Tag: AI

The Importance of Biopharma Analytical Testing

In the world of biopharmaceuticals, precision and safety are non-negotiable. As companies work to develop advanced therapies and biologics, the role of analytical testing becomes ever more critical. Analytical testing serves as the backbone of biopharma development, ensuring that every product released to the market meets stringent regulatory standards while maintaining the highest safety and efficacy levels. Chemetrix supports this vital process by equipping laboratories with state-of-the-art technologies to optimise testing workflows and ensure regulatory compliance.

 

Why Analytical Testing Matters in Biopharma

Biopharmaceutical products, including monoclonal antibodies, cell and gene therapies, and vaccines, are inherently complex. Unlike traditional small-molecule drugs, these products are often derived from living cells, making them highly sensitive to variations in manufacturing and storage conditions.

Analytical testing ensures the quality, purity, potency, and stability of biopharmaceuticals throughout their lifecycle, from early development to final product release.

Without rigorous testing, even minor inconsistencies in a product can lead to reduced efficacy, compromised safety, or regulatory non-compliance. By employing advanced analytical methods, biopharma companies can identify impurities, confirm molecular structures, and monitor critical quality attributes (CQAs) that are essential for maintaining product integrity.

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Key Phases of Analytical Testing

Early development

During the early stages of biopharma development, testing focuses on characterising the biological product and defining CQAs. Techniques such as mass spectrometry, high-performance liquid chromatography (HPLC), and spectroscopy play a central role in these analyses. These tools help determine factors like molecular weight, structural integrity, and glycosylation patterns.

Process development

As manufacturing processes are developed, analytical testing ensures consistency and scalability. Process-related impurities, such as host cell proteins or residual solvents, must be identified and quantified. Additionally, methods like capillary electrophoresis and liquid chromatography-mass spectrometry (LC-MS) are employed to optimise purification steps and ensure process robustness.

Final product release

Before a product reaches the market, it undergoes comprehensive testing to confirm that it meets regulatory specifications. This includes assays for potency, sterility, endotoxin levels, and stability. Modern analytical platforms, such as multi-mode plate readers and automated systems, provide the throughput and accuracy needed for these critical assessments.

 

Trends in Analytical Testing for Biopharma

Emergence of advanced techniques

The biopharma industry is increasingly adopting technologies like LC-MS and next-generation sequencing (NGS) to enhance analytical capabilities. These methods allow for greater sensitivity and specificity, enabling researchers to detect low-level impurities and subtle molecular changes that could impact product performance.

Adoption of automation and AI

Automation is transforming analytical testing, reducing human error and increasing throughput. AI-driven software is also being integrated into testing workflows, enabling predictive analytics and more efficient data interpretation.

Focus on emerging therapies

The rise of cell and gene therapies has introduced new challenges for analytical testing. These therapies require novel analytical approaches to address their unique complexities, such as the characterisation of viral vectors and the assessment of genome editing outcomes.

Regulatory compliance and data integrity

With stringent guidelines from organisations like the FDA and EMA, ensuring data integrity has become a top priority. Advanced software systems with audit trails and robust data management capabilities are increasingly essential in biopharma testing.

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Driving excellence in Analytical Testing

Chemetrix is at the forefront of supporting biopharma companies with advanced analytical solutions. By offering cutting-edge instruments and technologies, we help laboratories address the challenges of testing biologics and other complex products.

We provide access to industry-leading platforms, including HPLC systems, LC-MS, and next-generation spectroscopy tools. These technologies are designed to deliver high sensitivity and precision, ensuring that every aspect of a biopharmaceutical product is rigorously tested.

The new generation Agilent 1260 Infinity III is a robust instrument that delivers the performance, reliability, and robustness you need for the highest confidence in daily HPLC results. With the freedom to mix and match new modules with existing HPLC instrumentation, it’s possible to maximise uptime and minimise disruption while also getting on the fast track to efficiency, optimizing speed and resolution for analysis.

Agilent 1260 Infinity II

Moreover, Chemetrix offers comprehensive support services, from installation and training to ongoing maintenance and technical assistance. This ensures that labs can maximise the performance of their analytical equipment and stay ahead of industry demands.

📚 Download the Mass Spectrometry of Macromolecules Using Standard Flow LC/MS application note to discover a robust and sensitive LC/MS method using standard LC flow for the analysis of native protein analysis >

 

The importance of analytical testing in biopharma cannot be overstated. As the industry continues to evolve, the need for advanced testing methods will only grow. By leveraging state-of-the-art technologies and partnering with trusted providers like Chemetrix, biopharma companies can ensure the safety, efficacy, and quality of their products while meeting regulatory expectations. With our commitment to innovation and excellence, Chemetrix stands as a trusted ally for laboratories navigating the complexities of biopharma analytical testing.

