The Future of Viral Vector Manufacturing: Yield Optimization
Viral vectors are more than a vehicle for a payload. Their ability to target specific cells has made them among the most promising treatment modalities to emerge in recent years. But the specificity enabled by this tropism has complicated scale-up.
Ensuring optimal yield for engineered viral vectors is crucial to their eventual commercial viability. Still, it's easy to overlook early yield drivers, resulting in suboptimal yields, rework, and the potential scrapping of an otherwise promising therapeutic. Often, yield issues are not uncovered until toxicology testing has begun, by which time considerable time and cost have already been invested in a transgene that, while effective, is production inefficient.
The heavy lifting inherent to cell and gene therapy contributes to the high production costs of these therapeutics and, commensurately, to the high cost to patients. Zolgensma, a gene therapy for spinal muscular atrophy, is the most expensive drug on the planet, averaging more than $2 million for a single dose. Driving down the cost of viral vector development is critical to making these life-changing therapies more accessible, enabling more targeted treatments across a wider range of diseases and improving quality of life.
The Variables that Impact Yield Optimization for Viral Vectors
Scientists have greatly advanced the field of engineered serotypes by fine-tuning epitopes and proteins to improve tropism, transduction, and specificity. In contrast, “wild serotypes,” such as rh74 orAAV9, have had over a billion years to optimize packaging efficiency, yielding superior production yields.
Another core focus of this research has been transgene development, with a particular emphasis on expression. Early in a product’s life cycle, the central question is how to design a transgene that achieves optimal expression within an already limited payload capacity. This is complex because some of that capacity is reserved for inverted terminal repeats (ITRs), promoters, poly(A) signals, and other features required to meet regulatory requirements. Therefore, the molecular development needed to produce a functional coding sequence with high expression that can be packaged in a tailored capsid is already difficult; ensuring yield may fall by the wayside because of this complexity.
Optimizing a yield profile early and then scaling with yield performance in mind can help companies meet productivity demands across the full product life cycle. Downstream purification losses average 50 to 70 percent for non-optimized processes. Ultra-centrifugation is a notorious source of product loss and a common workhorse step in purification; transitioning entirely to column purification could minimize that loss. But purification losses typically compound; while a discrete purification step may have an average 20 percent product loss, previous and subsequent steps with the same average loss will account for most of the product lost to purification when evaluated holistically. Some level of static, adsorptive loss is unavoidable at each step, but improving up-front yield can mitigate losses and improve downstream purification.
Mitigating Costs Through Standardized Platform Technology
Developers must understand that a product's yield profile can vary significantly by serotype and DNA sequence. Therefore, researchers must thoroughly screen transgenes, backbones, and serotype configurations to establish critical production parameters before selecting the best candidate for production and clinical performance. To do so, AAV candidates can be sent to a platform development lab with standardized processes, equipment, materials, and expertise to evaluate performance using a standardized Design of Experiments (DoE) study in adherent or suspension cultures. By balancing customization and standardization through flexible approaches, companies can gain important insights into both upstream yield and downstream purification.
While prioritizing tropism and transgene expression is integral, focusing on other variables, such as cell density, packaging efficiency, incubation and hold time, stability, and impurity profiles, is critical to mitigating costs and improving efficiency. Enabling material interchangeability and working toward process standardization across as many serotypes as possible are key to the future of the cell and gene therapy space. Today, the proliferation of custom-built platforms for specific transgenes has created a flood of siloed, individualized processes, affecting cost, time to market, and manufacturing efficiency.
Optimizing viral vector yield also means right-sizing processes. Accurate lot sizing is critical to this optimization; the ability to operate at multiple scales, including sub-lot production sizes to minimize pooling, can reduce waste and lower production costs. This standardization can be elusive for some therapeutics. Still, for projects that can accommodate it, it can be an important tool for optimizing yield at a lower long-term cost. Many of the nuances in AAV production and scale-up can only be identified and addressed over multiple production runs. Manufacturer experience and standardization can be critical to avoiding unnecessary delays.
