
To be effective, analytical method development should not take place in isolation. Widespread interactions between process development scientists, engineers, and analytical scientists are required to make sure that analytical methods address the precise needs of the process development group. Additionally, persistent, data exchange and enduring communication on the information requirements of the group are important for the effective development of fit-for-purpose procedures that can fast-track process development efforts.
Fast-tracking process development activities is essential to remain viable in the marketplace today and entail collaboration with analytical development efforts. Biopharmaceutical companies must establish an experienced analytical team that focuses on supporting process development and ensure rapid tech transfer and scale-up of biopharma partner processes.

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