Boosting Biotech Efficiency: Key Metrics and Strategies for Success

White Paper CDMO June 2025

In the evolving landscape of industrial biotechnology, operational efficiency remains a key driver of competitiveness. Which metrics define operational efficiency and are important to monitor? What tools can be employed to support continuous process improvement? Let’s explore some of the strategies we’ve implemented over the years, all aimed at reducing the cost per unit a financial metric that directly reflects economic efficiency and performance.

Boosting Biotech Efficiency: Key Metrics and Strategies for Success

This paper presents a framework for continuous process improvement, leveraging key metrics such as cycle time (Ct), space-time yield (STY), and throughput to ultimately reduce manufacturing costs. We outline actionable pathways for process enhancements implemented at industrial scale, using approaches such as downscaling, process debottlenecking, and fine-tuning of downstream processing. Our biotechnology contract development and manufacturing organization (CDMO) maintains a competitive edge in this rapidly evolving industry by enhancing performance metrics for the benefit of our customers – without compromising on quality.

Operational Excellence (OpEx) encompasses a holistic approach to improving quality, compliance, efficiency, and customer satisfaction. Quantifying OpEx relies on a set of key performance indicators (KPIs) that can cover several aspects of successful operations. E.g. compliance metrics evaluate adherence to regulatory standards through indicators such as the number of inspections or audit findings1. Quality metrics such as deviations or batch rejections are critical in ensuring product safety. Efficiency metrics focus on overall manufacturing process productivity and cost-effectiveness, with measures directly leading to cost reduction playing a central role. Operational efficiency in biotechnology refers to the ability to maximize output while minimizing input, whether in terms of time, cost, or resources, without compromising product quality or regulatory compliance. Unlike other industries, biotechnology operations are inherently complex due to the biological nature of the processes involved. Variability in microbial behavior, sensitivity to environmental conditions, and stringent regulatory requirements all contribute to the challenge of maintaining consistent and efficient production. To effectively measure and improve operational efficiency, we focus on a set of important KPIs. Cycle time (Ct) is defined as the time between the start of one batch and the start of the next and directly impacts labor, energy and depreciation costs. Reducing Ct can lead to faster production rate and increased capacity but may also introduce trade-offs such as higher energy consumption or increased labor intensity. Space time yield (STY), a critical metric of the upstream process part (USP), evaluates the amount of product generated per unit volume per unit time. Improvements in STY can significantly enhance overall productivity but must be balanced against operational constraints and seen holistically considering downstream processing (DSP) capacity and set up. Other important metrics include throughput, which gauges the volume of product produced over a given period, and DSP yield, which reflects the proportion of product that meets product specification without requiring rework. In addition to these metrics, efficient integration of laboratory capabilities and problem-solving skills, and operational competence is becoming increasingly vital. Together, these capabilities and metrics form the foundation for robust operations and drive value across the product lifecycle.

Through illustrative examples, we demonstrate how continuous process improvements can be effectively tailored to diverse biotechnology processes utilizing various microorganisms across different scales and campaign durations. By leveraging our R&D capabilities, diverse bioprocess optimization strategies, and strong operational expertise, we helped customers unlock hidden value across their product pipelines. During the following model commercial campaigns, we applied several optimization strategies that can be categorized into two key areas:

(i) bioprocess downscaling and bench-scale experiments to enhance space-time yield (STY) and/or product purity, and (ii) debottlenecking and fine-tuning of downstream processing at scale, ultimately leading to reduced product unit costs.

Figure 1 highlights improvements achieved during the manufacturing campaign of a large molecule with application as an active nutraceutical ingredient. Experiencing reduced process performance when scaling up the process from lab to commercial scale, we conducted small-scale experiments to optimize culture medium composition and feeding strategy. Semi-throughput screening (STS) for the impact of various medium components and fractional factorial design of experiments (DoE), followed by statistical analysis, enabled us to define and fine-tune the parameters with significant effect on STY. These upstream optimizations, combined with more efficient DSP unit operations, significantly improved overall process productivity as measured by the overall yield of the pure product. Key insight – medium composition, and nutrient availability can vary due to sterilization conditions and/or nutrient gradients, influencing cellular responses. Unlike traditional trial-and-error methods, which often result in inconsistent and temporary gains, DoE-driven lab-scale experiments offer fast, reliable, and economically low-risk solutions that can be seamlessly integrated into ongoing production campaigns.

Another Design of Experiments (DoE) approach was employed to optimize the production process of an enzyme used as a feed additive. This method revealed a significant relationship between the substrate-specific uptake rate (qS) and enzyme activity. Implementing an optimized induction-phase feeding profile, along with adjustments to aeration and pressure at scale to meet increased oxygen demand, led to enhanced STY and reduced Ct during a large-scale manufacturing campaign (Figure 1). Key insight – it is important to choose relevant physiological parameters for optimization to correctly interpret experimental results as well as to leverage technical parameters of large bioreactors.