Future Trends in Standardizing Yields for Viral Vectors
The current AAV research landscape remains far from the standardization seen in other parts of the biopharmaceutical market because of the inherent variability of the biological process. The sheer volume of data needed to enable predictive analytics is still far off for many developers, most of whom work with highly proprietary, engineered serotypes in a highly competitive market. Achieving product equivalency will be critical to maturing the market in the coming years, and maturing the analytics behind it will be key to achieving that equivalency.
Variability among vectors is substantial, driven by the selected serotype and transgene, as well as factors such as genetic payload size and sequence, which can affect packaging, density, buoyancy, or affinity. Intersecting variables that inform AAV development, coupled with competition and evolving regulatory standards for these therapies, have made developing a standard approach difficult. This, along with interchangeability and a push for harmonization, represents the future of affordable, accessible AAV therapies.
Ultimately, partnering with a contract development and manufacturing organization (CDMO) that has expertise and platform technologies to balance a project’s customization and standardization can help companies avoid common AAV development pitfalls. Ensuring optimal yield for these therapeutics is complex but crucial, as many projects with immense therapeutic potential have been derailed by poor yield. In a market constrained by costs for both developers and end users, pursuing long-term advances in process standardization, data collection, and yield optimization will stabilize the space and enable more targeted therapies.
Viral vectors are more than a vehicle for a payload. Their ability to target specific cells has made them among the most promising treatment modalities to emerge in recent years. But the specificity enabled by this tropism has complicated scale-up.
Ensuring optimal yield for engineered viral vectors is crucial to their eventual commercial viability. Still, it's easy to overlook early yield drivers, resulting in suboptimal yields, rework, and the potential scrapping of an otherwise promising therapeutic. Often, yield issues are not uncovered until toxicology testing has begun, by which time considerable time and cost have already been invested in a transgene that, while effective, is production inefficient.
The heavy lifting inherent to cell and gene therapy contributes to the high production costs of these therapeutics and, commensurately, to the high cost to patients. Zolgensma, a gene therapy for spinal muscular atrophy, is the most expensive drug on the planet, averaging more than $2 million for a single dose. Driving down the cost of viral vector development is critical to making these life-changing therapies more accessible, enabling more targeted treatments across a wider range of diseases and improving quality of life.
The Variables that Impact Yield Optimization for Viral Vectors
Scientists have greatly advanced the field of engineered serotypes by fine-tuning epitopes and proteins to improve tropism, transduction, and specificity. In contrast, “wild serotypes,” such as rh74 orAAV9, have had over a billion years to optimize packaging efficiency, yielding superior production yields.
Another core focus of this research has been transgene development, with a particular emphasis on expression. Early in a product’s life cycle, the central question is how to design a transgene that achieves optimal expression within an already limited payload capacity. This is complex because some of that capacity is reserved for inverted terminal repeats (ITRs), promoters, poly(A) signals, and other features required to meet regulatory requirements. Therefore, the molecular development needed to produce a functional coding sequence with high expression that can be packaged in a tailored capsid is already difficult; ensuring yield may fall by the wayside because of this complexity.
Optimizing a yield profile early and then scaling with yield performance in mind can help companies meet productivity demands across the full product life cycle. Downstream purification losses average 50 to 70 percent for non-optimized processes. Ultra-centrifugation is a notorious source of product loss and a common workhorse step in purification; transitioning entirely to column purification could minimize that loss. But purification losses typically compound; while a discrete purification step may have an average 20 percent product loss, previous and subsequent steps with the same average loss will account for most of the product lost to purification when evaluated holistically. Some level of static, adsorptive loss is unavoidable at each step, but improving up-front yield can mitigate losses and improve downstream purification.
