How to Best Optimize Your Lyophilization Process Using Minimal Drug Substance

May 30, 2019

Source: AbbVie

By Jeff Tremain, Associate Director of Business Development, and Ted Tharp, Associate Director of Parenteral Science and Technology, AbbVie


Lyophilization is a complex and important process commonly utilized for the preservation of biopharmaceutical therapies. Lyophilization can often be resource-intensive requiring many labor hours, time, and investment, especially when working with certain classes of biologic drug substances.

Until recently, attempts at “optimizing” the lyophilization process were based on trial and error. This costly approach was rationalized by most biopharma and CDMO/CMO partners as a cost of doing business. In fact, in many biopharmaceutical manufacturing environments, pilot-scale trial and error based on know how is still commonplace and accepted as a starting point for many lyophilization processes. But, even in environments where the drug substance itself is inexpensive, the trial approach can add up to significant costs during the development phase of a product. Committing headcount, production facilities, and analytical services in early-stage product development with potentially long-drying cycles, may lead to both a lost batch and productivity. This inevitably disrupts pipeline progression and precludes more profitable and efficient manufacturing.

Scale-up and technology transfer of lyophilization processes remain a challenge. But recent data-driven advances in steady-state computer modeling and subsequent bench-scale lyophilization practices are having a positive impact on the optimization of lyophilization processes. Computational fluid dynamics and analysis of specific product, process, and laboratory equipment attributes allow us to model the entire lyophilization process in both laboratory and manufacturing environments. Those attributes include a broad range of factors, including formulation, critical temperatures, vial dimensions and fill volume, pressure, heat transfer and sublimation rates.

Modeling also allows one to distinguish and compensate for variables in equipment performance and design, as well as the impact of those variables on specific formulations and primary packaging. This produces an educated baseline before beginning to place product in the lyophilization chamber.

Resource Availability and Need for Lyophilization Modeling

In a supply-and-demand economy, scarcity breeds value. Subjecting product development to sub-optimal lyophilization approaches extends timelines, adds avoidable costs and delays getting the therapy into the patients’ hands.  Therefore, methodically approaching lyophilization with the right manufacturing partner is critical in overcoming the challenge of developing a scalable and repeatable lyophilization process for biologic drug substances.

That’s why modeling, followed by a bench-scale lyophilization exercise to confirm modeling data on a small  scale, proves  prudent as a critical pre-production first step. The benefits to the developer is that by taking a, preemptive bench-scale approach minimizes drug substance and associated costs required in the early stages.  Then once the product advances to larger scale GMP production, higher confidence is achieved around critical process parameters leading to efficiencies in drug substance utilization, optimized manufacturing capacity and appropriate allocation of supporting labor resources.

Mitigating Risk Against GMP Manufacturing Failure

There is pressure to advance through therapeutic development stages quickly to enable speed to market. A thorough understanding of requirements at the GMP stage are needed to develop a robust path to manufacturing which includes a mitigation plan especially for tasks identified on critical path. One such consideration may be the timing, availability and quantity of the bulk drug substance for larger scale lyophilization production runs. It is recommended to engage in an at-scale cycle using a surrogate suitable to demonstrate equivalency to the actual drug substance. By employing a surrogate, it can aid in the identification of physical integrity issues of the product, such as fogging in the vials ahead of utilizing the potentially scarce and costly bulk drug substance.

Modeling and bench-scale work demonstrate the impact of transfer from pilot to commercial scale manufacturing by enabling thorough characterization of the process and equipment, revealing performance attributes in advance of lyophilization of the final active drug substance at production scale quantities.

Reduce Manufacturing Costs Through Minimized Lyophilization Cycles

Again, with potentially limited quantities of expensive drug substance, some manufacturers choose conservative, longer approaches to lyophilization cycle time at the development stage. Longer lyophilization cycle times lead to additional  cost and a reduction of available capacity.