Figure 1: Bioprocess improvements through downscaling and laboratory experimentation. The charts illustrate improvements in key performance metrics following the implementation of optimization strategies. Left, large-scale manufacturing campaign of a food ingredient. Right, large-scale manufacturing campaign of a feed additive.

Figure 1: Bioprocess improvements through downscaling and laboratory experimentation.

The charts illustrate improvements in key performance metrics following the implementation of optimization strategies. Left, large-scale manufacturing campaign of a food ingredient. Right, large-scale manufacturing campaign of a feed additive.

 

To debottleneck biotechnology processes represents a challenge given by the variability and complexity in modern biomanufacturing. Through existing mathematical framework and software solutions we performed a sensitivity analysis of a manufacturing process for production of an alternative food protein in order to identify the most important rate-limiting steps in the process. By focusing on fine-tuning of the identified DSP unit operations we significantly reduced Ct during the mid-size manufacturing campaign (Figure 2).  Key insight – debottlenecking is an ongoing process. Computational tools may be helpful to improve steps with the largest impact on throughput without installation of extra capacity, thus avoiding further investments.

DSP is equally important to fermentation processes. While USP generates a value, the DSP part preserves the value and delivers the product in required purity and non-compromised functionality in its final form. DSP is dependent on the quality and consistency of the fermentation broth. Mixing, flow dynamics, and membrane behavior often change at production scale. Due to our vast operational experience, we fine-tuned DSP unit operations in the large manufacturing campaign of a small molecule used in medical food applications, resulting in increased intermediate product recovery and purity and thus increased overall DSP yield (Figure 2B). Key insight – there is always room for improvement and downstream operations may take time to improve. Close coordination between USP and DSP teams enables better process harmonization. 

Figure 2. Track record of on-site external audit between 2021-2024 

Figure 2: Track record of on-site external audit between 2021-2024

Figure 2: Improvements through process debottlenecking and fine-tuning of downstream processing at scale. The charts illustrate improvements in key performance metrics following the implementation of optimization strategies. Left, large-scale campaign of an alternative protein. Right, large-scale campaign of a small molecule with application as a food ingredient.

Summary

Operational efficiency in biotechnology is a dynamic, multi-dimensional challenge. This paper presents a taste of strategies to improve the manufacturing process efficiency in biotechnology through targeted process optimizations and improvements in cost-related KPIs. Optimization efforts should be aligned with the process in question, its technology readiness level (TRL) and economic context. The most impactful gains often stem from a combination of host strain engineering, bioprocess design, and operational enhancements. However, technical improvements alone are not sufficient. It is essential to evaluate the full economic impact of any change, consider smart use of predictive analytical tools and operational experience, and foster strong collaboration across R&D and operations. Ultimately, long-term success hinges on balancing technical gains with business realities.

Our offer

  •       Fully integrated CDMO services in the field of industrial biotechnology
  •       Engagement at any stage of product/process development 
  •       99% batch success rate
  •       Excellent on-time in full delivery performance with over 60 processes transferred to commercial scale in the past decade
  •       Strong focus on continuous process improvement  

Authors information

Pavel Havelka Evaluation Manager

Pavel Havelka

Evaluation Manager

Vratislav Stovicek, Business Development Analyst CDMO

Vratislav Stovicek

Business Development Analyst CDMO

Acknowledgments

This work was funded by Arxada AG, Peter Merian-Strasse 80‎‏‏‎, 4052 Basel, Switzerland.

References

1Sarkady, J., Stovicek, V.: Vital role of quality in biotechnology CDMO. Arxada white paper, May 2025. Vital role of quality in biotechnology CDMO: Ensuring excellence at every step

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About Arxada

Arxada is an industry leader in science-based specialty chemicals that creates innovative chemistry and solutions. Comprised of two business units, Arxada’s Microbial Control Solutions (MCS) business provides more sustainable, science-based solutions that utilize differentiated capabilities in microbiology, actives delivery and formulation chemistry. Its manufacturing and unmatched regulatory expertise meets customer needs in variety of endmarkets, specifically, Professional Hygiene, Home & Personal Care, Paints & Coating, Wood Protection and Material Protection. Arxada’s Nutrition, Care & Environmental (NCE) business serves the needs of our partners in a diverse range of industries including food and feed supplements, aerospace, electronics, renewables, agriculture and industrial, as well as pharma intermediates. Leveraging our strong vertical integration into chemical building blocks, such as ethylene, acetylene, ketene/diketene and HCN, along with our fermentation capabilities and our deep technical expertise, NCE transforms customer needs into high performing solutions. This is achieved through direct product supply or contract development and manufacturing (CDMO). With major sites strategically located in the heart of Europe, Arxada secures its customers’ supply chains, while actively supporting their sustainability efforts.

Headquartered in Basel, Switzerland, the company’s global footprint spans 24 production sites and 14 R&D centers. Its 3,400 associates contribute daily to its overall success.

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