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How do you keep cost of goods (COGs) for viral vector-based medicines within reason to develop a product that is both affordable and financially viable?  In this 3-part series we take a deep-dive into how in silico cost modelling is being used to pinpoint the cost-drivers in development and manufacturing of viral vector-based vaccines and therapies. We’ll explore how better and earlier cost assessment can help biopharmaceutical companies improve decision-making throughout the development process, establish more robust and financially sustainable manufacturing processes, and keep COGs under control.

From vectored vaccines to gene therapies to oncolytic agents, viral vectors are at the heart of many exciting scientific and medical breakthroughs. Yet companies in this sector face a difficult balancing act: how to keep these potentially life-changing treatments affordable for patients and payers, while still producing a product that is financially viable. The ongoing rapid expansion of markets and population sizes for viral-based treatments only intensifies the challenges, as manufacturers scramble to scale production capacity, often pushing traditional process technologies and facilities to their limits. In this high-stakes, high-pressure climate, success hinges on reaching new pinnacles of cost-efficiency and productivity in development and manufacturing of viral vectors.

Gene and cell therapies: harsh economic realities put COGs in the spotlight

Over the past decade, sky-high prices for emerging gene therapies have evoked public outcry.  At $1.2 million per patient, jaws dropped when Glybera was launched in 2012. Less than 3 years later uniQure and its European partner Chiesi withdrew it from the market amidst rumors that only a single dose had been sold for commercial use.[1] While the small patient base affected by this rare disease had a lot to do with the drug’s commercial implosion, high COGs were almost certainly part of the mix that made Glybera a losing proposition.

Thanks in large part to the adoption of innovative reimbursement schemes, more recent AAV1-based gene therapies such as Zolgensma for spinal muscle atrophy ($1.2m per dose) and Luxterna for inherited retinal disease ($425K/eye) have actually exceeded investor expectations, despite their higher price tags.[2],[3] Nevertheless, cost-effective manufacturing remains a challenge, and the spotlight on pricing practices and COGs contributions is not likely to fade anytime soon.

The trend towards higher doses for viral vector-based therapies is intensifying the need for greater cost-efficiency and economies of scale in clinical development and manufacturing. Take Sarepta Therapeutics’ investigational gene therapy for Duchenne’s Muscular Dystrophy, for example.  By some estimates, the cost of manufacturing a single dose of 8×1015 vg could be as high as $100,000 with conventional manufacturing platforms and facilities.[4] While such high COGs may not lead to an affordability crisis when targeting relatively small populations with one-time curative treatments, the commercial and logistical propositions become less tenable at larger scales.

As advances in cell and gene therapy technologies enable targeting of much larger patient populations and more mainstream markets, minimizing COGs and maximizing productivity will become even more crucial. Oncology-directed gene and cell therapies, for example, will have to compete with more traditional drugs, including biosimilars, in terms of pricing and cost-effectiveness.

COGs challenges in the vaccine industry – a different dynamic

The challenges and cost implications of large-scale production are already acutely felt in the vaccine industry. In developing and low-income countries, cost-per-dose and manufacturing capacity are major barriers to vaccine access.  Efforts to roll out rotavirus vaccines on a global scale are a good example.

Despite clear evidence that existing rotavirus vaccines can prevent fatal gastroenteritis, nearly 60 million children worldwide still lack access—most of them living in just 10 countries.[5] In the course of developing a scalable manufacturing process for an improved rotavirus vaccine, researchers estimated that COGs would need to be ≤$3.50 per course of three doses in order to meet predicted market requirements.[6] This is in stark contrast to more affluent cell and gene therapy markets, where bringing COGs of some AAV-based gene therapies down to $10,000 per dose would be seen as a significant achievement.[7]

The COVID-19 pandemic brings the need for more equitable global access to vaccines into sharp focus. With the realization that “no one is safe until everyone is safe,” the urgency of developing more scalable and cost-effective processes for manufacture of viral vector vaccines has never been greater.

Gaining insights with in silico cost modeling

Understanding how various technology and process choices will affect COGs is crucial to develop a robust, high-yielding and cost-effective manufacturing process.

Often the cost implications of these choices are discovered too late—after the clinical manufacturing process has been locked down. This can lead to delay approval in latter stages have devastating consequences for the development program.

In silico cost modeling of manufacturing processes is a powerful tool that can help product developers identify the main cost drivers early, so that they can make more informed, data-driven design decisions throughout the development process. In the next articles of this series, we’ll take a closer look at what cost modelling entails and the benefits it can bring to viral vector process development.

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