Two–cycle product development: Condensed clinical trials consisting of combined Phase I and II to assess safety, pharmacokinetics, and dose-dependent pharmacodynamics,
and Phase III to assess efficacy, instead of discrete Phase I, Phase II, and Phase III clinical studies.
Product development phase: Clinical trials leading to commercialization of a new drug are typically classified into three phases, each requiring regulatory
approval before proceeding to the next: Phase I assesses safety, tolerability, pharmacokinetics, pharmacodynamics, Phase II
assesses safety and dose-ranging efficacy in a larger population, and Phase III assesses definitive efficacy of the drug.
PD life-cycle stage: Structured approach to PD consisting of four stages of defined studies to address the needs of the given product development
phase and increase predictability of success at manufacturing scale. The stages are technical feasibility, development, optimization,
and confirmation or qualification.
Target process and product profile (TPPP): Detailed, desirable targets for process (e.g., titer and yield to meet manufacturing capacity and supply demand needs) and
for product (e.g., protein concentration, excipient, and product quality to meet the dose and administration route requirements
for the given patient population). Upon completion of PD optimization, the final (actual) process and product profile (PPP)
GAINING EFFICIENCY THROUGH TECHNOLOGY PLATFORMS
Although process technology platforms have been established for manufacturing monoclonal antibodies over the past two decades,
such benefit was not available for other protein products such as ERTs. This section summarizes the evolution and effect of
PD platforms established for these complex enzymes to accommodate accelerated development. Such platforms allowed efficient
PD and predictable scale-up performance.
Glycosylation is critical to targeting the cellular uptake of lysosomal enzymes and their localization into lysosomes, requiring
the development of platform process technologies to generate such highly glycosylated proteins. One of the systems used for
expressing these glycoproteins was a human cell line (2, 3). Expression in human cell lines required building knowledge to
improve titer, to grow cells in suspension, to control critical attributes, and thereby to increase production yields and
tighten process controls. The cell culture process changed from roller-bottle to bioreactor process, thus leading to increased
yields and better process control. The bioreactor cell-culture process could be conducted in either batch or perfusion mode,
depending on factors such as the stability of the enzymes in the culture media and the desired product output. Animal-derived
serum or plant hydrolysate initially used in the cell-culture media was later replaced with chemically defined media to ensure
consistent raw materials and control of the process. To this end, the cell lines were adapted from an attached line on roller
bottles to suspension culture, first on microcarriers, and eventually free of any carriers. These combined changes were implemented
over three years and consumed approximately 25 PD full-time equivalents to accomplish. Applying the cumulated process knowledge
to build process platforms led to efficiency in development time and lower cost.
Simultaneous measures for standardizing PD were introduced during the past eight years. Rapid screening of chromatographic
resins is now performed to more efficiently identify suitable resins and initial conditions. Although each process must be
adapted to the unique features of each enzyme, a standard purification process flow has been established; for example, an
initial capture step, one or more viral inactivation steps, chromatographic steps, and ultrafiltration or diafiltration steps.
In the purification area, small-scale models were developed to systematically learn about the effect of upstream and downstream
processes on product quality. To accommodate the large number of samples generated by the process groups, the analytical strategy
had to be revised. A decision was made to invest in robotics. Robots were subsequently adapted to perform analytical methods,
such as enzyme-linked immunosorbent assay and enzyme-activity assay determinations, at a throughput of approximately 2000
samples per week.
The organizational structure was changed to define a centralized unit dedicated to supporting PD testing, to remove the conflict
between development and routine testing activities. Systems were defined to accommodate sample-in, data-out for multiple projects
from multiple stakeholders. Such investment and restructuring allowed for an order of magnitude increase in the sample testing
throughput (see Figure 2). Additional automation was introduced in the bioassay development to speed up analytical optimization
while addressing the complexity and variability in such assays. The overall effect of the combined changes was a doubling
of PD capacity for developing multiple complex enzymes at a time.
Figure 2: Outcome of organizational redesign to enable faster process development (PD). Sample throughput was increased by
orders of magnitude by centralizing dedicated analytical resources to support process development and introducing robotics.
These changes enabled development of multiple products in a systematic and more efficient manner. This organizational redesign
freed up resources in cell culture and purification PD, allowing analysts to focus on process, and enhanced the efficiency
of the analysts by not requiring them to divide their time between development and routine testing priorities.
A key component of enhanced PD effectiveness was the technical problem-solving approach that provided feedback about gaps
between the desired and the actual performance at manufacturing scale. Basic knowledge about the process–product relationship
was gained during a decade of developing ERTs, initially through trial and error, later through using previous knowledge to
design small-scale or pilot-scale studies that would predict process performance and minimize rework at the manufacturing
scale. Specifically, a large-scale development laboratory at pilot scale was built to verify the lab-scale studies before
implementation at the manufacturing scale. Small-scale and pilot-scale studies to characterize the process and to define
the design space, process parameters, and process ranges also provided more efficient and effective mechanisms to resolve