Unlock efficiency: Leverage the right digital tool to build process knowledge and streamline drug development

By Unjulie Bhanot, Product Marketing Manager, Process Development & Manufacturing, IDBS

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Over the last half-century, the BioPharma industry has focused on collecting data and increasing knowledge about their therapeutic products – transitioning from analog to digital formats and expanding their library of laboratory informatics tools. Over time, these tools have developed to go beyond traditional paper-on-glass approaches and expand into areas such as inventory management, equipment calibration or statistical analyses – but with little emphasis on the documentation and management of processes and parameters – the factors responsible for achieving a high-quality product.

Join us for this three-part series as we uncover why the BioPharma industry needs to shift its focus to capturing, managing and leveraging parameter and process data to create process knowledge and ultimately optimize drug development and tech transfer.

The drug development boom

From the turn of the 20th century, there was a rise in the discovery of small-molecule therapeutics – marked by the discovery of Aspirin. And by the middle of the century, the world was witnessing a pharmaceutical revolution. From antibiotics like penicillin and streptomycin to non-steroidal anti-inflammatory drugs like ibuprofen and diclofenac, each year brought new molecules to market.

In 1975, a groundbreaking report detailed a method for generating large quantities of monoclonal antibodies with specific targets. This innovation paved the way for the vast array of therapeutic and diagnostic monoclonal antibodies produced to date.

This revolution in pharmaceuticals was accompanied by stricter FDA guidelines. Following the Thalidomide scandal, the Kefauver-Harris Drug Amendment of 1962 mandated that drug manufacturers prove the efficacy and safety of their products before marketing them. This required thorough documentation of a product’s quality, safety and effectiveness.

The birth of laboratory informatics tools soon followed to meet the growing need for managing experimental records and samples while adhering to increasing regulatory demands. The 1980s and 1990s saw the introduction of basic electronic lab notebooks (ELNs) and laboratory information management systems (LIMS). In 1997, the FDA published 21 CFR Part 11, setting standards for the management and use of electronic records and signatures in pharmaceuticals. These regulations were, and continue to be, fundamental in enabling drug manufacturers to leverage digital solutions to streamline research, development, manufacturing and validation activities, ensuring the safe introduction of new drugs to the market.

Since 2000, the FDA has approved over 190 biological therapeutics (including monoclonal antibodies, proteins and enzymes) and more than 600 small molecule treatments (see Nature Review Drug Discovery for more details), and we are continuing to see a rise in the development of cell, viral vector and oligonucleotide therapeutics, too. The functionality and features of ELNs, LIMS and other informatics tools, such as laboratory execution systems (LES), have also evolved to serve these growing biological and technological needs of the lab today – for example, to integrate directly with large automation systems and drug analysis instruments, or manage the product lifecycle of therapeutic products, but still, these systems are not focused on cultivating process knowledge.  Currently, there are nearly 100 active ELNs and over 20 LIMS available on the market, with these markets projected to grow at over 5.5% and 6.7% respectively, over the next five years.

Digital maturity for accelerated drug development

With rising global competition, and a growing demand for targeted, innovative therapies, shorter development and tech transfer timelines are essential. Patients rely on consistent, high-quality products to reach them promptly, which can only be achieved by drug manufacturers prioritizing digitalization and automation to mitigate risks and ensure safe development.

Digital maturity, which measures how effectively an organization leverages digital technologies, is crucial for maintaining product and process knowledge across a drug’s development lifecycle – alongside all information providing more context to the data, such as supporting inventory, contributing unit operations and analytical methods, equipment suitability, and material hand-offs between teams and organizations.

To enable and enhance digital maturity, drug manufacturers often end up deploying a complicated web of different tools and systems, but inevitably create inefficient and error-prone data silos. Using archaic and basic laboratory systems can impact data integrity, risk regulatory compliance, limit collaboration capabilities, and impede process insights.

Without being empowered to harness process knowledge, organizations could face delays in understanding the true impact their process parameters, instruments, consumables and process decisions have on the product. Despite overlapping functionality and expanding capabilities across existing informatics tools, the ability to manage, monitor and seamlessly qualify parameters and processes, within the same software platform where experimental execution and analysis are conducted, remains untapped.

We know a lot about our product, but how much do we really know about the process?