 

Harnessing AI for Next-Level Quality Assurance

While it can seem like Artificial Intelligence (AI) is a fancy tool only applicable in certain industries, AI is closer to you than you might think. From social media to your streaming service, AI processes are assisting with data processing and management in all sorts of innovative ways.

As the modern lab continues to evolve, AI adoption is becoming more commonplace. The increasing demand for accuracy but also shorter turnaround times has laboratories seeking technological and often digital solutions to help them achieve their business and operational goals. Lab analysts needn’t fear, AI isn’t coming for their jobs, but what it can do is support the work of lab staff to boost efficiency and ensure that quality control is optimised.

Quality assurance in labs

The quality assurance processes in labs are all about ensuring that the laboratory’s procedures, data analysis and results are of the highest quality. Without good quality assurance, there is a far higher probability of errors which can affect the results delivered. This can have a direct effect on product research and development, the development of environmental management solutions, and the manufacturing of products.

In testing labs, the integrity of samples is paramount in the quality assurance process. A good quality assurances process will make sure the samples aren’t compromised, which can lead to costly setbacks. Of course, good quality assurance means that the results from the lab can be trusted and they are reproducible. As laboratories seek to build strong relationships between themselves and stakeholders, good quality assurance provides quantitative and qualitative evidence of why the lab can be trusted.

Finally, safety also forms part of lab quality assurance. The process should make sure all the equipment is functioning properly and that proper procedures are documented and followed for handling samples, hazardous materials, and chemicals. By doing this, labs can prevent minor accidents that could lead to bigger safety risks.

Levelling up with AI for QA

AI opens a world of possibilities for the modern laboratory. Because of the big volumes of data and frequent tests and analyses, labs can benefit quite a lot from AI and machine learning. Traditional lab operations often involve repetitive and time-consuming tasks such as data backups, data review, and preliminary analysis. By automating these tasks, AI allows scientists to focus on higher-value activities such as experimental design, interpretation of results, and innovation.

In terms of quality assurance, there are a few key benefits from utilising AI:

Greater speed without greater risk of errors – The speed at which data can be processed and reviewed using AI significantly reduces the overall time required to complete experiments and projects. This acceleration in the workflow is crucial for meeting tight deadlines and maintaining competitive edges in research and development. Furthermore, AI’s ability to quickly analyse vast amounts of data helps in identifying trends and anomalies that might be missed by human reviewers. This enhances the accuracy and consistency of repetitive tasks, ensuring that data is reliable and free from human error.

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Cost management – Automation of tasks is one of the big advantages of AI and this can assist with cost management by potentially reducing overtime or weekend work hours, which aids operational costs. The resources saved from routine tasks can be allocated to more strategic investments and research, and this includes the brain power of key laboratory staff. Laboratories can also expand their capabilities without a proportional increase in manual workload and this assists labs in scaling their operations up without greater cost pressure.

Optimise resources – AI systems can do real-time monitoring of experiments and equipment to provide immediate feedback should a problem arise. It also means staff don’t have to be in the lab watching over the analytical instruments all the time, particularly if it requires hours before there are results and they could monitor the process remotely. This improves safety and resource management. AI can also assist with efficient resource management to reduce waste and lower the overall environmental impact while simultaneously checking instruments for preventative maintenance.

Labs looking to the future finding success now

Chemetrix is proud to be a local supplier of Agilent innovation. Agilent is on the forefront of leveraging software to fuel lab productivity – testing and proving the value of AI in day-to-day operations. This world-leading brand is seeing results from labs that are testing the integration of AI into their operations.

Agilent 5977C GC-MSD

In pilot testing, data review, a task that used to take nearly an hour to complete, was reduced to a few minutes, using AI capabilities. This type of efficiency gain in any lab would boost productivity and allow scientists to focus on more complex and high-value tasks. This type of result underscores the potential of AI to revolutionise lab operations, making them more efficient, cost-effective, and high-quality.

“Quality control labs rely on analytics to ensure product safety. We’re using new, exciting software approaches to enable faster, more efficient, and more accurate results.” – Tom Lillig, VP, GM, Agilent Software Informatics Division

We want scientists and researchers to dedicate the majority of their valuable time to critical thinking and complex problem-solving. So, embrace the power of technology and boost the efficiency of labs by offloading repetitive and mundane tasks to AI. Whether its through software or through instrument monitoring, there are different ways labs and their quality assurance processes can be improved through artificial intelligence and machine learning to enhance research, product development, and analysis now and in the future.