Mitigating Costs Through Standardized Platform Technology
Developers must understand that a product's yield profile can vary significantly by serotype and DNA sequence. Therefore, researchers must thoroughly screen transgenes, backbones, and serotype configurations to establish critical production parameters before selecting the best candidate for production and clinical performance. To do so, AAV candidates can be sent to a platform development lab with standardized processes, equipment, materials, and expertise to evaluate performance using a standardized Design of Experiments (DoE) study in adherent or suspension cultures. By balancing customization and standardization through flexible approaches, companies can gain important insights into both upstream yield and downstream purification.
While prioritizing tropism and transgene expression is integral, focusing on other variables, such as cell density, packaging efficiency, incubation and hold time, stability, and impurity profiles, is critical to mitigating costs and improving efficiency. Enabling material interchangeability and working toward process standardization across as many serotypes as possible are key to the future of the cell and gene therapy space. Today, the proliferation of custom-built platforms for specific transgenes has created a flood of siloed, individualized processes, affecting cost, time to market, and manufacturing efficiency.
Optimizing viral vector yield also means right-sizing processes. Accurate lot sizing is critical to this optimization; the ability to operate at multiple scales, including sub-lot production sizes to minimize pooling, can reduce waste and lower production costs. This standardization can be elusive for some therapeutics. Still, for projects that can accommodate it, it can be an important tool for optimizing yield at a lower long-term cost. Many of the nuances in AAV production and scale-up can only be identified and addressed over multiple production runs. Manufacturer experience and standardization can be critical to avoiding unnecessary delays.
Future Trends in Standardizing Yields for Viral Vectors
The current AAV research landscape remains far from the standardization seen in other parts of the biopharmaceutical market because of the inherent variability of the biological process. The sheer volume of data needed to enable predictive analytics is still far off for many developers, most of whom work with highly proprietary, engineered serotypes in a highly competitive market. Achieving product equivalency will be critical to maturing the market in the coming years, and maturing the analytics behind it will be key to achieving that equivalency.
Variability among vectors is substantial, driven by the selected serotype and transgene, as well as factors such as genetic payload size and sequence, which can affect packaging, density, buoyancy, or affinity. Intersecting variables that inform AAV development, coupled with competition and evolving regulatory standards for these therapies, have made developing a standard approach difficult. This, along with interchangeability and a push for harmonization, represents the future of affordable, accessible AAV therapies.
Ultimately, partnering with a contract development and manufacturing organization (CDMO) that has expertise and platform technologies to balance a project’s customization and standardization can help companies avoid common AAV development pitfalls. Ensuring optimal yield for these therapeutics is complex but crucial, as many projects with immense therapeutic potential have been derailed by poor yield. In a market constrained by costs for both developers and end users, pursuing long-term advances in process standardization, data collection, and yield optimization will stabilize the space and enable more targeted therapies.
Viral vectors are more than a vehicle for a payload. Their ability to target specific cells has made them among the most promising treatment modalities to emerge in recent years. But the specificity enabled by this tropism has complicated scale-up.
Ensuring optimal yield for engineered viral vectors is crucial to their eventual commercial viability. Still, it's easy to overlook early yield drivers, resulting in suboptimal yields, rework, and the potential scrapping of an otherwise promising therapeutic. Often, yield issues are not uncovered until toxicology testing has begun, by which time considerable time and cost have already been invested in a transgene that, while effective, is production inefficient.
The heavy lifting inherent to cell and gene therapy contributes to the high production costs of these therapeutics and, commensurately, to the high cost to patients. Zolgensma, a gene therapy for spinal muscular atrophy, is the most expensive drug on the planet, averaging more than $2 million for a single dose. Driving down the cost of viral vector development is critical to making these life-changing therapies more accessible, enabling more targeted treatments across a wider range of diseases and improving quality of life.
The Variables that Impact Yield Optimization for Viral Vectors
Scientists have greatly advanced the field of engineered serotypes by fine-tuning epitopes and proteins to improve tropism, transduction, and specificity. In contrast, “wild serotypes,” such as rh74 orAAV9, have had over a billion years to optimize packaging efficiency, yielding superior production yields.