As an industry, we have become very good at collecting data and increasing our knowledge about the product, with existing tools enabling this. For example, ELNs allow scientists to record experimental data in an efficient, easy-to-document format, replacing the traditional paper laboratory notebook.  However, the data tends to be captured in an unstructured format, thus rendering the ELN more of a digital repository or compliant storage location, than being able to directly harness the value of that data.

LIMS systems offer a different perspective – with a primary focus on samples, meticulously managing the journey of samples through the product lifecycle. From login to disposal, LIMS diligently track each step in a compliant fashion, while also offering capabilities for instrument calibration and inventory maintenance.

Sometimes paired with these tools is an LES – as a specialized version of an ELN, LES are workflow-centric and ensure procedural consistency during execution.

However, for a team to accurately determine the impact of a process parameter or the success of their chosen process, they often need to manually collect data from various sources. This is because process or parameter details may still be recorded on paper protocols or standard operating procedures (SOPs), or simply reside in the mind of the principal scientist responsible for a specific unit operation. Tracing and statistically analyzing how a single input parameter affects a product’s yield or structural formation, or understanding how multiple parameters interact to fine-tune the overall process, can be a tedious and error-prone task. This often takes place well after the experiment or run is performed, leading to lost time and consumed materials.

The process of having to externally analyze this data, and then reintegrate it back into the point of execution to implement the required changes, introduces risks and delays. Altogether, this creates a significant roadblock to effectively leveraging data to optimize the process and renders the development of process knowledge challenging.

Quality and process knowledge go together

Throughout the product lifecycle, BioPharma organizations continuously seek opportunities to enhance product quality. Since the establishment of the quality by design (QbD) principles by the ICH in 2004, QbD has become the gold standard for process development in the BioPharma industry. Core elements of QbD include evaluating process performance, analyzing historical and design of experiments (DoE) data, and understanding how processes and materials impact the final product. This methodology ensures that quality is integrated into every stage of the product lifecycle, with a focus on identifying critical process steps and parameters to build comprehensive process knowledge.

During the process development phase, the primary goal is to pinpoint critical process parameters that must be monitored and controlled to guarantee the delivery of a high-quality product. The selection, control and updating of these processes must be thoroughly documented—a task that can be cumbersome and prone to errors without the aid of digital tools.

Therefore, it is essential for the BioPharma industry to adopt a process-focused digital solution. In today’s fast-paced world of scientific and biological advancements, the industry must effectively capture data about their processes, track their evolution through development, and understand how they translate to and impact manufacturing. Join us for the next blogs in this three-part series, as we dive deeper into the evolution of process parameters and quality attributes over process development, the impact on technology transfer, and the potential to use AI/ML to transcend process knowledge and develop process intelligence.

Read the next blog in the series.

 

About the author

By Unjulie Bhanot, Product Marketing Manager, Process Development & Manufacturing, IDBS

Unjulie Bhanot is the Product Marketing Manager for Process Development and Manufacturing at IDBS. With over 10 years of experience in the Biopharma informatics space, she has led the strategy and development of IDBS’ Bioprocess solutions and was instrumental in the launch of IDBS Polar to market.

 

 

References:

1. (1975). Retrieved from https://www.nature.com/articles/256495a0
2. S. Food and Drug Administration. (n.d.). Milestones in U.S. food and drug law. Retrieved from https://www.fda.gov/about-fda/fda-history/milestones-us-food-and-drug-law
3. (2022). Retrieved from https://www.nature.com/articles/s41596-021-00645-8
4. S. Food and Drug Administration. (2003). Part 11, electronic records; electronic signatures – scope and application. Retrieved from https://www.fda.gov/regulatory-information/search-fda-guidance-documents/part-11-electronic-records-electronic-signatures-scope-and-application
5. (2022). Retrieved from https://www.nature.com/articles/s41596-021-00645-8
6. Grand View Research. (2023). Electronic lab notebook (ELN) market analysis. Retrieved from https://www.grandviewresearch.com/industry-analysis/electronic-lab-notebook-eln-market
7. Grand View Research. (2023). Laboratory information management system market size. Retrieved from https://www.grandviewresearch.com/horizon/outlook/laboratory-information-management-system-market-size/global
8. European Medicines Agency. (2017). ICH guideline Q8 (R2) pharmaceutical development. Retrieved from https://www.ema.europa.eu/en/documents/scientific-guideline/international-conference-harmonisation-technical-requirements-registration-pharmaceuticals-human-use-considerations-ich-guideline-q8-r2-pharmaceutical-development-step-5_en.pdf