The modeling and bench-scale exercise creates an opportunity to optimize lyophilization cycle speed by determining the fastest freeze-drying rate that a formulation will safely and effectively tolerate without causing negative impact to the cake appearance, stability, and other product characteristics. This up-front knowledge speeds cycle times through subsequent at-scale manufacturing, typically late phase clinical and commercial runs, while further reducing the risk of failure by verifying lyophilization parameters from the start.

Accelerated Timeline for Fast-Track and Breakthrough FDA Status

The FDA is granting fast-track and breakthrough therapy status at record levels. In 2018, 29 fast-track designation requests were granted and a record 59 breakthrough designation requests were approved, up from 50, 46, and 32 the previous three years, respectively. As of March 2019, 22 breakthrough designation requests have already been approved, putting fiscal year 2019 on pace to surpass last year’s record.

With these designations comes an increased urgency and compressed timeline for commercial readiness. This urgency may accelerate the need for data-gathering, clinical production timelines and CMC readiness.

Fast-track and breakthrough designations make the efficiency gains and risk mitigation benefits of modeling and bench-scale lyophilization even more relevant to developers. They provide baseline process characterization that instills confidence in the likelihood of getting it right the first time, which in turn creates a foundation to meet accelerated clinical and commercialization time frames.

Will Computer Modeling and Bench-Scale Lyophilization Catch On?

Despite the demonstrable outcome of providing a pre-production baseline that mitigates risk, saves money, and speeds time to market, modeling and bench-scale lyophilization haven’t caught on industry-wide. In fact, a recent survey conducted by the BioPhorum Operations Group’s (BPOG’s) Lyophilization Workstream (of which AbbVie is a member) found that few drug developers and manufacturers are implementing modeling for scale-up and transfer. As recently as 2015, less than half of the major pharmaceutical manufacturers surveyed were leveraging modeling to optimize some level of the lyophilization process: process development (5 out of 11), scale-up and transfer (5 out of 11), process optimization (5 out of 11), deviation analysis and decision making (2 out of 11), and providing suitable feedback to regulatory authorities (1 out of 11). Though there was plenty of literature supporting its rationale, no modeling of the freezing step was reported by participating companies at the time.

The BPOG has been working collaboratively to change that, define best practices, and map out some standards in hopes of pushing wider adoption of modeling and bench-scale lyophilization.

Implementing Modeling and Bench-Scale Lyophilization in Your Development Process

Computer modeling and bench-scale lyophilization isn’t dependent on any proprietary science or technology. So, why isn’t it the standard for drug developers, particularly those working with low-quantity biologic drug substances? In short, because it adds both a level of complexity and time on the front end of product development. Despite the significant time, money, and risk mitigation benefits realized later in the process, it’s challenging for many to slow the development pace. If incorporated, the outcome of heat-transfer modeling can provide an understanding of how the formulation influences cake resistance, freeze-drier and drug substance interaction, impact of equipment scale and type to drive an optimized process.

Does the risk and potential to program delay outweigh the risks in long term robust manufacturing? In operations, it is highly preferred that manufacturing not be on the critical path to commercialization; yet striking the proper balance between speed and time to market is a decision that is best done on a program by program basis.  One input to that decision is that assessing the relatively small investment of upfront modeling time and effort, to drive the best payback of timely regulatory approval and commercial robustness.

Drug producers considering engaging an outsourced manufacturer for manufacturing and fill/finish work should contemplate the benefits of computer modeling and bench-scale lyophilization. Typically, the best time to explore those benefits are during or immediately following Phase 1 clinical trials, to ensure the CMO can fully engage with and benefit from Phase 1 data. This is also advantageous to the developer because pivotal studies outside of the commercial site result in the best chance of getting through development and closer to a commercial phase early in your trial.

Look to a CMO with computer modeling and bench-scale lyophilization experience. Even if you choose not to work it into your process now, suggest letting your qualified CMO share a bit about how it’s benefitted some of your peers on the path to commercial success.