Another core focus of this research has been transgene development, with a particular emphasis on expression. Early in a product’s life cycle, the central question is how to design a transgene that achieves optimal expression within an already limited payload capacity. This is complex because some of that capacity is reserved for inverted terminal repeats (ITRs), promoters, poly(A) signals, and other features required to meet regulatory requirements. Therefore, the molecular development needed to produce a functional coding sequence with high expression that can be packaged in a tailored capsid is already difficult; ensuring yield may fall by the wayside because of this complexity.
Optimizing a yield profile early and then scaling with yield performance in mind can help companies meet productivity demands across the full product life cycle. Downstream purification losses average 50 to 70 percent for non-optimized processes. Ultra-centrifugation is a notorious source of product loss and a common workhorse step in purification; transitioning entirely to column purification could minimize that loss. But purification losses typically compound; while a discrete purification step may have an average 20 percent product loss, previous and subsequent steps with the same average loss will account for most of the product lost to purification when evaluated holistically. Some level of static, adsorptive loss is unavoidable at each step, but improving up-front yield can mitigate losses and improve downstream purification.
Mitigating Costs Through Standardized Platform Technology
Developers must understand that a product's yield profile can vary significantly by serotype and DNA sequence. Therefore, researchers must thoroughly screen transgenes, backbones, and serotype configurations to establish critical production parameters before selecting the best candidate for production and clinical performance. To do so, AAV candidates can be sent to a platform development lab with standardized processes, equipment, materials, and expertise to evaluate performance using a standardized Design of Experiments (DoE) study in adherent or suspension cultures. By balancing customization and standardization through flexible approaches, companies can gain important insights into both upstream yield and downstream purification.
While prioritizing tropism and transgene expression is integral, focusing on other variables, such as cell density, packaging efficiency, incubation and hold time, stability, and impurity profiles, is critical to mitigating costs and improving efficiency. Enabling material interchangeability and working toward process standardization across as many serotypes as possible are key to the future of the cell and gene therapy space. Today, the proliferation of custom-built platforms for specific transgenes has created a flood of siloed, individualized processes, affecting cost, time to market, and manufacturing efficiency.
Optimizing viral vector yield also means right-sizing processes. Accurate lot sizing is critical to this optimization; the ability to operate at multiple scales, including sub-lot production sizes to minimize pooling, can reduce waste and lower production costs. This standardization can be elusive for some therapeutics. Still, for projects that can accommodate it, it can be an important tool for optimizing yield at a lower long-term cost. Many of the nuances in AAV production and scale-up can only be identified and addressed over multiple production runs. Manufacturer experience and standardization can be critical to avoiding unnecessary delays.
Future Trends in Standardizing Yields for Viral Vectors
The current AAV research landscape remains far from the standardization seen in other parts of the biopharmaceutical market because of the inherent variability of the biological process. The sheer volume of data needed to enable predictive analytics is still far off for many developers, most of whom work with highly proprietary, engineered serotypes in a highly competitive market. Achieving product equivalency will be critical to maturing the market in the coming years, and maturing the analytics behind it will be key to achieving that equivalency.
Variability among vectors is substantial, driven by the selected serotype and transgene, as well as factors such as genetic payload size and sequence, which can affect packaging, density, buoyancy, or affinity. Intersecting variables that inform AAV development, coupled with competition and evolving regulatory standards for these therapies, have made developing a standard approach difficult. This, along with interchangeability and a push for harmonization, represents the future of affordable, accessible AAV therapies.
Ultimately, partnering with a contract development and manufacturing organization (CDMO) that has expertise and platform technologies to balance a project’s customization and standardization can help companies avoid common AAV development pitfalls. Ensuring optimal yield for these therapeutics is complex but crucial, as many projects with immense therapeutic potential have been derailed by poor yield. In a market constrained by costs for both developers and end users, pursuing long-term advances in process standardization, data collection, and yield optimization will stabilize the space and enable more targeted therapies.
